WHO SDG and UHC Baseline Report by Alexander Pascual

Monitoring Universal Health Coverage and Health in the Sustainable Development Goals Baseline Report for the Western Pacific Region 2017

© World Health Organization 2017 ISBN 978 92 9061 840 9 Some rights reserved. This work is available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO licence (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). Under the terms of this licence, you may copy, redistribute and adapt the work for non-commercial purposes, provided the work is appropriately cited, as indicated below. In any use of this work, there should be no suggestion that WHO endorses any specific organization, products or services. The use of the WHO logo is not permitted. If you adapt the work, then you must license your work under the same or equivalent Creative Commons licence. If you create a translation of this work, you should add the following disclaimer along with the suggested citation: “This translation was not created by the World Health Organization (WHO). WHO is not responsible for the content or accuracy of this translation. The original English edition shall be the binding and authentic edition”. Any mediation relating to disputes arising under the licence shall be conducted in accordance with the mediation rules of the World Intellectual Property Organization (http://www.wipo.int/amc/en/mediation/rules). Suggested citation. Monitoring universal health coverage and health in the sustainable development goals: baseline report for the Western Pacific Region 2017. Manila. World Health Organization Regional Office for the Western Pacific. 2017. Licence: CC BY-NC-SA 3.0 IGO. Cataloguing-in-Publication (CIP) data. 1. Conservation of natural resources. 2. Health priorities. 3. Universal coverage. I. World Health Organization Regional Office for the Western Pacific. (NLM Classification: WA528) Sales, rights and licensing. To purchase WHO publications, see http://apps.who.int/bookorders. To submit requests for commercial use and queries on rights and licensing, see http://www.who.int/about/licensing. For WHO Western Pacific Regional Publications, request for permission to reproduce should be addressed to Publications Office, World Health Organization, Regional Office for the Western Pacific, P.O. Box 2932, 1000, Manila, Philippines, Fax. No. (632) 521-1036, email: wpropuballstaff@who.int Third-party materials. If you wish to reuse material from this work that is attributed to a third party, such as tables, figures or images, it is your responsibility to determine whether permission is needed for that reuse and to obtain permission from the copyright holder. The risk of claims resulting from infringement of any third-partyowned component in the work rests solely with the user. General disclaimers. The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of WHO concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted and dashed lines on maps represent approximate border lines for which there may not yet be full agreement. The mention of specific companies or of certain manufacturers’ products does not imply that they are endorsed or recommended by WHO in preference to others of a similar nature that are not mentioned. Errors and omissions excepted, the names of proprietary products are distinguished by initial capital letters. All reasonable precautions have been taken by WHO to verify the information contained in this publication. However, the published material is being distributed without warranty of any kind, either expressed or implied. The responsibility for the interpretation and use of the material lies with the reader. In no event shall WHO be liable for damages arising from its use. Cover images. Goal 1 photo: © Yoshi Simishu, Goal 2 photo: © Pep Bonet / NOOR, Goal 4 photo: © 2013 Monsin De Los Reyes on Photoshare, Goal 5 photo: © Pep Bonet / NOOR

CONTENTS Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi Acknowledgements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Abbreviations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii Executive summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2. Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 SDGs and UHC Regional Monitoring Framework. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 3. Baseline: Health SDGs and UHC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Key findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.1 SDG 3: Good Health and Well-Being. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Reproductive, maternal, newborn and child health. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Infectious disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Noncommunicable Diseases (NCDs). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Urban and environmental health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Health system resources and capacity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.2 Health in other SDGs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Childrenâ&#x20AC;&#x2122;s health. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Urban and environmental health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Health system resources and capacity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.3 Universal health coverage (UHC). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Health system performance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.4 Equity-focused monitoring. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4. Equity analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Key findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 4.1 Reproductive, maternal, newborn and child health. . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.2 Noncommunicable disease (NCD) risk factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 4.3 Financial protection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 4.4 Case studies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Cambodia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Papua New Guinea. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 5. Regional relationships. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Key findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 5.1 Reproductive, maternal, newborn and child health. . . . . . . . . . . . . . . . . . . . . . . . . . 33 5.2 Infectious diseases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 5.3 Noncommunicable diseases (NCDs). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 5.4 UHC and health system performance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 6. Country profiles for SDGs and UHC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 7. Limitations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

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8. The way forward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Overall recommendations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Priority actions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix 1. Baseline values – SDG 3 and health-related indicators of the other SDGs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix 2. Baseline values for additional indicators of UHC. . . . . . . . . . . . . . . . . . . . . Appendix 3. Coverage of essential health services and an alternative health expenditure measure (as proxy for financial risk protection). . . . . . . . . Appendix 4. Equity analysis for reproductive, maternal, newborn and child health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix 5. Equity analysis – NCD risk factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix 6. Equity analysis – Papua New Guinea. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix 7. Reference list of 88 SDG and UHC indicators listed according to health system results chain (logic model). . . . . . . . . . . . . . . Appendix 8. Regional relationship analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Reproductive, maternal, newborn and child health. . . . . . . . . . . . . . . . . . . . . . . . . B. Infectious diseases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Noncommunicable diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

46 46 47 49 56 61 66 75 80 81 82 82 89 91

Tables Table 1. Key statistics from 27 Western Pacific countries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Table 2. Examples of indicators from the SDG and UHC Regional Monitoring Framework that measure quality and efficiency . . . . . . . . . . . . . . . . 20 Table 3. Examples of indicators from the SDG and UHC Regional Monitoring Framework that measure quality and safety, facility-level efficiency, and health service coverage and access. . . . . . . . . . . 21 Table 4. Commonly used stratifiers available in the SDG and UHC metadata. . . . . . . 23 Table 5. Examples of relationships following a logic model approach. . . . . . . . . . . . . . . 32 Table 6. Proposed disaggregation for under-5 mortality rate. . . . . . . . . . . . . . . . . . . . . . . 45

Figures Fig. 1. Fig. 2. Fig. 3. Fig. 4. Fig. 5. Fig. 6. Fig. 7. Fig. 8.

SDG and UHC Regional Monitoring Framework. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Number of indicators with missing baseline values, 27 Western Pacific countries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Country distribution of three SDG indicators where there is a specific 2030 target, 2015–2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Country distribution of TB incidence, hepatitis B incidence and number of people requiring interventions against NTDs, 2015–2016. . . . . . . . . . . . . . . . . . 9 Country distribution of prevalence of tobacco smoking and mortality related to chronic diseases, 2015. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Country distribution of road traffic mortality rate and mortality rate attributed to household and ambient air pollution, 2012–2013 . . . . . . . . 11 Country distribution of skilled health professional density and International Health Regulations core capacity, 2005–2016 . . . . . . . . . . . . 12 Health in other SDGs. Number of indicators with missing values, 27 Western Pacific countries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Fig. 9. Country distribution of three SDG indicators of malnutrition, 2005–2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Fig. 10. Country distribution of the proportion of population using improved drinking water and sanitation, 2015. . . . . . . . . . . . . . . . . . . . . . . 14 Fig. 11. Country distribution of government health expenditure, 2014 . . . . . . . . . . . . . 15 Fig. 12. Country distribution of coverage of UHC essential health services (SDG 3.8.1), target=100, 27 Western Pacific countries. . . . . . . . . . . . . . . . . . . . . . . 16 Fig. 13. Overall progress towards the delivery of UHC, 11 Western Pacific countries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Fig. 14. Overall progress towards the delivery of UHC, using a proxy measure for financial risk protection, 27 Western Pacific countries. . . . . . . . . . . . . . . . . . . 19 Fig. 15. DTP3 immunization coverage among 1-year-olds (%) by economic status (in quintile) and subnational region. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Fig. 16. Births attended by skilled health personnel (%) by economic status (in quintile) and subnational region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Fig. 17. Noncommunicable disease risk factors by place of residence, Cambodia, 2010. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Fig. 18. Proportion of the population with household expenditures on health exceeding 10% of daily per capita total household consumption or income (%), stratified by income quintile (based on draft estimates), 9 Western Pacific countries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Fig. 19. Tuberculosis case notification rates, and other indicators, by household poverty rates, Cambodia, 2010. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Fig. 20. Availability of medical supplies: percentage of months that facilities do not have shortage of any of selected essential supplies for more than one week in any month stratified by province, Papua New Guinea, 2011–2015, 22 provinces. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Fig. 21. Relationships between health spending, coverage of essential health services for reproductive, maternal, newborn and child health, and child mortality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Fig. 22. Relationships between service capacity and access, coverage of essential health services for infectious diseases and TB incidence . . . . . . . . 35 Fig. 23. Relationship between coverage of essential services related to infectious diseases and life expectancy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Fig. 24. Relationship between coverage of essential services for noncommunicable diseases and outcomes/impacts. . . . . . . . . . . . . . . . . . . . 37 Fig. 25. Relationship between coverage of essential services for noncommunicable diseases and outcomes/impacts (cont.). . . . . . . . . . . . 38 Fig. 26. Relationship between UHC service coverage index and life expectancy, 26 Western Pacific countries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Fig. 27. Correlation between 30-day hospital mortality and life expectancy, 33 OECD countries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Fig. 28. Per capita total health expenditure vs. coverage of essential health services. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Fig. 29. Per capita total health expenditure vs. life expectancy. . . . . . . . . . . . . . . . . . . . . 41 Fig. 30. Per capita total health expenditure vs. coverage of essential health services in three main focus areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

FOREWORD I am pleased to present Monitoring Universal Health Coverage and Health in the Sustainable Development Goals: Baseline Report for the Western Pacific Region 2017. The report is expected to serve as a benchmark for assessing progress in implementing the 2030 Agenda for Sustainable Development and actions towards universal health coverage (UHC) over the next 14 years. The report has three purposes. First, it describes the baseline situation for UHC and health in the Sustainable Development Goals (SDGs) in the Region, including equityfocused monitoring. Second, it introduces analyses, techniques and tools that can inform policy dialogue and policy-making. Finally, it highlights current limitations in monitoring the SDGs and UHC in an effort to inform future action plans and technical work in the Region. The report can serve as a guide, but is not a substitute for each countryâ&#x20AC;&#x2122;s own monitoring framework. Countries can use the report to identify priorities for action over the next 14 years, including areas where progress is needed and areas where further countryspecific analysis and review are required, as well as areas that currently have no data that can be used to assess progress. Countries can also use the report to foster dialogue on progress and to encourage knowledge-sharing and reciprocal learning both within countries and among countries at the regional level. In addition to presenting the regional baseline situation, the report highlights critical elements of monitoring, and it provides to those involved in monitoring a deeper appreciation of the complexities of the process, as well as practical knowledge and techniques for the systematic monitoring of the SDGs and UHC. Countries are expected to use this report as a benchmark not only to support their own monitoring efforts and activities, but to assist in the formulation of evidence-informed policies, programmes and practices targeting health system development.

Shin Young-soo, MD, Ph.D. WHO Regional Director for the Western Pacific

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

ACKNOWLEDGEMENTS This report was produced under the guidance of Dr Vivian Lin, Director of the Division of Health Systems at the World Health Organization (WHO) Regional Office for the Western Pacific, with the technical assistance of Dr Guillermo A. Sandoval, WHO consultant and Assistant Professor at the University of Toronto Institute of Health Policy, Management and Evaluation, and of Ms Navreet Bhattal, WHO consultant. The work also benefited from the contributions of Dr Stephen John Duckett of the Grattan Institute in Australia. Valuable contributions, comments and feedback were provided by the Health Intelligence and Innovation unit at the WHO Regional Office for the Western Pacific and by technical officers at the Regional Office, WHO country offices and WHO headquarters, as well as from experts from Member States.

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ABBREVIATIONS CRD chronic respiratory diseases CVD cardiovascular disease DHS Demographic and Health Survey DTP3 diphtheria-tetanus-pertussis FPM fine particulate matter GDP gross domestic product GIS geographic information system HEAT Health Equity Assessment Toolkit IHR (2005) International Health Regulations (2005) MDGs Millennium Development Goals MDR-TB multidrug-resistant tuberculosis MICS Multiple Indicator Cluster Survey NCDs noncommunicable diseases NTDs neglected tropical diseases OECD Organisation for Economic Co-operation and Development PPP purchasing power parity RMNCH reproductive, maternal, newborn and child health SDGs Sustainable Development Goals STEPS STEPwise approach to surveillance TB tuberculosis UHC universal health coverage WHO World Health Organization

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MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

EXECUTIVE SUMMARY Monitoring progress towards the Sustainable Development Goals (SDGs) and universal health coverage (UHC) is a priority in the World Health Organization (WHO) Western Pacific Region. It is a complex and demanding process that includes a wide range of activities from data collection and infrastructure to data transformation and analysis that can inform and drive policy change. This report, Monitoring Universal Health Coverage and Health in the Sustainable Development Goals: Baseline Report for the Western Pacific Region 2017, provides a starting point to support this process by providing countries with a first snapshot of the current SDG and UHC baseline situation in the Region. Countries can use the report to identify priority areas for action so that each country’s monitoring process can be aligned with these priority areas in order to accelerate progress towards the SDGs and UHC. The indicators for which values are reported in this baseline report are from the Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework for the Western Pacific. The Framework currently contains 88 indicators, including indicators for the main health goal (SDG 3), health-related indicators for the other SDGs and additional indicators to monitor UHC. The baseline values come from global estimates, where possible, compiled from data for 2010–2016, where available. The baseline values and regional aggregates in this report are from 27 Western Pacific countries; they do not include data from the areas (territories) in the Region. The current SDG and UHC situation is organized in four sections: Baseline, Equity Analysis, Regional Relationships and The Way Forward.

Baseline This section summarizes the baseline health situation relevant to the SDGs and UHC, including findings from equity-focused monitoring. Key findings include the following: –– Maternal and child mortality rates for the Region as a whole already are below the global 2030 SDG targets. However, within the Region there are wide country variations, with more Pacific island countries still above the global SDG targets. Regional demand for family planning satisfied with modern methods is at 90%. Nine countries are less than or close to halfway towards the target of 100%. –– Regional rates for infectious disease are lower than the global rates; however, some lower-middle-income countries have high tuberculosis (TB) incidence rates. –– All countries will face important challenges to reach the SDG targets for noncommunicable diseases (NCDs), given that the SDG Agenda calls for a one third reduction of premature deaths and of suicide mortality by 2030.

–– Regional premature mortality attributable to chronic disease is below the global rate. However, there is wide variation: in eight countries premature mortality from NCDs is at least 1.5 times higher than the regional value of 17.1% – that is, the probability of dying from any of cardiovascular disease (CVD), cancer, diabetes and chronic respiratory disease (CRD) between the ages of 30 and 70 years. –– The regional mortality rate attributed to household and ambient air pollution is 134 per 100 000 population, which is almost 50% higher than the global rate of 92. For the annual mean concentrations of fine particulate matter (FPM) in urban areas, the regional rate is higher than the global rate, influenced by the particularly high score for China. –– There is wide variation among countries on the adequacy of health system resources and capacity. –– With a target of 100, the UHC service coverage index (SDG 3.8.1) increases with a country’s income level; it is slightly higher in the Region’s Asian countries, compared to the Pacific island countries. –– Indicators for health system performance, particularly those for service quality, are not currently measured in any of the Region’s lower- and upper-middle-income countries. –– Equity-focused monitoring is largely unreported in the Region.

Equity analysis To demonstrate how countries can conduct equity analysis, this section focuses on three areas where data are available for selected countries in the Region. Key findings include the following: –– There appears to be widespread inequity across the Region in relation to access to health services, NCD risk factor prevalence, health status and financial protection. This means that a large number of people are still being “left behind”. –– There are well-known and continuing disparities between rich and poor, between urban and rural households, and across subnational regions. In some countries, subnational regions are clustered, leaving only some regions behind. –– The inequity situation for specific health issues varies substantially in different countries. Some countries have greater inequities, for example the Lao People’s Democratic Republic, while in others the inequities appear to be relatively less pronounced, for example Mongolia. –– The determinants of inequity also vary across countries and health issues. For example, place of residence may not be a contributing factor to inequity of immunization coverage in Viet Nam, while it appears to be an important factor in Cambodia, the Lao People’s Democratic Republic and Vanuatu. –– The limited availability of data to conduct equity analysis in the Region is a major barrier to progress towards the SDGs and UHC.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Regional relationships This section uses a logic model to organize some country-level indicators and explore their relationships in order to identify potential contributors to improved health. Key findings include the following: –– F or reproductive, maternal, newborn and child health, the analysis shows that a country’s resources and service capacity are positively associated with institutional deliveries, skilled birth attendance, and coverage of essential services for women and children. These factors, in turn, may potentially influence maternal and child mortality, child stunting, the adolescent birth rate, and ultimately life expectancy. –– For infectious diseases, the analysis shows a weakly positive association between a country’s resources and service capacity and coverage of essential services for TB and HIV as well as access to improved sanitation. Service coverage, in turn, was related to TB incidence and life expectancy. –– For NCDs, there is a weak relationship between a country’s resources and service capacity and its coverage of NCD-related services, as currently measured through proxy indicators for the status of NCD risk factors. However, coverage of NCDrelated services does show an inverse relationship with the probability of dying from chronic conditions, that is, premature mortality. –– The analysis shows a strong positive relationship between UHC service coverage and life expectancy. This suggests that improved coverage of essential health services may be associated with prolonged life expectancy for a country’s population.

The way forward The results of this baseline report were presented and discussed at a technical workshop in Manila in May 2017. The workshop used the report findings to help identify priority actions for Member States and WHO to improve SDG and UHC monitoring in the Western Pacific Region. The recommendations outlined here provide overall directions relevant to most countries. However, the specific action on each recommendation may differ according to each country’s stage of development.

Member States are encouraged: 1. to develop or finalize a country-specific SDG and UHC monitoring framework. Each country should identify the targets and indicators of highest priority, in light of the country’s characteristics, challenges and capacity to implement monitoring activities; 2. to actively engage in capacity development and training on multiple aspects of SDG and UHC monitoring, for example data collection processes, flows and standards, data analysis, target setting, and evidenced-informed policy-making; 3. to strengthen the national health information system by creating a national coordinating body able to harmonize monitoring-related aspects and activities with other ministries, provincial or district-level governments, agencies and the private sector; and

4. to invest in fundamental health information infrastructure and tools by introducing innovative, direct and indirect forms of incentives so that unfragmented and coordinated health and health-related data and information systems are available at all levels.

WHO in the Western Pacific Region will: 1. provide technical support and assistance to countries on multiple aspects of SDG and UHC monitoring by: a. guiding all technical work related to indicator development, selection and analysis, including guidance on effective methods to capture information on those at risk of being left behind; b. facilitating the adoption of common standards and a common framework to enable comparative analysis and sharing of lessons learnt; c. undertaking analysis of available data related to the SDGs and UHC and using this analysis to inform technical assistance to countries as well as for regional and comparative reporting; d. providing training to countries and producing training materials, including a minimum set of indicators for which data should be collected (for example, tracer indicators), guidelines on data analysis, target setting and reporting to support policy-making, and reporting templates; e. continually updating indicator metadata and the communication and dissemination of its use; and f. guiding the use of global estimates vs. country-reported values in SDG and UHC monitoring; and 2. provide more effective country support through: a. better partner and interagency coordination and collaboration; b. higher-level advocacy and awareness; and c. better communication among the WHO Regional Office, WHO country offices, and ministries of health and ministries of foreign affairs.

xii

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

INTRODUCTION

The World Health Organization (WHO) Regional Office for the Western Pacific has prepared this report, Monitoring Universal Health Coverage and Health in the Sustainable Development Goals: Baseline Report for the Western Pacific Region 2017, to support Member States as they guide, monitor and review their progress towards the healthrelated targets of the Sustainable Development Goals (SDGs) and the achievement of universal health coverage (UHC). The report describes the Western Pacific Regionâ&#x20AC;&#x2122;s current baseline situation, including the level of equity focus, and presents the results of analyses that countries may consider when incorporating SDG and UHC monitoring into their policy- and decision-making. This baseline report is a starting point for cross-country comparisons and to foster dialogue, knowledge sharing and reciprocal learning, both within and among countries. Each country can use the report to identify action priorities, according to its own unique characteristics, challenges and capacity to drive change. The report is based on global estimates wherever possible. This means that indicator values have been computed using standardized categories and methods to aid crossnational comparability. This approach may have resulted in some differences between WHO estimates presented in this report and official national statistics prepared and endorsed by individual Member States. Some estimates have large confidence intervals and are subject to uncertainty, especially in countries with weak information systems and where the quality of empirical data is limited. The report contains eight chapters. Following this Introduction, Chapter 2 provides background information on regional work conducted and briefly describes the framework for reporting the regional baseline situation. Chapter 3 summarizes the baseline situation for health in the SDGs and for UHC in individual countries. Chapter 4 demonstrates how countries can conduct equity analyses, focusing on the three main areas where there are suitable data for several countries in the Region. Chapter 5 presents regional relationships of the multiple factors that may be associated with improved health in the areas of reproductive, maternal, newborn and child health (RMNCH), infectious disease, noncommunicable diseases (NCDs) and injuries, and UHC. Chapter 6 describes WHO work to build country profiles, and Chapters 7 and 8 discuss the limitations of the baseline and recommended actions and technical work to improve regional monitoring of the SDGs and UHC. Complete tables of baseline values, including regional and global rates, are in Appendices 1 and 2, organized according to the domains of the Framework for Monitoring SDGs and UHC in the Western Pacific Region.

The baseline values and regional aggregates presented in this report are from 27 countries in the Western Pacific Region; they do not include data from the areas (territories) in the Region. Table 1 summarizes some key statistics from each of the 27 countries. Table 1. Key statistics from 27 Western Pacific countries Member State Year

Population

GDP per capita (current US$)

Total health expenditure as percentage of GDP

Total health expenditure per capita (current US$)

Life expectancy at birth

2016

2014–2016

2010–2014

2006–2015

Asian countries Australia Brunei Darussalam Cambodia China Japan Lao People’s Democratic Republic Malaysia Mongolia New Zealand Philippines Republic of Korea Singapore Viet Nam

24.1 m 423 196 15.8 m 1378.7 m 127 m 6.8 m 31.2 m 3.0 m 4.7 m 103.3 m 51.2 m 5.6 m 92.7 m

49 928 26 939 1270 8123 38 895 2353 9503 3687 39 427 2951 27 539 52 961 2186

9.4 2.6 6.3* 5.5 10.2 2.8** 4.2 4.7 11 4.7 7.4 4.9 7.1

6031 958 69* 420 3703 35.5** 456 195 4896 135 2060 2752 142

82.8 77.7 68.7 76.1 83.7 65.7 75.0 68.8 81.6 68.5 82.3 83.1 76.0

Pacific countries Cook Islands Fiji Kiribati Marshall Islands Micronesia (Federated States of) Nauru Niue Palau Papua New Guinea Samoa Solomon Islands Tonga Tuvalu Vanuatu

20 800 898 760 114 395 53 066 104 937 13 049 1600 21 503 8.1 m 195 125 599 419 107 122 11 097 270 402

15 324 5153 1449 3449 3069 7821 15 608 13 626 2183 4028 2006 3689 3084 2861

3.4 4.5 10.2 17.1 13.7 3.3 7.4 9 4.3 7.2 5.1 5.2 16.5 5

518 204 154 625 415 516 1162 1150 92 301 102 213 633 158

76.4 69.9 66.3 71.8 69.4 61.2 73.2 62.9 74.0 69.2 73.5 69.6 72.0

GDP = Gross domestic product, m = millions * Cambodia National Health Accounts Report, 2014. ** Lao People‘s Democratic Republic National Health Accounts Report, 2011/2012. Sources: World Development Indicators, World Bank; Global Health Observatory, WHO; Global Health Expenditure Database, WHO; National Minimum Development Indicator, Secretariat of the Pacific Community.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

BACKGROUND

The Western Pacific Region, one of the six WHO regions, is home to nearly 1.9 billion people, more than one quarter of the world’s population. Beginning in 2000, the Region made great progress towards the Millennium Development Goals (MDGs), achieving all but two of the health-related MDG targets and making significant progress towards the two goals that were not reached. In 2015, the regional framework, Universal Health Coverage: Moving Towards Better Health, was endorsed by the Regional Committee for the Western Pacific. In October 2016, the Regional Committee endorsed the Regional Action Agenda on Achieving the Sustainable Development Goals in the Western Pacific. The Agenda suggests practical options for Member States to consider in the transition from the MDGs to the SDGs, based on each country’s own context, resources and entry points. The Agenda also urges a broader and more integrated approach to the many factors that shape health in different environments and suggests ways of identifying and responding to the most pressing needs of communities to ensure that no one is left behind. All Member States have agreed that UHC is a core part of the 2030 Agenda for Sustainable Development, which brings together various health and development efforts. Leaving no one behind is core to both UHC and the SDGs. In May 2017, the WHO Regional Office for the Western Pacific held a three-day technical workshop for participants from countries in the Western Pacific Region and temporary advisers, with observers from partner agencies. The workshop included a presentation and discussion of a preliminary summary of the baseline situation for health in the SDGs and UHC, including equity-focused information, helping countries to appreciate the complex issues and processes involved in SDG and UHC monitoring, and the sharing of practical knowledge and techniques for monitoring. Issues were raised and discussed in the context of each country’s challenges and needs, and specific priorities for action were highlighted.

SDGs and UHC Regional Monitoring Framework The Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework for the Western Pacific was endorsed at the sixty-seventh session of Regional Committee in October 2016. The Framework builds on extensive work conducted over the last decade at the global, regional and national levels. It captures the breadth of the SDG agenda and the multidimensional perspective of UHC.

The Framework is made up of four overarching monitoring domains, within which are 17 indicator domains, comprising a total of 88 indicators (Fig. 1). Of these 88 indicators, 27 fall under SDG 3 which is the health-focused goal, 20 are from other SDGs and 41 are to monitor progress towards UHC. The Framework sets out the priority areas to guide action over the next 14 years, up to 2030. Each country is expected to use these indicators as a reference in conducting its own regular monitoring and review, guided by its national health policies, priorities and strategies, and according to its own monitoring capacity. The use of the monitoring and indicator domains is flexible. Each Member State should select those domains that best suit its priorities and use them to build its own monitoring frameworks or models, or overlap them with existing frameworks or models. Fig. 1. SDGs and UHC Regional Monitoring Framework (4 Monitoring Domains and 17 Indicator Domains)

HEALTH IMPACT THROUGH THE LIFE COURSE

DETERMINANTS OF HEALTH

INDIVIDUAL HEALTH

POPULATION HEALTH

Are these factors contributing to good health?

Indicator Domain 1. Physical environment factors 2. Individual characteristics and behaviours 3. Socioeconomic factors 4. Social environment factors

UNIVERSAL HEALTH COVERAGE

Are all people accessing needed services without suffering financial hardship?

Indicator Domain 1. Financial protection 2. Health service coverage 3. Accessibility and use

HEALTH SYSTEM RESOURCES AND CAPACITY Indicator Domain 1. Effectiveness 2. Quality and safety 3. Responsiveness and peoplecentredness

Does the system deliver value for money and is it sustainable? 4. 5. 6. 7.

Resources and infrastructure Availability and readiness Health financing Efficiency and sustainability

MULTIPLE POPULATION GROUPS (EQUITY-FOCUSED MONITORING)

Indicator Domain 1. Mortality 2. Morbidity 3. Life expectancy and wellbeing

How healthy are people in the Western Pacific?

Source: Adapted from the Framework agreed to at the sixty-seventh session of the Regional Committee of the Western Pacific in October 2016.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

BASELINE: HEALTH SDGs AND UHC

This section provides a summary of the baseline situation for health based on the indicators in the SDGs and UHC, including equity-focused monitoring. The complete list of baseline values, including regional and global rates, is in Appendices 1 and 2 and is organized according to the domains of the Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework. To facilitate interpretation of the regional baseline situation, however, the indicators are grouped and reported under specific health topics in the main body of the report, for example communicable disease and urban and environmental health. Most of the baseline values have been estimated using data from 2010Ââ&#x20AC;&#x201C;2016 and are reported at the country level. For an overall assessment of UHC in individual countries, the report also combines data on the coverage of essential health services with information on financial risk protection.

Key findings zz

The current performance of the Western Pacific Region, as measured by the seven indicators of reproductive, maternal, newborn and child health (RMNCH), is better than the overall global performance. For maternal and child mortality, the regional rates are already below the global 2030 SDG targets. The Region has reached 90% of the target for demand for family planning satisfied with modern methods. However, 12 of the 27 Member States are still above the global target for maternal and child mortality, and nine countries are less than or close to halfway towards the target of 100% in demand for family planning satisfied with modern methods. While the regional rates for infectious disease are lower than the global rates, some lower-middle-income countries report high tuberculosis (TB) incidence rates. For NCDs, regional premature mortality attributable to chronic disease is below the global rate. However, there is wide variation: in eight countries, premature mortality from NCDs is at least 1.5 times higher than the regional value of 17.1%, that is, the probability of dying from any of cardiovascular disease (CVD), cancer, diabetes and chronic respiratory disease (CRD) between the ages of 30 and 70 years. The prevalence of male smoking (age 15 and above), which is much higher than female smoking prevalence, ranges from 17â&#x20AC;&#x201C;64%. The regional mortality rate attributed to household and ambient air pollution is 134 per 100 000 population, which is almost 50% higher than the global rate of 92. For the annual mean concentrations of fine particulate matter (FPM) in urban areas, the regional rate is higher than the global rate, influenced by the particularly high score for China.

There is wide variation among countries on the adequacy of health system resources and capacity. The Region outperforms global rates for eight health-related SDG indicators. However, eight countries have extremely high values for child malnutrition. The UHC service coverage index increases with the income levels of countries, and is higher in Asian countries. Twelve countries, however, have scores below 60 points for the UHC service coverage index. Most of these lean towards a lower risk of financial hardship, which may actually mean increased financial barriers to access or unavailability of quality health services. The UHC index does not capture the quality of the health services provided, nor other essential attributes of high-performing health systems such as the processes of accessing and delivering services. The Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework proposes additional indicators to measure some of these attributes, but the relevant data are largely lacking, particularly in the domains of quality and safety, responsiveness and patient centredness, and efficiency and sustainability.

3.1 SDG 3: Good Health and Well-Being Baseline values are available for 25 of the 27 indicators under SDG 3 (Table A, Appendix 1). There is no data for indicator 3.5.1 (coverage of treatment interventions for substance use disorders) and 3.b.3 (the proportion of health facilities having a core set of relevant essential medicines available and affordable on a sustainable basis). For indicators 3.3.4 (hepatitis B incidence) and 3.b.1 (vaccination coverage), proxy (alternative) indicators are reported. For most indicators there are some missing values, with only 10 indicators having complete data for all 27 countries (Fig. 2). In addition to two indicators with no data, there are three indicators for which more than 50% of the countries did not report data. For example, data on new HIV infections among adults are only available in seven of the 27 Western Pacific countries, in other words 20 have missing values. Fig. 2. Number of indicators with missing baseline values, 27 Western Pacific countries 12

Number of indicators

10 8

8 6

3 2

2 0 Complete data

Up to 7 countries with missing values

8â&#x20AC;&#x201C;13 countries with missing values

Number of countries with missing values Source: WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

14â&#x20AC;&#x201C;26 countries with missing values

No countries with baseline data

Reproductive, maternal, newborn and child health The current performance of the Western Pacific Region, as measured by the seven indicators of RMNCH, is better than the overall global performance. The regional rates for maternal and child mortality are already below the 2030 SDG targets (Fig. 3), and the Region is close to the 2030 target on demand for family planning satisfied with modern methods. The Region also performs well on some indicators for which there is no specific target. For example, the regional baseline value for adolescent births is 15 births per 1000 women aged 15â&#x20AC;&#x201C;19 years compared to 44 globally, and for skilled birth attendance the regional baseline is 96% compared to 78% globally. Immunization coverage for three doses of diphtheria-tetanus-pertussis vaccine (DTP3) for 1-year-old children is currently 97% in the Region and 86% globally. However, there is wide variation across individual countries. For the indicators on maternal and child mortality, all high-income countries and half of upper-middleincome countries have already achieved the global 2030 SDG targets. These countries must now focus on ensuring that improvement continues and that these gains in mortality reach the poor and disadvantaged so that no one is left behind. On the other hand, most lower-middle-income countries are above the global 2030 SGD targets for maternal and child mortality. For the Lao Peopleâ&#x20AC;&#x2122;s Democratic Republic and Papua New Guinea, major efforts will be required to achieve the 2030 SGD targets. Maternal mortality in these two countries is close to or above 200 deaths per 100 000 live births. They will need to show improvement of about 7% per year over a 15-year period to reach the global target of 70 deaths per 100 000 live births. Fig. 3. Country distribution of three SDG indicators where there is a specific 2030 target, 2015â&#x20AC;&#x201C;2016

250

Maternal mortality ratio (per 100 000 live births)* Global

200

Under-5 mortality rate (per 1000 live births)**

50 150

100

30 Target

Region

25 Global

Target

Region

Asia

Pacific

Global

Target

10 Region

Neonatal mortality rate (per 1000 live births)**

0 Asia

Pacific

Asia

Pacific

* 21 countries. The target of 70 deaths per 100 000 live births is a global target and not necessarily the target for each individual country. ** 27 countries. The targets of 25 deaths per 1000 live births for under-5 mortality and 12 deaths per 1000 live births neonatal mortality are global targets aiming at every country. Source: WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division

Baseline: Health SDGs and UHC

Most lower-middle-income countries have baseline data for the indicator “demand for family planning satisfied with modern methods”. These countries are on average halfway towards the target of 100%. Countries needing significant improvement include Kiribati, Nauru, Papua New Guinea, Samoa, Tonga, Tuvalu and Vanuatu, all with current values at 50% or lower for this indicator. There is no specific target for skilled birth attendance, although it is considered essential to reaching the 2030 global goal of reducing the maternal mortality ratio (SDG 3.1). Two countries will require major efforts to improve their current rates. In the Lao People’s Democratic Republic and in Papua New Guinea, 40–55% of births are attended by skilled health personnel, compared to 96% for the Region as a whole. All the other 25 countries have skilled birth delivery rates of over 70%, with 20 having rates over 90%. For these countries, future efforts should ensure that no one is left behind. Similarly, while a low rate is clearly preferable, there is no specific target rate for adolescents giving birth. SDG 3.7 aims for universal access to sexual and reproductive health services by 2030. Five Member States have adolescent birth rates of more than four times the current regional rate of 15.3 births per 1000 women aged 15–19 years. They are the Lao People’s Democratic Republic, the Marshall Islands, Nauru, Solomon Islands and Vanuatu. On average, these countries would need to reduce the adolescent birth rate by about 11% per year over a 15-year period to reach the current regional adolescent birth rate.

Infectious disease Although there are no targets for prevalence or incidence of specific infectious diseases, the 2030 goal is to end the epidemics of AIDS, TB, malaria and neglected tropical diseases (NTDs), as well as to combat hepatitis, waterborne diseases and other communicable diseases (SGD 3.3). The current performance of the Western Pacific Region on the incidence of infectious diseases is better than the global performance, but again with wide variation at the country level. The rate of new HIV infections among adults is five times higher in Papua New Guinea and three times higher in Malaysia and Viet Nam than the current regional rate of 0.1 new HIV infections among adults 15–49 years old per 1000 uninfected population. The incidence of TB in all high-income countries1 is below the regional rate of 95 cases per 100 000 population. However, some lower- and upper-middle-income countries report TB incidence higher than the regional rate (Fig. 4). Countries with particularly high incidence include Cambodia, Kiribati, the Marshall Islands, Papua New Guinea and the Philippines, with incidence above 300 cases per 100 000 population in 2016. These countries, on average, would need to reduce the incidence by about 8% per year over a 15-year period to reach the current regional incidence rate. Two lower-middle-income countries, Cambodia and the Lao People’s Democratic Republic, report malaria incidence rates of four to seven times the regional rate of 3.1 cases per 1000 population at risk. Whereas Papua New Guinea and Solomon Islands have incidence rates 40 and 22 times the regional rate, respectively. 1

With the exception of Palau.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

This report presents a proxy measure for hepatitis B incidence: the percentage of infants receiving three doses of hepatitis B vaccine (Fig. 4). For this indicator, 22 of the 27 countries reported over 75% coverage and 16 countries reported over 90%. These high-coverage countries should now focus on ensuring that no infant is left behind, and that immunization coverage reaches every part of the country. Four countries have coverage below 75%. These are the Marshall Islands, Papua New Guinea, Samoa and Vanuatu, with coverage ranging from 55–74%. Fig. 4. Country distribution of TB incidence, hepatitis B incidence* and number of people requiring interventions against neglected tropical diseases (NTDs), 2015–2016

600

TB incidence (per 100 000 population)**

100

Region

500

Global Global

400

300

Region

10 1 0.1

0.01

40 Asia

Pacific

10 000

100

Global

100

100 000

1000

200

Reported number of people requiring interventions against NTDs (in thousands)**

Infants receiving three doses of hepatitis B vaccine (%)***

0.001 Asia

Pacific

Asia

Pacific

* A proxy measure is reported in this report. ** 27 countries *** 26 countries Source: WHO

Regarding NTDs, it is estimated that 90.7 million people in the Region require interventions. Three countries in the Region account for almost 84% of the regional total (90.7 million). They are the Philippines (43.4 million), China (26.1 million) and Papua New Guinea (6.4 million). These are followed by Cambodia with 5.6 million and Viet Nam with 4.5 million people requiring NTD interventions.

Noncommunicable Diseases (NCDs) SGD 3 has four indicators related to NCDs. The two outcome-related indicators are premature mortality from NCDs and suicide mortality. The current performance of the Western Pacific Region on premature mortality from NCDs is better than the global performance (Fig. 5). However, in eight countries, premature mortality from NCDs is at least 1.5 times higher than the regional value of 17.1%, that is the probability of dying from any of CVD, cancer, diabetes and CRD between age 30 and 70. They include the lower-middle-income countries: Fiji, Kiribati, the Lao People’s Democratic Republic, the Federated States of Micronesia, Mongolia, Papua New Guinea, the Philippines and Solomon Islands. The situation for suicide is different. The performance of the Region is similar to the global performance. In 2015, most lower- and upper-middle-income countries had rates lower than the regional rate of 10.8 deaths per 100 000 population, while four high-income countries are above the regional rate. These are Australia (11.8), Japan (19.7), New Zealand (12.6) and the Republic of Korea (28.3 deaths per 100 000 population).

Baseline: Health SDGs and UHC

The SDG 2030 target is to reduce these rates by one third. For the Region, this means 11.4% for premature mortality from NCDs and 7.2 suicide deaths per 100 000 population. Regional improvement of 2.5â&#x20AC;&#x201C;3.0% per year will be required over a 15-year period to reach these targets, and each country will also have to reduce its current rates of premature mortality and suicide mortality by one third. The other two NCD indicators are for risk factors in people aged 15 years and over: harmful use of alcohol and the prevalence of tobacco smoking. In 2016, countries with the highest per capita alcohol consumption in the Region were Australia at 11.2, New Zealand at 10.1 and the Republic of Korea at 11.9. There is no specific target for reduction of the harmful use of alcohol, but the 2030 goal focuses on strengthening prevention and treatment (SDG 3.5). Fig. 5 presents the distribution of the prevalence of tobacco smoking in the Region. In almost every country, tobacco smoking prevalence is higher among males than females. Fig. 5. Country distribution of prevalence of tobacco smoking and mortality related to chronic diseases, 2015

Age-standardized prevalence of tobacco smoking among persons 15 years and older (%)*

Probability of dying from any of CVD, cancer, diabetes, CRD between age 30 and exact age 70 (%)** 40

Global

Region

10 0

5 Male

Female Asia

Male

Female

Asia

Pacific

* 19 countries ** 21 countries CVD = cardiovascular disease, CRD = chronic respiratory disease Source: WHO

With the exception of Australia, New Zealand and Niue, male smoking is high in the Western Pacific Region, ranging from about 30% to more than 60%. Countries with the highest rates of tobacco smoking in the Region include China, Kiribati, the Lao Peopleâ&#x20AC;&#x2122;s Democratic Republic, Mongolia, the Republic of Korea, Tonga and Viet Nam, all with smoking rates close to or above 50% in the male population aged 15 and above. For these countries, reductions of as much as 3.2% per year in male prevalence will be needed to reduce smoking rates to levels similar to Australia, New Zealand or Niue. The prevalence of female smoking is particularly high in Kiribati and Nauru at 41% and 52%, respectively. For the most part, however, female smoking prevalence in the Region is below 15%. Although there is no specific target for prevalence of tobacco use, the 2030 goal focuses on strengthening the WHO Framework Convention on Tobacco Control in all countries.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Urban and environmental health The remaining four mortality indicators in SDG 3 relate to road traffic accidents, pollution and contamination. In 2013, countries with particularly high road traffic mortality rates included Malaysia, Cook Islands and Viet Nam, all at an estimated 24 deaths per 100 000 population. Countries with very low rates included Kiribati, the Federated States of Micronesia and Singapore, all at an estimated 4 or less deaths per 100 000 population. The SDG target is to reduce the global rate by half. Fig. 6. Country distribution of road traffic mortality rate and mortality rate attributed to household and ambient air pollution, 2012–2013

Road traffic mortality rate (per 100 000 population)*

Mortality rate attributed to household and ambient air pollution (per 100 000 population)** 180

160 140

20 Global Region

Region

120 100

Global

80 10

60 40

20 0

0 Asia

Pacific

Asia

Pacific

* 24 countries ** 16 countries Source: WHO

There is no specific target for the pollution and contamination indicators. However, the 2030 goal (SDG 3.9) is to “substantially reduce” the number of deaths and illnesses from hazardous chemicals and air, from water and soil pollution, and from contamination. The regional mortality rate of 134 per 100 000 population attributed to household and ambient air pollution is particularly high, compared to the global rate of 92. The countries with the highest rates are China and Mongolia, with rates of 161 and 132 deaths per 100 000 population, respectively. Countries with mortality rates close to or higher than 80 deaths per 100 000 population include Fiji, the Lao People’s Democratic Republic, the Philippines and Viet Nam. To reach even the current global mortality rate, the Region would need to decrease its current rate by approximately 2.5% per year over a 15-year period. The baseline regional value of the indicator of mortality attributable to unsafe water, unsafe sanitation and lack of hygiene is 0.8 deaths per 100 000 population, which is significantly lower than the global value of 12.4, again with wide variation across countries. Cambodia, the Lao People’s Democratic Republic, Papua New Guinea and Solomon Islands have estimated values at least seven times the regional value. The regional mortality rate for unintended poisoning is estimated at 1.4 deaths per 100 000 population, which is close to the global rate of 1.5. With the exception of China, Kiribati, Mongolia and Papua New Guinea, all countries in the Region are below the regional rate.

Baseline: Health SDGs and UHC

Health system resources and capacity The net regional official development assistance totalled US$ 0.2 per capita in 2014, which is well below the global assistance value of US$ 1.2 per capita. Countries receiving the highest amounts were Vanuatu at US$ 22, Fiji at US$ 12, Tuvalu at US$ 11, Nauru at US$ 9.80 and Solomon Islands at US$ 9.40. The other two indicators measuring health system resources and capacity in the Region are the density of skilled health professionals and a score for International Health Regulations (2005), or IHR (2005), core capacity (Fig. 7). There are no specific targets for these indicators. However, the 2030 goals stress the need for a substantial increase in health financing, in recruitment and retention of the health workforce, and improved capacity to manage national and global health risks. Based on the years 2005–2015, the regional density of skilled health professionals was 42.0 per 10 000 population, compared with 45.6 globally. Similarly, based on 2010–2016 data, the Region had an IHR (2005) core capacity score of 79 compared with 73 globally (target=100). Fig. 7. Country distribution of skilled health professional density and International Health Regulations core capacity, 2005–2016

Average of 13 International Health Regulations core capacity scores**

Skilled health professionals density (per 10 000 population)* 100

180 160

140

Global

100

80 60

Global

Region

20 0

Region

120

Asia

Pacific

60 50 40

Asia

Pacific

* 26 countries ** 27 countries Source: WHO

Countries with relatively low density of skilled health professionals include Cambodia, the Lao People’s Democratic Republic and Papua New Guinea, all with 11 or fewer professionals per 10 000 population. Countries with a relatively high density of skilled health professionals include Australia, Brunei Darussalam, Japan, New Zealand and Niue, with rates close to or above 100 per 10 000 population. These countries will need to ensure that health personnel are equally distributed across the population so that no one is left behind. In terms of IHR (2005) core capacities, countries with very low values include the Marshall Islands, Nauru and Vanuatu, each with an index score close to or below 50. In contrast Australia, China, Fiji, Japan, Malaysia, New Zealand, the Republic of Korea, Singapore and Viet Nam each have a score close to 100. The current regional average is 79. To reach a regional score of 100 by 2030, will require an average increase of 1.6% per year. Countries that have already reached high levels of IHR (2005) core capacities must plan to sustain these gains. 12

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

SDG 3 includes two indicators for UHC: indicator 3.8.1 is the coverage of essential health services, and indicator 3.8.2 is financial risk protection. Section 3.3 below describes these indicators in greater detail and provides an overall assessment of the current state of individual countries on UHC.

3.2 Health in other SDGs There are currently 20 health-related indicators under the SDGs other than SDG 3, of which baseline values are available for 16 (see Table B, Appendix 1). For six of these 16 indicators, proxy (alternative) indicators are reported. The four indicators without data fall under the indicator domains of social environment factors, and responsiveness and patient centredness. There are missing values for most indicators; only two indicators have data for all 27 countries (Fig. 8). Fig. 8. Health in other SDGs. Number of indicators with missing values, 27 Western Pacific

Number of indicators

countries

10 9 8 7 6 5 4 3 2 1 0

7 5 4 2

Complete data

Up to 7 countries with missing values

8–13 countries with missing values

14–26 countries with missing values

No countries with baseline data

Number of countries with missing values Source: WHO

Children’s health Three indicators report on child malnutrition under SDG 2.2, which aims to end all forms of malnutrition by 2030. A significant difference is observed in the prevalence of stunting in children under 5 years, where the regional rate is 7.0% compared with 22.9% globally. Despite the seemingly low regional average, some countries report significantly high prevalence of stunting in this age group. They include Papua New Guinea at 49.5%, the Lao People’s Democratic Republic at 43.8%, Solomon Islands at 32.8%, Cambodia at 32.4%, the Philippines at 30.3% and Vanuatu at 28.5%. Fig. 9 presents the country distribution of this indicator and the other two malnutrition-related indicators: wasting and overweight. Some countries reported high values for the prevalence of wasting in children under 5. Compared with the regional value of 2.4%, Papua New Guinea reported 14.3% and Cambodia close to 10%. Malaysia followed with 8.0%, the Philippines with 7.9% and the Lao People’s Democratic Republic and Viet Nam with 6.4%. The prevalence of overweight in children under 5 is 5.2% in the Region and 6.0% globally. High values for overweight prevalence are reported for Tonga at 17.3%, Papua New Guinea at 13.8% and Mongolia at 10.5%.

Baseline: Health SDGs and UHC

Fig. 9. Country distribution of three SDG indicators of malnutrition, 2005–2016 Prevalence of stunting in children under 5 (%)*

Prevalence of wasting in children under 5 (%)*

20 18

12 40

12 Global

8 Global

10 8

Region

0 Asia

Global

4 10

Prevalence of overweight in children under 5 (%)*

Pacific

Asia

Pacific

Asia

Pacific

* 17 countries Source: UNICEF, WHO, and the World Bank Group

Urban and environmental health On the four indicators measuring urban and environmental health, the Region underperforms the global rates on the annual mean concentration of FPM in urban areas, with a value of 49.2 µg/m3 compared to 38.4 µg/m3 globally. Particularly high values are reported by China at 59.5, and by the Lao People’s Democratic Republic, Mongolia, the Philippines, the Republic of Korea and Viet Nam, all of which have values close to 30. The goal for 2030 is to reduce the adverse per capita environmental impact of cities (SDG 11.6). The Region outperforms the global rate for the proportion of population with primary reliance on clean fuels, with a value of 61% compared to 57% globally. However, there is wide regional variation on the use of clean fuels, with Kiribati, the Lao People’s Democratic Republic and Solomon Islands using less than 10% clean fuels. For the use of improved drinking water and sanitation, Papua New Guinea has particularly low rates, with about 40% of the population using improved drinking water and 19% improved sanitation (Fig. 10). There is no specific target for this indicator, but Fig. 10. Country distribution of the proportion of population using improved drinking water and sanitation, 2015

100

Proportion of population using improved drinking-water sources (%) (proxy)* Region Global

90 80

100

Proportion of population using improved sanitation (%) (proxy)*

90 80

Region

Global

50 60

30 20

40 30

10 Asia

Pacific

Asia

* 24 countries. These indicators are used here as proxies for the SDG indicators 6.1.1 and 6.2.1 Source: UNICEF and WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Pacific

the 2030 goal is universal and equitable access to safe and affordable drinking water, sanitation and hygiene (SDGs 6.1 and 6.2).

Health system resources and capacity There are two indicators for health resources and infrastructure: civil registration coverage of births, and completeness of cause-of-death data. Most countries have close to or above 75% birth registration coverage, but a few are lagging, including Samoa at 58.6%, Tuvalu at 50% and Vanuatu at 43.4%. The completeness of cause-of-death data is also high in most countries of the Region. The few countries with lower values, at close to 60%, include China, Kiribati and Malaysia. The third indicator in this group is general government health expenditure as a percentage of general government expenditure. In 2014, the regional value for this indicator was 14.3% and the global value 15.5%. Fig. 11 presents the distribution of government health expenditure in the Region. Fig. 11. Country distribution of government health expenditure, 2014 General government health expenditure as % of general government expenditure* 25 20 Global

Region

10 5 0

Asia

Pacific

* 27 countries Source: WHO

Other indicators for which regional and global rates are reported measure mortality from natural disasters, homicides and major conflicts. For mortality related to natural disasters, the Region underperforms global rates, with a value of 0.5 deaths per 100â&#x20AC;Ż000 population compared to 0.3 globally. For mortality related to homicides and major conflicts, the Region rates are lower than global rates.

3.3 Universal health coverage (UHC) UHC means that all people have access to quality health services without suffering financial hardship from paying for care. UHC is the overarching vision for health sector development and is a specific aim within the SDGs. UHC is measured through SDG 3.8.1 (coverage of essential health services) and SDG 3.8.2 (financial risk protection).

Baseline: Health SDGs and UHC

Indicator 3.8.1 is reported as an index, combining 16 tracer indicators organized under four main tracer domains (Fig. 12). The indicators capture the extent to which those in need of health services receive the care they need. The index does not measure the quality or efficiency of the services provided. The scale of the index ranges from 0 to 100, with 100 interpreted as the target value for coverage of essential health services. The first of the four tracer domains captures the coverage of essential services related to RMNCH. As a sub-index, it measures the extent to which those in need of family planning, pregnancy and delivery care, child immunization, and treatment receive the care they need. The second tracer domain (infectious diseases) measures: (i) the extent to which those in need of TB and HIV treatment and malaria prevention receive the care and services they need; and (ii) access to improved sanitation. The third tracer domain (NCDs) measures the status of NCD risk factors in the population, including blood pressure, glucose level and tobacco consumption, as a proxy indicator of the success of both prevention efforts and screening and treatment programmes. The fourth tracer domain (service capacity and access) measures general features of service capacity and access to care within a health system. Measures include availability of hospital beds and health professionals per capita, and a measure of health security for responding to epidemics and other health threats. In general, the baseline data show that country values for the UHC index increase with income level. Overall, high-income countries in the Region2 report an index of 75 or higher, indicating good coverage of essential health services. Countries with relatively low values include Cook Islands, Kiribati, the Marshall Islands and Papua New Guinea with an index of close to 40. To reach an index value close to 90 by 2030, countries in the Region would need to increase their score by approximately 2.5% per year, on average. In terms of the four tracer domains, the average regional values are high for RMNCH and for service capacity and access, but low for infectious and NCDs (Fig. 12). Fig. 12. Country distribution of coverage of UHC essential health services (SDG 3.8.1), target=100, 27 Western Pacific countries by percentage, 2002â&#x20AC;&#x201C;2015 Asia

100

Pacific

Asia

Pacific

Asia

Pacific

Asia

Pacific

Avg

Asia

Pacific

Avg

40 20 0 UHC Index

RMNCH

Infectious Diseases

NCD

Service Capacity

Note: UHC Index: overall UHC service coverage index. RMNCH: UHC tracer index for reproductive, maternal, newborn and child health. Infectious Diseases: UHC tracer index for infectious diseases. NCD: UHC tracer index for noncommunicable diseases. Service Capacity: UHC tracer index for service capacity and access. Source: WHO

With the exception of Palau.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Indicator 3.8.2 is defined as the proportion of the population having large household expenditures on health as a share of total household consumption expenditures or income. The draft financial protection estimates are in consultation and available for 11 of the 27 countries. Although interpretation of this indicator depends on each country’s context, in general a higher value means a higher level of health-related financial hardship for the population. Countries with values above the average for this indicator on financial risk protection include Cambodia, China, Japan, the Republic of Korea and Viet Nam. Lower values may not necessarily indicate more financial risk protection, but may indicate non-use of health services due to financial barriers to access or lack of availability of quality services. It is important to consider health service utilization when assessing financial protection. To provide an overall assessment of the state of UHC of individual countries, Figs. 13 and 14 present an analysis combining coverage of essential health services and financial risk protection. On a country basis, looking at coverage and financial protection is useful in evaluating UHC progress; however, further analysis is needed specifically on utilization rates to capture those who do not use health services because of barriers to access. This analysis helps to understand whether people have coverage of the services they need and the extent of financial protection they have when doing so.3 Fig. 13. Overall progress towards the delivery of UHC, 11 Western Pacific countries 6%

Financial risk protection (SDG 3.8.2)*

VNM

KHM

CHN JPN

KOR

3% 2%

PHL

MNG AUS

LAO

FJI

0% 20

MYS 70

100

UHC index -coverage of essential health services (target=100)** AUS = Australia, KHM = Cambodia, CHN = China, FJI = Fiji, JPN = Japan, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MNG = Mongolia, PHL = Philippines, KOR = Republic of Korea, VNM = Viet Nam. * Proportion of population with out-of-pocket health spending exceeding 25% of total household consumption or income (%), 2005–2015. The 2% threshold is not a target. It was arbitrarily selected to map countries in a way that allows cross-country comparison and a baseline position for future trend analysis. ** Defined as the average coverage of essential services based on tracer interventions that include reproductive, maternal, newborn and child health, infectious diseases, NCDs and service capacity and access, 2002–2015. Source: WHO

Fig. 13 maps the 11 regional countries with data on financial risk protection along with the corresponding overall UHC service coverage index. Each dot captures the current progress of a country in terms of achieving UHC. In general, countries in the southeast quadrant have relatively higher coverage of essential health services and relatively 3

Saksena P., Hsu J., Evans DB. Financial Risk Protection and Universal Health Coverage: Evidence and Measurement Challenges. PLoS Med. 2014 Sep; 11(9).

Baseline: Health SDGs and UHC

lower risk of financial hardship for the population. Countries in the opposite quadrant (north-west) may have limited coverage of essential health services and relatively higher risk of financial hardship for the population. Australia, Malaysia, Fiji and Mongolia seem to have a low level of financial risk and relatively high coverage. China, Japan, the Republic of Korea and Viet Nam are all in the north-east quadrant, meaning relatively high coverage of essential health services, but relatively high risk of financial hardship. Cambodia is currently in the north-west quadrant, with limited coverage of essential health services and relatively high risk of financial hardship. Philippines and the Lao Peopleâ&#x20AC;&#x2122;s Democratic Republic are in the south-west quadrant, showing limited coverage but not necessarily lower risk of financial hardship. In these countries, as noted, a lower value for the financial risk protection indicator may imply financial barriers to access or unavailability of quality services, rather than financial protection. In this case, non-users of health services are not counted in the financial risk protection indicator, which may partially reflect the trade-offs people make between paying for services they need and paying for other necessities such as food and basic education.4 To explore the extent of UHC in a larger number of Western Pacific countries, the overall UHC service coverage index was mapped against an alternative measure of financial hardship built from data on health expenditure (Appendix 3). This measure is out-of-pocket health expenditure per capita as a percentage of gross domestic product (GDP) per capita.5 This measure showed good correlation with SDG indicator 3.8.2. Fig. 14 shows the results of this analysis, which is available for 27 Western Pacific countries. With some minor differences, the classification of countries in Fig. 13 is similar to that observed in Fig. 14. China, Japan and the Philippines experienced some movement in the classification; all other countries remained in the quadrant previously mapped. Overall, this analysis shows that countries are at different stages in their progress towards UHC, half of the countries are above the mean (2.5%) when it comes to financial risk protection. Within these countries, there is a wide range of service coverage. The countries with relatively low risk of financial hardship may mean increased financial barriers to access or unavailability of quality health services. Achieving UHC will require countries to move closer towards the 100-point target while maximizing financial risk protection for their populations. The trajectory to UHC will be country specific, and will depend on each countryâ&#x20AC;&#x2122;s history, political economy, available resources and expectations. It is important for countries to consider further in-depth analysis to continue monitoring UHC, specifically monitoring vulnerable groups and progress through time trend analysis.

Saksena P., Hsu J., Evans DB. Financial Risk Protection and Universal Health Coverage: Evidence and Measurement Challenges. PLoS Med. 2014 Sep; 11(9). This indicator does not necessarily measure financial risk protection and is not a replacement for the UHC financial risk protection indicator (3.8.2).

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Fig. 14. Overall progress towards the delivery of UHC, using a proxy measure for financial risk protection, 27 Western Pacific countries

Proxy measure for financial protection (OOPS/GDP per capita, %)*

5% KHM

4% 3%

PHL MHL

MNG PLW

FSM PNG COK

0% 20

CHN MYS

JPN

FJI

LAO

SGP

VNM

NRU

AUS NZL

TON

WSM

SLB KIR

KOR

TUV

VUT

BRN

NIU

100

UHC index -coverage of essential health services (target=100)** AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao Peopleâ&#x20AC;&#x2DC;s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. * OOPS: out-of-pocket expenditure per capita in US$, 2013; GDP: gross domestic product in current US$ per capita, 2013. This indicator does not necessarily measure financial risk protection and is not a replacement for the UHC financial risk protection indicator (3.8.2). The 2% threshold is not a target. It was arbitrarily selected to map countries in a way that allows cross-country comparison and a baseline position for future trend analysis. ** Defined as the average coverage of essential services based on tracer interventions that include reproductive, maternal, newborn and child health, infectious diseases, NCDs and service capacity and access, 2002â&#x20AC;&#x201C;2015. Source: WHO

Additional analyses of the current state of individual countries across the four main domains of the UHC service coverage index can be found in Appendix 3. For RMNCH and for service capacity and access, the Member States lean towards the south-east quadrant, showing relatively high coverage and relatively low risk of financial hardship. In regard to the other two domains of the UHC index, for coverage of infectious and NCDs, overall the countries lean towards the south-west quadrant showing lower coverage and lower financial risk, which, as noted, may be due to high financial barriers to access or unavailability of quality health services.

Health system performance The current SDG service coverage index reports on a limited number of essential health services, largely within the scope of public health. This index does not capture the quality of services provided nor other essential attributes of high-performing health systems, including the process of accessing and delivering services. To fill this gap, the Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework proposes additional indicators to measure some of these attributes. However, at present the data for the additional indicators are largely lacking. One of the missing attributes is quality, which encompasses the safety and effectiveness of both individual and population-level interventions. Improving quality also implies a satisfactory experience for the user, and requires an integrated, people-centred system of health service delivery. Table 2 provides examples of indicators from the Sustainable

Baseline: Health SDGs and UHC

Development Goals and Universal Health Coverage Regional Monitoring Framework that measure quality, and highlights those for which there is a baseline value. A second missing attribute is efficiency, which shows whether the best use is being made of available resources. Improving health service efficiency enables the system to generate more output for the same level of resources. Currently, the Framework only incorporates two measures of facility-level efficiency (Table 2). There are no measures of system-level efficiencies, which would entail better understanding of the resources spent at different levels of the health system, including facility, primary care and community levels, and the outputs and outcomes produced from those levels. Equity is a third important attribute of a high-performing health system. It refers to the absence of avoidable or remediable differences of service and access among groups of people. Chapter 4, below, addresses the concept of equity by disaggregating indicators using commonly agreed stratifiers. Table 2.

Examples of indicators from the SDGs and UHC Regional Monitoring Framework that measure quality and efficiency

Attribute of highperforming health system QUALITY

SDG and UHC framework indicator domain Effectiveness

Indicator zz zz zz zz zz

Quality and safety

zz zz zz

EFFICIENCY

Responsiveness and people Efficiency and sustainability

zz zz zz

Baseline value

Immunization coverage rate for DTP3 Immunization coverage rate for measles Viral suppression rate among people on ART Proportion of newborns receiving essential newborn care Cataract surgical rate and coverage 30-day hospital mortality rate Postoperative sepsis rate Hospital admission and readmission rates* Patient experience Bed occupancy rate Hospital average length of stay

3 3

*These indicators can also be used as tracer indicators to measure access to and quality of primary and community care. DPT3 = three doses diphtheria-tetanus-pertussis. ART = antiretroviral therapy.

The fourth attribute of a high-performing health system is accountability, which is concerned with the requirement that stakeholders provide information and justify their decisions and actions in return for rewards or sanctions. The Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework does not include direct measures of accountability. The fifth and final attribute, sustainability and resilience, is concerned with the extent to which future generations will continue to benefit from the health system, and with the system’s capacity to cope with and recover from internal and external shocks, and to prepare for and adapt to changing environments. SDG indicator 3.d.1 – IHR (2005) core capacity index – measures this attribute. For this indicator, the Western Pacific Region has a score of 79 compared with the global score of 73 (target=100). For the two indicators of immunization coverage, the Region outperforms global rates. In 2016, immunization coverage was close to 96–97% in the Region, compared to approximately 85–86% globally. However, some countries lag behind at 65% or below. These include Samoa (for DTP3 only) and Vanuatu.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Data from the Organisation for Economic Co-operation and Development (OECD) Data for some indicators measuring essential health system attributes are available from the database of the Organisation for Economic Co-operation and Development (OECD). Countries from the Western Pacific Region that also report to OECD include Australia, Japan, New Zealand and the Republic of Korea. Singapore, although not a member of the OECD, also reports some indicators. Table 3 summarizes data for the OECD indicators of quality and safety, efficiency, and health service coverage and access. Two indicators of quality presented in Table 3 are important markers of health system performance, as they reflect quality in more than one sector. Hospital admission rates for certain conditions are proxy measures for medical problems that are potentially preventable. For example, hypertension (high blood pressure), as reported in Table 3, can be treated in primary and community care; hospital admission may indicate problems with access to and quality of primary care. New Zealand reports the lowest Table 3.

Examples of indicators from the SDGs and UHC Regional Monitoring Framework that measure quality and safety, facility-level efficiency, and health service coverage and access

Member State

Year Australia Brunei Darussalam Cambodia China Cook Islands Fiji Japan Kiribati Lao People’s Democratic Republic Malaysia Marshall Islands Micronesia (Federated States of) Mongolia Nauru New Zealand Niue Palau Papua New Guinea Philippines Republic of Korea Samoa Singapore Solomon Islands Tonga Tuvalu Vanuatu Viet Nam

30-day mortality after Hospital Hospital admission to Cervical cancer admission rate average length hospital (acute screening**** (hypertension)* of stay (days)** myocardial infarction)*** 2011–2014 36.5

2014–2015 5.3

22.5

Doctor consultations per capita (in all settings) – outpatient visits

Post-operative sepsis rate***** 2013–2014 1457.6

2011–2014 4.0

2013–2016 56.4

2012–2016 7.6

12.2

42.1

12.7

17.3

4.3

6.6

76.1

3.7

158.4

10.0

8.3

57.7

16.0

30.5

256.4

11.0

*Age-sex standardized rate per 100 000 population (15 years and older). ** Infectious and parasitic diseases. *** Age-sex standardized rate per 100 patients (45 years old and older). **** % of females aged 20–69 screened (survey and programme data). ***** Crude rate per 100 000 hospital discharges (surgical episode-related method). Source: https://data.oecd.org/

Baseline: Health SDGs and UHC

rate of hospital admission for hypertension at 17 admissions per 100 000 population, while the Republic of Korea has the highest rate at 158 admissions. Similarly, the 30-day mortality rate is a marker for the quality of hospital care and for access to and quality of primary and community care, and care provided in other facilities. Mortality risk increases when the quality of care in hospitals is insufficient. This may also include whether a hospital is preventing complications, educating patients about their care needs and arranging transition from hospital to home or another type of facility. The mortality risk also increases if the patient is not receiving the necessary follow-up care after discharge. This could happen in a primary care setting or in other facilities, for example long-term care facilities, where the patient resides. Australia reports the lowest 30-day mortality rate at 4.1 deaths per 100 patients and Japan the highest at 12.1 deaths. However, care is needed with interpretation as a large part of the difference in these mortality rates may be explained by differences in the mix of patients treated in individual countries. Indicators described in this section are part of the Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework, in the group of additional indicators to monitor UHC in the Western Pacific. This section of the Framework currently proposes 41 additional indicators beyond those which measure health in the SDGs. Of the 41 proposed indicators, there are baseline values for 20, where more than 50% of countries report data. The topics covered include some aspects of health status, individual characteristics and behaviours, and health service coverage and effectiveness, largely in RMNCH and NCDs (Appendix 2).

3.4 Equity-focused monitoring The current baseline situation presented above does not describe health inequities within countries. Appendices 1 and 2 report baseline values at the country level only. The 2030 Agenda for Sustainable Development, however, stresses the importance of equity for the poor and disadvantaged, with the aim of leaving no one behind. A prerequisite to creating this equity orientation is the systematic identification of where inequities exist, and then monitoring the change in inequities over time.6 An important step in this process is to disaggregate indicators following commonly used attributes or stratifiers. Table 4 lists some of the common stratifiers used for disaggregation of routine health statistics, as proposed in the metadata. Some stratifiers, such as sex, age and wealth quintiles, are important for a large number of indicators, while others may be relevant only for a few indicators, for example provider type.

World Health Organization (2013). Handbook on health inequality monitoring: with a special focus on low- and middle-income countries. http://apps.who.int/iris/bitstream/10665/85345/1/9789241548632_eng.pdf

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Table 4.

Commonly used stratifiers available in the SDG and UHC metadata

Stratifiers Age, motherâ&#x20AC;&#x2122;s age Disability status Education, maternal education Ethnic group, race, indigenous groups Facility type (e.g. public/private), provider type, health subsector Key populations (e.g. HIV status, transgender, prisoners) Marital status Place of residence, urban/rural, subnational district, geographic location Sex, sex of household head Socioeconomic status, wealth quintile, employment status

The use of these stratifiers can provide a first look at health inequities. Countries are encouraged to strengthen their systems and capacity for equity-focused data collection and analysis using these common stratifiers, and also to share their disaggregated data so that country comparisons can be reported and monitored in the Region. The data available for equity analysis, presented in Section 4 below, come from surveys which used a limited number of stratifiers. Other data sources, such as administrative data, should be used for better assessment of health inequities, using other common stratifiers proposed in the metadata. In the absence of adequate disaggregation, countries may consider using data on the broader social determinants of health to assess and tackle health inequity. For example, gender inequality may result in lower school enrolment rates for girls than for boys. In turn, poor education results in poorer health outcomes for girls and women themselves, and for their children and families. Disability, marginalization or ethnicity can compound gender-based disadvantage, further limiting access to health and social services. Based on existing knowledge of the broader social determinants of health, countries may identify disadvantaged populations to assess where health inequities may exist. This approach will require the use of data beyond the health sector (for example education, housing and living conditions), and efforts to coordinate action in partnership with various sectors and levels of government.

Baseline: Health SDGs and UHC

EQUITY ANALYSIS

To illustrate how countries can conduct equity analysis, this section focuses on three areas where there are data for some countries in the Region. The areas are: reproductive, maternal, newborn and child health (RMNCH); NCD risk factors; and financial protection. In addition, two country case studies are presented. These case studies use indicators that are not necessarily part of the Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework but that respond to the individual country’s unique priorities and needs. There are relatively good data to explore inequities in RMNCH, but only for six countries in the Region. Data for NCD risk factors are available for 20 countries and areas, and mostly stratified by age and sex. Financial Protection draft estimates are available for 11 countries using the stratifiers of economic status and place of residence.

Key findings zz

zz zz

There appears to be widespread inequity across the Western Pacific Region, in relation to access to health services, risk factors, health status and financial protection. This means that a large number of people are still being “left behind”. There are well-known and continuing disparities between the rich and the poor, between urban and rural households, and across subnational regions. In some countries, subnational regions are clustered, leaving only some regions behind. The extent of inequity for identified health issues varies widely among countries. The determinants of inequity also vary across countries and health issues. For example, place of residence may not be a contributing factor for inequity of immunization coverage in Viet Nam, but it is an important factor in Cambodia, the Lao People’s Democratic Republic and Vanuatu. Countries and programmes should apply targeted and tailored approaches based on their own patterns of inequity to reduce the gaps and promote health in disadvantaged subgroups. The limited availability of data for equity analysis in the Region is a major barrier to progress towards the SDGs and UHC. It is important to establish common mechanisms and data collection tools in order to obtain the evidence for better understanding of inequity in the Region.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

4.1 Reproductive, maternal, newborn and child health A total of 11 indicators of RMNCH were identified from the Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework (Appendix 4) and analysed using the Health Equity Assessment Toolkit (HEAT).7 Stratifiers available in the toolkit include economic status, education, place of residence, sex and subnational region. This section presents some examples of equity analysis for illustrative purposes. The complete stratification of the 11 indicators is available in Appendix 4. The data are available for six countries – Cambodia, the Lao People’s Democratic Republic, Mongolia, the Philippines, Vanuatu and Viet Nam. Fig. 15 presents data for DTP3 immunization coverage of 1-year-old children, disaggregated by economic status and subnational region. Additional graphs showing disaggregation by level of education, place of residence and sex are in Appendix 4. With the exception of Mongolia, all countries show substantial inequity in DTP3 immunization coverage. The rich and educated have better coverage than the poor and uneducated. Similarly, urban residents have better coverage than those living in rural areas. Variation in coverage across subnational regions also indicates that DTP3 immunization is not reaching every 1-year-old child across the country. However, the analysis suggests that the sex of a child does not affect their chance of being immunized. The pattern of inequity varies across countries and stratifiers. In Vanuatu, richer and educated groups are clustered towards better coverage, leaving only the poorest and least-educated population with lower coverage. In Cambodia and the Philippines, most regions seem to be clustered toward better coverage, leaving only one region behind. In the Lao People’s Democratic Republic, the opposite appears to be the case; one region has better immunization coverage, leaving all others behind with lower coverage. The Lao People’s Democratic Republic also shows the most in-country inequity across all stratifiers, with the exception of sex, and has the lowest overall level of immunization coverage, compared to the other five countries. Fig. 16 presents disaggregated data for births attended by skilled health personnel using the stratifiers of subnational region and economic status. With the exception of Mongolia, all countries present some inequity in the coverage of skilled birth attendance. The pattern of inequity varies for different countries and stratifiers. In Cambodia and Viet Nam, most regions are clustered towards better coverage, leaving only a few regions behind. In the Lao People’s Democratic Republic on the other hand, only one region has better coverage, leaving all others behind with lower coverage. In Cambodia, the Philippines and Viet Nam, richer groups are clustered towards better coverage, leaving the poorer groups with lower coverage. The Lao People’s Democratic Republic presents the largest in-country inequity, and the lowest level of coverage at the country level, compared to the other five countries. Disaggregated data for under-5 mortality shows significant variation in mortality rates across regions in both 7

Health Equity Assessment Toolkit (HEAT): Software for exploring and comparing health inequalities in countries. Built-in database edition. Version 1.1. Geneva, World Health Organization, 2017

Equity analysis

Cambodia and the Philippines (Appendix 4). Only one region in Cambodia and a few in the Philippines have mortality rates below the 2030 SDG target of 25 deaths per 1000 live births. Populations in the richest quintile in Cambodia and the Philippines benefit from lower under-5 mortality rates. Fig. 15. DTP3 immunization coverage among 1-year-old children (%) by economic status (in quintile) and subnational region

Subnational region

Economic status (in quintile) Q5 Q1 Q5 (richest)

Q1 Q5

60 50

30 20 Cambodia

Viet Nam

Vanuatu

Phillipines

Mongolia

Lao People‘s Democratic Republic

Cambodia

50 40

Q1 (poorest)

Viet Nam

Vanuatu

Phillipines

80 Coverage (%)

Mongolia

Lao People‘s Democratic Republic

100

Coverage (%)

100

Source: Health Equity Assessment Toolkit (HEAT): Software for exploring and comparing health inequalities in countries. Built-in database edition. Version 1.1. Geneva, World Health Organization, 2017: Cambodia (DHS, 2014), Lao People’s Democratic Republic (MICS, 2011), Mongolia (MICS, 2010), Philippines (DHS, 2013), Vanuatu (MICS, 2007), Viet Nam (MICS, 2013).

Fig. 16. Births attended by skilled health personnel (%) by economic status (in quintile) and subnational region

Economic status (in quintile) Q5 Q1

Q5 Q5 (richest)

Q1 Q1

70 (%)

60 Q1

60 50

30 20 Viet Nam

Vanuatu

Viet Nam

Vanuatu

10 Phillipines

Cambodia

Mongolia

Q1 (poorest)

Phillipines

Lao People‘s Democratic Republic

(%)

Mongolia

Lao People‘s Democratic Republic

Subnational region 100

Cambodia

100

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

4.2 Noncommunicable disease (NCD) risk factors Seven indicators for NCD risk factors were identified from the Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework (Appendix 5) and analysed following the WHO STEPwise approach to NCD risk factor surveillance (STEPS). The main stratifiers used in this approach are sex and age. For this analysis, the five Western Pacific countries with the latest available data were selected: Cambodia, the Lao Peopleâ&#x20AC;&#x2122;s Democratic Republic, Niue, Papua New Guinea and Vanuatu. This section presents some analyses for illustrative purposes. The complete stratification of the indicators is in Appendix 5. Fig. 17 disaggregates all seven indicators for NCD risk factors, stratified by place of residence in Cambodia, which is the only country that reported this stratifier. The data shows that inequity is greater for the prevalence of tobacco use and for overweight, with almost 10 percentage points difference between populations who live in urban and in rural areas. The pattern of inequity varies across risk factors. For tobacco use and for hazardous and harmful alcohol drinking, prevalence is higher in rural areas. For all other risk factors, including low physical activity, overweight and obesity, and raised blood pressure and blood glucose, prevalence is higher in urban areas. Review of the country-level data for the five selected countries indicates that, among all NCD risk factors, overall prevalence is highest for tobacco use and lowest for obesity. Fig. 17. Noncommunicable disease risk factors by place of residence, Cambodia, 2010 35 Rural

30 25

Urban

(%)

Urban

Rural

Rural Urban Rural

Prevalence of raised blood pressure, excluding those on medications

Prevalence of obesity

Prevalence of overweight

Urban Rural

Prevalence of low physical activity

Prevalence of tobacco use

Percentage of alcohol drinker engaging in hazardous and harmful drinking in the last 7 days

Rural Urban

5 0

Urban

Rural

Prevalence of raised blood glucose or currently on medications for diabetes

Source: World Health Organization. STEPS Country Reports. http://www.who.int/chp/steps/reports/en/

With the exception of Niue, all countries show a difference of over 35 percentage points in the prevalence of tobacco use between males and females (Appendix 5). The largest difference is observed in Cambodia, where the prevalence of tobacco use is 54.1% among males, and 5.9% among females, a difference of 48.2 percentage points. In Cambodia and the Lao Peopleâ&#x20AC;&#x2122;s Democratic Republic the prevalence of tobacco use increases with age, while in all other countries, prevalence decreases with age. In

Equity analysis

this analysis, the highest prevalence of tobacco use is in Papua New Guinea where the prevalence across all age groups ranges from 37–46%. In Cambodia and the Lao People’s Democratic Republic, overweight is more prevalent in females (Appendix 5). In all other countries, the differences in prevalence of overweight between males and females are minor. The pattern of age and overweight varies by country. In Cambodia and the Lao People’s Democratic Republic, the prevalence of overweight increases with age. In Niue, the youngest and oldest population groups have higher prevalence of overweight. In Papua New Guinea, prevalence of overweight decreases with age, while in Vanuatu the youngest adult group (25–34 years old) has the lowest prevalence of overweight. Among these five countries, Cambodia has the lowest overall prevalence of overweight and Vanuatu the highest. The pattern of inequity in the prevalence of raised blood pressure is similar for all five countries (Appendix 5), with the prevalence generally higher in males and increasing with age. The Lao People’s Democratic Republic, Niue and Vanuatu have the greatest range of prevalence, with differences of up to 38 percentage points in the prevalence of raised blood pressure in the youngest and oldest population groups.

4.3 Financial protection Indicator SDG 3.8.2 captures the risk of financial hardship. It focuses on the proportion of the population with large household expenditures on health as a share of total household consumption expenditure or income. Two thresholds are proposed to define “large” household expenditures on health: a lower threshold at 10% and a higher threshold at 25%. In this section, the 10% threshold is used to illustrate equity assessment of household health expenditures. Fig. 18 shows the proportion of the population with household expenditures on health exceeding 10% of daily per capita total household consumption or income, stratified by income quintile, based on draft estimates for 9 countries in the Region. The pattern of inequity is quite different across these countries, highlighting the need to interpret the findings on financial risk protection according to each country’s unique context, including how the health system is organized and funded. Of the 9 countries, only Malaysia appears to have relatively similar values for this indicator across all income quintiles. This finding means that for this country, no single income group spends disproportionally more on health than the others.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Fig. 18. Proportion of the population with household expenditures on health exceeding 10% of daily per capita total household consumption or income (%), stratified by income quintile (based on draft estimates), 9 Western Pacific countries Proportion of the population with household expenditures on health exceeding 10% of daily per capita total household consumption or income (%), stratified by income quintile 30% Q4 Q2 Q1 Q5

Q5 (richest) Q3 Q2 Q4 Q1 Q5

Q2 Q1 (poorest)

Q1 Q5

10% Q4 Q3 Q2 Q1

Q4 Q3 Q2 Q1

Q5 Q1 Mongolia

Fiji

China

Q5 Q3 Q1

Malaysia

Q5 Q3 Q1

Lao Peopleâ&#x20AC;&#x2DC;s Democratic Republic

Cambodia

Q4 Q5 Q3 Q2

Viet Nam

15%

Philippines

20%

Republic of Korea

25%

Source: WHO

In four lower-middle-income countries, Cambodia, the Lao Peopleâ&#x20AC;&#x2122;s Democratic Republic, the Philippines and Viet Nam, the analysis shows that the wealthier population groups spend more on health services (relative to income) than does the poorer population. This may not indicate that the poor have better financial protection, but rather that the poor spend on other basic needs such as housing, food and clothing first, rather than on health care. That is, the poor have less income to spare for needed health services. The low value for the indicator in the low-income population may reflect lack of access to health services. In China, the middle quintiles or near poor face a higher burden from health payments. In the Republic of Korea, the upper and lowest quintiles have a lower risk of financial burden, whereas for Fiji it seems that the higher and middle quintiles are at higher risk.

4.4 Case studies Given the limited data available for equity analysis, regular case studies may be the only option for many countries to address this analytical need. This section presents two case studies to help understand additional aspects of equity analysis.

Cambodia In 2013, a study of the association between household poverty and TB case notification in 77 districts found lower TB notification rates in poorer districts (Fig. 19). The investigators suggest that this situation may be influenced by poor geographic access to TB care, the high costs of seeking care, and low awareness of TB disease and TB services. Other variables used in the study also show health-related inequity. HIV prevalence is highest in the richest districts and lowest in the poorest districts. For vaccination coverage, the

Equity analysis

districts appear to be clustered towards better coverage, but the poorest districts are left behind with 64.4% coverage. The perception that distance to health facilities is a barrier to care is clearly associated with household poverty. Distance to health facilities is perceived as most problematic in the poorer districts. Fig. 19. Tuberculosis case notification rates, and other indicators, by household poverty rates*, Cambodia, 2010

Sputum-positive TB case notification rates (per 100 000 population)

1.4 1.2

Level 2 Level 5

0.8

130

0.6

Level 1 richest Level 3 Level 4 Level 6 poorest

Level 1 Richest

1.0

140

120

90 80

160 150

HIV prevalence (% of adults 15–49 years)

0.2

100

0.0

Level 6 poorest

40 30 Level 1 richest

20 10

0.4

110

Level 1 richest

Level 6 poorest

0 All basic vacination coverage (%)

Distance to health facilities (% perceived as problem)

* Level 1: <15% of households living below poverty line; level 2: 15–19%; level 3: 20–24%; level 4: 25–29%; level 5: 30–34%; level 6: ≥35%. Source: Wong MK et al. The association between household poverty rates and tuberculosis case notification rates in Cambodia, 2010. Western Pacific Surveillance and Response Journal, 2013, 4(1):25–33.

The study also presents a map of TB case notification rates along with district household poverty rates. The map is an example of the use of a geographic information system (GIS) to show patterns and relationships that would be more difficult to understand in tabular form. The map shows that the highest rates of household poverty are in the north-eastern region of Cambodia, which has some of the country’s lowest sputumpositive TB case notification rates. The same region also has the lowest vaccination coverage and the worst physical barriers for access to health facilities. The southern part of the country, which is less poor than the other regions, shows much higher sputumpositive TB case notification rates.

Papua New Guinea This Papua New Guinea case study shows how equity analysis can incorporate trends over time. Monthly or yearly data on patterns of inequity allow assessment of policy efforts, whether they are targeted to the right areas, and whether they are making a difference. Since 2011, Papua New Guinea, which has 22 provinces, has been reporting on 27 indicators to monitor progress towards the National Health Plan 2011–2015. All indicators are stratified by province. Three indicators are discussed below to illustrate the use of trends in equity analysis. Fig. 20 shows the availability of medical supplies in health facilities for all 22 provinces since 2011. Between 2011 and 2013, the wide variation in availability of medical supplies

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

throughout the year highlights widespread inequity in access to essential medicines across the country. A large number of provinces had medicine shortages for at least half of the year (six months) during this period. In 2013, only one province had medicines available for 10 months of the year. In 2014 and 2015, however, all provinces tended to cluster towards better availability, leaving no province behind. In 2015, all 22 provinces reported availability of medicines for at least nine (75%) or more of the months. For antenatal care (Appendix 6), the data show wide variation in coverage every year, with no clear pattern of improvement or deterioration. Each year, a few provinces cluster towards better coverage (close to 100%), leaving the majority behind at lower coverage. The pattern of inequity for under-5 mortality in hospitals does show some improvement over time (Appendix 6). In 2015, most provinces are clustered towards lower mortality rates, leaving only one province behind with a higher mortality rate. Fig. 20. Availability of medical supplies: percentage of months that facilities do not have shortage of any of selected essential supplies for more than one week in any month stratified by province, Papua New Guinea, 2011â&#x20AC;&#x201C;2015, 22 provinces

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2011

2012

2013

2014

2015

Year Source: Papua New Guinea (2016). 2015 Sector Performance Annual Review. (http://www.health.gov.pg/publications/2015_SPAR. pdf )

Equity analysis

REGIONAL RELATIONSHIPS

This section uses a logic model to organize some country-level indicators and explore their relationships in order to identify potential contributors to improved health. The selected indicators are for reproductive, maternal, newborn and child health (RMNCH), infectious diseases and NCDs. The section also presents a limited analysis of health system relationships. Table 5 summarizes the indicators used, selected from the Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework. Logic models â&#x20AC;&#x201C; also referred to as theory of change â&#x20AC;&#x201C; provide a rationale to identify areas for policy intervention and to help ensure that policy decisions are informed by evidence. Logic models present a sequence of relationships or logical connections to show how resources and inputs contribute to expected changes or results. From a health system perspective, logic models can show how different functions contribute to UHC. For example, it can allow us to see how health sector governance, financing, workforce and service delivery each contribute to the quality and efficiency of the health system. From a programme or intervention perspective, logic models can help show how certain resources are transformed into the production of health services and the extent to which expected results are achieved. Appendix 7 organizes the core reference list of 88 indicators following a logic model approach. The use of logic models in SDG and UHC monitoring stimulates critical thinking through the policy development process. The models help to identify problems and their causes, to target solutions and interventions, and to formulate, implement and evaluate policy. Table 5.

Examples of relationships following a logic model approach

Inputs/Processes (Resources) zz

Per capita total health expenditure UHC tracer index for service capacity and access

Outputs zz zz

Institutional deliveries (%) Proportion of births attended by skilled health personnel

Outcomes zz

UHC tracer index for reproductive, maternal, newborn and child health UHC tracer index for infectious diseases UHC tracer index for noncommunicable diseases

Impacts zz

zz zz zz zz zz zz

Source: WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Prevalence of stunting in children under 5 (%) Neonatal mortality rate Under-5 mortality rate Adolescent birth rate Maternal mortality ratio Tuberculosis incidence Probability of dying from any of cardiovascular disease, cancer, diabetes, chronic respiratory disease between age 30 and 70 Life expectancy at birth

In practice, more sophisticated analysis, such as regression models, may be needed for deeper understanding of the relationships, as well as data from other sectors. However, this section illustrates the utility of a logic model and demonstrates an analysis that countries can conduct as a first step to inform initial policy discussions and guide further analysis.

Key findings zz

For RMNCH, the analysis shows that a country’s resources and service capacity are positively associated with institutional deliveries, skilled birth attendance, and coverage of essential health services for women and children. These factors, in turn, may potentially influence maternal and child mortality, child stunting, adolescent births, and ultimately life expectancy. For infectious diseases, the analysis shows a positive association between a country’s resources and service capacity and coverage of essential services for TB and HIV as well as access to improved sanitation. Service coverage, in turn, was related to TB incidence and life expectancy. For NCDs, the analysis showed a weak relationship between a country’s resources and service capacity and coverage of essential NCD services, as currently measured through proxy indicators of NCD risk factors. However, coverage of essential NCD services showed an inverse relationship with the probability of dying from chronic conditions, in other words premature mortality. Since the coverage measures were based on actual levels of risk factors, including blood pressure, blood sugar and smoking, this relationship also stresses the association between the risk factors and the health status of the population. The UHC service coverage index captures some attributes of high-performing health systems, such as quality, through indicators of immunization effectiveness, and sustainability and resilience, through the IHR (2005) capacity score. The index showed a strong relationship with life expectancy, suggesting that increased coverage of essential health services may be associated with prolonged life expectancy of a country’s population. To explore the importance of quality measures not currently available in the Region, the 30-day hospital mortality rate was reviewed, using data from OECD countries. The analysis showed that an increase in 30-day mortality after hospital admission may be associated with overall decreased life expectancy of a country’s population.

5.1 Reproductive, maternal, newborn and child health Appendix 8 (Section A) presents the complete results of the relationship analysis for RMNCH. The analysis demonstrates a series of reasonably strong relationships in the process by which certain inputs and outputs link to improved service coverage and then to better health outcomes. It shows a positive correlation of resources and service capacity with institutional deliveries, skilled birth attendance, and coverage of essential services for RMNCH.

Regional relationships

The analysis also shows that the outputs for institutional deliveries and skilled birth attendance, and also the outcome for essential service coverage for RMNCH, potentially contribute to reduction of maternal and child mortality, child stunting, adolescent births, and ultimately to increased life expectancy. Fig. 21 shows an example of essential health service coverage. Total health expenditure per capita measures how much a country spends in health services in a year on average per capita. Fig. 21 shows the relationship of per capita total health expenditure with the UHC tracer index for RMNCH. This index combines measures of service coverage of family planning with modern methods, pregnancy and delivery care, and child immunization and treatment. Changes in the index may be greater in countries where the per capital total health expenditure is less than US$ 1000 purchasing power parity (PPP) per year. These are largely lower- and upper-middle-income countries, including a proportionately larger number of Pacific countries. In high-income countries, increased per capita health spending may only be related to marginal gains in coverage. Fig. 21. Relationships between health spending, coverage of essential health services for reproductive, maternal, newborn and child health, and child mortality

UHC Tracer index for reproductive, maternal newborn and child health (target=100)*, 2004–2015

100 BRN

90 FJI

MNG COK TUV

KHM

SLB KIR

LAO

TON PHL VUT PNG

NZL

KOR

CHN

VNM

FSM

MYS MHL

AUS

SGP

JPN PLW

NIU

NRU

WSM

50 40 30

Asia Pacific

20 0

500

1000

1500

2000 2500 3000 3500 Per capita total health expenditure (in PPP int. $), 2014

4000

4500

5000

70 LAO

Under-five mortality rate (per 1000 live births), 2016

KIR

PNG

50 40

NRU

VUT

WSM

MHL

FSM PHL

TUV SLB TON

KHM FJI

VNM MNG

NIU PLW

MYS

JPN

SGP

0 40

BRN

CHN

COK

NZL AUS KOR

Asia Pacific

100

UCH tracer index for reproductive, maternal, newborn and child health (target=100)*, 2004–2015 AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. * It measures the extent to which those in need for family planning, pregnancy and delivery care, child immunization, and treatment receive the care they need. Source: WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Fig. 21 also shows a strong relationship between coverage of essential health services and under-5 mortality. This may indicate that improved coverage of RMNCH can potentially contribute to saving children’s lives.

5.2 Infectious diseases Appendix 8 (Section B) presents the results of applying a logic model to infectious diseases. In general, there were limited data to capture multiple elements of infectious disease, and the analysis shows weak relationships throughout the logic model (Fig. 22). Fig. 22. Relationships between service capacity and access, coverage of essential health services for infectious diseases and TB incidence

UHC Tracer index for infectious diseases (target=100)*, 2002–2015

KOR AUS

80 NIU

TON WSM

NRU

KHM

MHL

50 LAO

VUT

VNM

FJI

PHL

FSM

KIR

SLB

NZL

BRN PLW

MYS

TUV

SGP JPN CHN

MNG

PNG

30 20

COK

Asia Pacific

0 20

100

UHC tracer index for service capacity and access (target=100)**, 2004–2015

600

PHL

TB incidence (per 100 000 population), 2016

KIR

500 PNG MHL

400

KHM

300 TUV

MNG LAO

200 100

FSM MYS

SLB VUT

VNM

PLW FJI

COK

0 0

NRU CHN

BRN SGP JPN WSM NIU TON

KOR NZL

Asia Pacific

AUS

100

UHC tracer index for infectious diseases (target=100)*, 2002–2015 AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. * It measures: (i) the extent to which those in need for TB and HIV treatment and malaria prevention receive the care and services they need; and (ii) access to improved sanitation. ** It measures general features of service capacity and access to care within a health system. Measures include hospital beds and health professionals per capita, and a measure of health security for responding to epidemics and other health threats. Source: WHO

Regional relationships

The UHC tracer index for service capacity and access exhibits some association with the tracer index for infectious diseases, which measures coverage of essential services for TB and HIV, and also access to improved sanitation (Fig. 22). The relationship suggests that for some countries improved service capacity and access may be associated with greater coverage of essential services for infectious disease. The weakness of the overall relationship suggests that other factors influence the coverage of essential services for infectious disease. These may include the pandemic situation of the country, the quality of service provided and inequity in service access. Fig. 22 also shows that coverage of essential infectious disease services may affect TB incidence. The figure indicates that improved service coverage may be associated with decreased TB incidence in a country. The strongest association observed in this analysis was between the UHC tracer index for infectious diseases and life expectancy (Fig. 23). It shows that improved coverage of essential services for infectious disease may be associated with increased life expectancy of the national population. Fig. 23. Relationship between coverage of essential services related to infectious diseases and life expectancy

Life expectancy at birth (years) both sexes, 2006–2015

100 90 JPN

COK SLB

MNG

70 PNG

LAO

KIR

VNM CHN MYS VUT MHL WSM FSM FJI TUV KHM PHL

NZL

SGP BRN

TON

KOR

AUS

NIU

NRU

50 Asia Pacific

40 0

30 40 50 60 70 UHC tracer index for infectious diseases (target=100)*, 2002–2015

100

The logic model for infectious diseases also showed that increased per capita health spending was somewhat associated with better coverage of essential infectious disease services.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

5.3 Noncommunicable diseases (NCDs) Appendix 8 (Section C) presents the results of a logic model applied to NCDs, using the limited data available. Measures of a country’s resources and service capacity showed weak relationships with the UHC tracer index for NCDs. The index measures coverage of essential health services for NCDs through proxy indicators for the current status of NCD risk factors. For countries with service capacity and access above the 60-point threshold of the index, increased service capacity is associated with better coverage of essential NCDrelated services. Similarly, for countries with annual per capita health spending above US$ 1000 (PPP), increased spending is associated with better NCD-related coverage. In countries with annual per capital health spending below US$ 500 (PPP), there is no clear association with coverage. Fig. 24 shows the strongest relationship in the logic model applied to NCDs. It indicates that increased coverage of essential NCD services may be related to a decreased probability of dying from chronic conditions, such as cardiovascular disease (CVD), cancer, diabetes and chronic respiratory disease (CRD). Since the UCH tracer index is built with actual levels of risk factors, including those related to blood pressure, blood sugar and smoking, this relationship also stresses the association between risk factors and the health status of the population. Fig. 24. Relationship between coverage of essential services for noncommunicable diseases and outcomes/impacts

Probability of dying from any of CVD, cancer, diabetes, CRD between age 30 and exact age 70 (%), 2015

40 PNG

FJI

30 KIR

TON

SLB

MNG

PHL

LAO

FSM

VUT

WSM

MYS CHN

KHM VNM BRN

NZL AUS

JPN KOR

Asia Pacific

0 0

20 30 40 50 60 UHC tracer index for noncommunicable diseases (target=100)*, 2008–2015

SGP

AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, FSM = Micronesia (Federated States of ), MNG = Mongolia, NZL = New Zealand, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, VUT = Vanuatu, VNM = Viet Nam. * It measures the current status of NCD risk factors in the population, including blood pressure, glucose level and tobacco consumption as a proxy indicator of success of both prevention efforts and screening and treatment programmes. CVD = cardiovascular disease, CRD = chronic respiratory disease Source: WHO

The analysis also shows a weak but positive association between the UHC tracer index for NCDs and life expectancy. Countries may experience improvements in life expectancy only when their UHC tracer index moves from below a 50-point threshold to beyond 70 for coverage of essential NCD services (Fig. 25). Regional relationships

Fig. 25. Relationship between coverage of essential services for noncommunicable diseases and outcomes/impacts (cont.)

Life expectancy at birth (years) both sexes, 2006–2015

100 90 KOR

JPN

80 MHL

KIR

MYS

COK

WSM

TON

FJI

SLB FSM MNG

PNG

CHN

VNM

VUT TUV PHL LAO

AUS

SGP

NZL BRN

NIU KHM

NRU

60 50

Asia Pacific

40 0

20 30 40 50 60 UHC tracer index for noncommunicable diseases (target=100)*, 2008–2015

5.4 UHC and health system performance High-performing health systems are said to be characterized by five attributes: quality, efficiency, equity, accountability, and sustainability and resilience.8 Strengthening these attributes will lead to progress towards UHC and to improved outcomes and impact. However, there is limited data to develop logic models for these relationships. This section presents a few potential examples.

Quality The UHC service coverage index captures some limited attributes of a high-performing health system. Using tracer indicators, the UHC index measures the attribute “quality” through effectiveness indicators on immunization, and the attribute “sustainability and resilience” through the IHR (2005) capacity score. The index value or score should thus be related to improved outcomes and impact. Fig. 26 presents the correlation of the UHC service coverage index with life expectancy for 26 Western Pacific countries. The relationship is strong and indicates that an improved UHC service coverage index may be associated with increased life expectancy of a country’s population. The average life expectancy in the Western Pacific Region is currently 76.6 years, which compares favourably with the reported global life expectancy of 71.4 years. However, in this Region, only high-income countries have life expectancy above the regional value. Countries with particularly low life expectancy are Nauru at 61.2 years, Papua New Guinea at 62.9 years, the Lao People’s Democratic Republic at 65.7 years and Kiribati at 66.3 years. 8

World Health Organization (2016). Universal Health Coverage: Moving Towards Better Health – Action Framework for the Western Pacific Region.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Fig. 26. Relationship between UHC service coverage index and life expectancy, 26 Western Pacific countries.

100 Life expectancy at birth (years) both sexes, 2006–2015

95 90 JPN

85 80 75

COK

MHL

KIR PNG

WSM SLB LAO

VUT KHM

MYS

TON NIU FSM PHL

MNG TUV

VNM

CHN

SGP KOR AUS NZL BRN

FJI

NRU

55 50

Asia Pacific

45 40 20

40 50 60 70 80 UHC index coverage of essential health services (target=100)*, 2002–2015

100

To explore the importance of quality measures that are currently unavailable in the Region, the 30-day hospital mortality rate was scatter-plotted with life expectancy, using data from 33 OECD countries. Thirty-day hospital mortality is an important indicator of health system performance as it captures not only the quality of hospital care but also access to and quality of primary and community care. Fig. 27 shows that increase in 30-day mortality after admission to hospital may be associated with decreased life expectancy of a country’s population. Fig. 27. Correlation between 30-day hospital mortality and life expectancy, 33 OECD countries

Life expectancy at birth, total population, year, 2012

100 95 90 85

AUS

SWE

SVN USA

POL

ITA

ESP

AUT CHL

NOR KOR SVK

EST

MEX

70 65 60 0

10 15 20 30-day mortality after admission to hospital for AMI*, 2012

AUS = Autralia, AUT = Austria, BEL = Belgium, CAN = Canada, CHL = Chile, CZE = Czech Republic, DNK = Denmark, EST = Estonia, FIN = Finland, FRA = France, DEU = Germany, HUN = Hungary, ISL = Iceland, IRL = Ireland, ISR = Israel, ITA = Italy, JPN = Japan, KOR = Republic of Korea, LVA = Latvia, LUX = Luxembourg, MEX = Mexico, NLD = Netherlands, NZL = New Zealand, NOR = Norway, POL = Poland, PRT = Portugal, SVK = Slovak Republic , SVN = Slovenia, ESP = Spain, SWE = Sweden, CHE = Switzerland, GBR = United Kingdom, USA = United States. * Age-sex standardized rate per 100 patients (45 years old and older). Source: OECD

Regional relationships

Efficiency The efficiency of a health system is assessed by comparing resources used in the production of health services with the outputs and/or outcomes of care. Fig. 28 compares annual per capita total health expenditure, as a measure of resources, with the coverage of essential health services measured through the UHC service coverage index (SDG 3.8.1) as an outcome measure. Per capita total health expenditure is an aggregate measure that combines all resources spent across the health system, from public and private sources, including out-of-pocket expenditure. The current UHC service coverage index reports on a limited number of essential services, largely within the scope of public health. The index does not capture service quality, nor coverage of some other health services, for example surgery, diagnostic tests and medications. Given the different scope of these two measures, caution is needed when interpreting the efficiency analysis. To interpret efficiency, one can compare countries with similar patterns of spending but different outcomes. Alternatively, countries with similar outcomes but with different patterns of spending may be compared. For example, in Fig. 28, China currently stands at 76 points for coverage of essential health services and spends approximately US$ 730 (PPP) annually per capita on health services (using 2014 expenditure data). Annual health expenditure per capita in the Marshall Islands is similar to that of China at US$ 680 (PPP); however, the Marshall Islands provides close to half the coverage of essential services provided by China, at 40 points. Japan has coverage of essential health services similar to China; however, its per capita expenditure is close to five times the amount that China spends on health services. Fig. 28. Per capita total health expenditure vs. coverage of essential health services

UHC index coverage of essential health services (target=100)*, 2002–2015

90 80

NZL

KOR

BRN

SGP

AUS

JPN

CHN VNM

FJI TON

VUT

PHL KHM

SLB

LAO PNG KIR

MYS TUV MNG FSM

PLW

NIU

WSM NRU COK

MHL

Asia Pacific

30 0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

In this example, the analysis does not necessarily show that China’s health system is more efficient than that of other countries. The differences in per capita spending may 40

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

indicate spending on different areas which are not necessarily measured in the UHC service coverage index, for example quality of care, access to hospital services and specialists, diagnostic services and medications. Comparing per capita total health expenditure with life expectancy is another way to assess efficiency. In Fig. 29, life expectancy in Viet Nam is currently 76 years, and per capita annual health spending is approximately US$ 390 (PPP). Annual per capita health expenditure in Fiji is similar to that in Viet Nam at US$ 364 (PPP); however, life expectancy in Fiji, at close to 70 years, is lower than in Viet Nam. Life expectancy in China is similar to that of Viet Nam; however, China spends almost twice what Viet Nam spends per capita on health services. Since life expectancy also depends on other complex socioeconomic factors related to a countryâ&#x20AC;&#x2122;s level of development, the analysis cannot conclude directly that Viet Nam is more efficient than the other counties. Fig. 29. Annual per capita total health expenditure vs. life expectancy Life expectancy at birth (years) both sexes, 2006-2015

90 85 KOR

VNM TON

75 SLB

KHM

VUT

PHL KIR LAO PNG

65 60

JPN

SGP NZL

AUS

BRN

COK CHN MYS WSM NIU MHL FJI TUV FSM MNG NRU

Asia Pacific

50 0

500

1000

1500

2000 2500 3000 3500 Per capita total health expenditure (in PPP int. $), 2014

4000

4500

5000

AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao Peopleâ&#x20AC;&#x2DC;s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. Source: WHO

To interpret health spending efficiency, each country should conduct its own efficiency analysis using longitudinal data, and also data on spending and outputs/outcomes of care, either for certain focus areas (for example, primary care) or for the whole health system. Fig. 30 presents additional analyses comparing annual per capita total health expenditure with each of the three main tracer domains of the UHC service coverage index. Beyond the efficiency interpretations that might be drawn from these analyses, the relationships presented in this section also suggest, that for some lower- and uppermiddle-income countries, increased health spending is associated with improved coverage and prolonged life expectancy. For high-income countries, however, increased health spending may not necessarily be associated with increased coverage and life expectancy.

Regional relationships

Fig. 30. Per capita total health expenditure vs. coverage in three main focus areas

UHC Tracer index for reproductive, maternal newborn and child health (target=100)*, 2004–2015

100 BRN

90 FJI

VNM

MNG COK TUV

KHM

SLB KIR

LAO

TON

SGP

JPN MYS

MHL

FSM

PHL VUT PNG

NZL

KOR

CHN

AUS

PLW

NIU

NRU

WSM

50 40 30

Asia Pacific

20 0

500

1000

1500

2000 2500 3000 3500 Per capita total health expenditure (in PPP int. $), 2014

4000

4500

5000

90 KOR

UHC Tracer index for infectious diseases (target=100)**, 2002–2015

80 TON

70 60

KHM

VUT

WSM NRU

VNM

FJI FSM PHL KIR SLB LAO PNG

CHN MHL

NZL

BRN

NIU MYS

TUV

AUS

SGP

JPN

PLW

MNG

30 20

COK

Asia Pacific

10 0 0

500

1000

1500

2000 2500 3000 3500 Per capita total health expenditure (in PPP int. $), 2014

4000

4500

5000

UHC Tracer index for noncommunicable diseases (target=100)***, 2008–2015

80 70

KHM VUT

PHL

LAO

BRN VNM

SLB

PNG

JPN

SGP NZL

AUS

MYS

MNG

PLW

FSM COK NRU

TON

CHN TUV

FJI

KOR

NIU

WSM

20 MHL

KIR

Asia Pacific

0 0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Per capita total health expenditure (in PPP int. $), 2014 AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. * It measures the extent to which those in need for family planning, pregnancy and delivery care, child immunization, and treatment receive the care they need. ** It measures: (i) the extent to which those in need for TB and HIV treatment and malaria prevention receive the care and services they need; and (ii) access to improved sanitation. *** It measures general features of service capacity and access to care within a health system. Measures include hospital beds and health professionals per capita, and a measure of health security for responding to epidemics and other health threats Source: WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

COUNTRY PROFILES FOR SDGs AND UHC

The WHO Regional Office for the Western Pacific is developing an interactive web-based tool to enable each Member State to review its profile and compare its profile with others. The tool will organize country information in multiple areas or sections. These include one section giving country values for each indicator, targets when available, and regional and global aggregates; one disaggregating indicator values according to the stratifiers suggested in the metadata, when available; and one incorporating some form of analysis following the regional relationships and the logic model approach presented in this report. This tool will help countries identify priority areas to guide and support monitoringrelated action, including areas where progress is needed, and also those where additional country-specific analysis and review are required, and those which currently have no data from which to assess progress, for example disaggregation. Countries can also use the information reported in this tool to stimulate cross-country comparison and foster dialogue on progress, knowledge sharing and reciprocal learning, both within countries and among countries at a regional level. To assist individual countries in the monitoring process, the WHO Regional Office for the Western Pacific will develop a country profile for each of the 27 Western Pacific countries that are included in this baseline report. The profiles will attempt to go beyond the typical table format where a number of indicator values are presented. Instead a format will be employed that compares indicator values to targets to make an overall assessment of progress and also highlight health issues where attention may be needed. The profile will include a UHC strategic map to view all countries at once in terms of overall progress towards UHC and how they compare to one another. It will also include a few inputâ&#x20AC;&#x201C;outcome relationships at the end as a way to show the type of analysis countries could use to support their own monitoring process.

LIMITATIONS

This baseline report has certain limitations. The statistics presented in the report have been compiled from data available over a baseline period of 2010â&#x20AC;&#x201C;2016, where possible, primarily using publications and databases produced and maintained by WHO, the United Nations and other international organizations. For those indicators with a reference period expressed as a range, country values refer to the latest available year in the range unless otherwise noted. Baseline values are available for only 25 of the 27 indicators under SDG 3. Of the current 20 health-related indicators under other SDGs, baseline values are only available for 16. There are 41 additional indicators to monitor UHC, beyond those measuring health in the SDGs; there are baseline values for 20 of these, where more than 50% of countries report relevant data. Wherever possible, global estimates have been computed using standardized categories and methods in order to enhance cross-national comparability. As a result, there may be some differences between the WHO estimates presented in this report and official national statistics prepared and endorsed by WHO Member States. In addition, some estimates may have large confidence intervals and be subject to uncertainty, especially in countries with weak statistical information systems and where the quality of the underlying empirical data is limited. Other data limitations include variations in reporting years across indicators, lack of baseline values for some indicators and the level of uncertainty of some estimates. These will all have important implications in the formulation of a countryâ&#x20AC;&#x2122;s monitoring framework, including the identification of priority areas and needs, and the selection of suitable monitoring indicators. They will also affect the process of defining and targeting areas for policy change and intervention, and historical comparisons. Comparability of country-reported data is uncertain for some indicators where original country data are used instead of global estimates. Data definitions, elements and methodologies, as applied to the primary collected and processed data, may not be standardized and harmonized across countries. This limitation may not affect a countryâ&#x20AC;&#x2122;s own monitoring, as long as the data attributes employed by any country remain consistent over time. Regardless, countries are encouraged to use the global metadata to inform their own data collection and reporting process. The current baseline situation presented in this report does not describe health inequity among groups within countries. There is limited disaggregated data in the Region. The

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

best disaggregated data are available for reproductive, maternal, newborn and child health; it is drawn from surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). These data are only available for six countries and for some indicators. Table 6 presents an example of the level of disaggregation needed to create an equityoriented health sector. The disaggregated data allows systematic identification of inequities, and the monitoring of any change over time. The stratifiers presented are those proposed in the global metadata. Table 6.

Proposed disaggregation for under-5 mortality rate Under-5 mortality rate

Member State Australia Brunei Darussalam Cambodia China Cook Islands Fiji Japan Kiribati Lao Peopleâ&#x20AC;&#x2122;s Democratic Republic Malaysia Marshall Islands Micronesia (Federated States of) Mongolia Nauru New Zealand Niue Palau Papua New Guinea Philippines Republic of Korea Samoa Singapore Solomon Islands Tonga Tuvalu Vanuatu Viet Nam

Sex

Age

Wealth quintile

Place of residence Motherâ&#x20AC;&#x2122;s education

3 Data available Source: https://unstats.un.org/sdgs/metadata/files/Metadata-03-02-01.pdf

Limitations

THE WAY FORWARD

Monitoring progress towards the SDGs and UHC is a priority in the WHO Western Pacific Region. It is a complex and demanding process that includes a wide range of activities and several stages â&#x20AC;&#x201C; from data collection and infrastructure to data transformation and finally analysis to inform and drive policy change. This baseline report provides a starting point to support this process. It describes the baseline situation of UHC and health in the SDGs for the Region, including equityfocused monitoring. The report also introduces relevant analyses, techniques and tools to inform policy dialogue and policy-making, and highlights the current limitations in monitoring health in the SDGs and UHC in the Region. Countries can use this report to identify priority areas to guide action over the next 14 years, including not only areas where progress is needed, but also those requiring additional country-specific analysis and review and where there is currently no data to assess progress. Countries can also use this report to foster dialogue on progress and to encourage knowledge sharing and reciprocal learning both within countries and among countries at a regional level.

Overall recommendations The following recommendations aim to address the limitations and challenges identified in this baseline report in order to ensure that countries and the Region can accelerate progress towards the SDGs and UHC. They constitute overall directions intended to be relevant to most Member States. However, the scope of each may vary depending on each countryâ&#x20AC;&#x2122;s stage of development. 1. Improve health information systems and information sharing between different sectors, including data from population surveys, for better availability and accessibility of data, better data quality, and better analysis of data at the country and subnational levels. 2. Measure the current indicators in the Sustainable Development Goals and Universal Health Coverage Regional Monitoring Framework but for which there are no data in the Region. They include indicators for the quality and efficiency of the health services provided, and others measuring essential attributes of high-performing health systems, for example the 30-day hospital mortality rate, hospital admission and readmission rates, and patient experience. 3. Promote the use of globally agreed indicator definitions for standardized collection and analysis of data, and encourage countries to share their metadata more broadly.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

4. Improve data dissemination, transparency and sharing, including data from surveys, at the country level and across countries to allow better engagement with broader audiences and stakeholders on SDG and UHC monitoring, and to improve international comparisons. 5. Improve capacity for health information system development and data analysis at the country and subnational levels, particularly in low- and middle-income countries. 6. Improve the use of data and health statistics to evaluate the impact of health policies and actions and use the results to inform and refine policies and strategies at the country level. 7. Use existing data sources such as patient records, health insurance data, hospital management data and other administrative data to monitor health system development and performance in areas currently unavailable such as health service quality, efficiency and sustainability. 8. Identify, develop and apply new methods for data collection and analysis based on current development of information technologies for health policy analysis, including big data and geospatial data and technologies.

Priority actions The results of this baseline report were presented and discussed in a technical workshop held in Manila in May 2017. At the workshop, participants from Member States discussed and appreciated the scope and complexities of SDG and UHC monitoring. The enormous diversity of countries in terms of their current stage of monitoring-related aspects and activities means that countries will have different pathways, timelines and priorities to monitoring and achieving progress towards the SDGs and UHC. The workshop was also an important forum to help identify priority actions for countries and WHO to improve SDG and UHC monitoring in the Western Pacific Region. The recommendations outlined below summarize these priorities, which will help inform action plans and further technical work needed in the Region to improve SDG and UHC monitoring.

Member States are encouraged: 1. to develop or finalize a country-specific SDG and UHC monitoring framework. Each country should identify the targets and indicators of highest priority, in light of the countryâ&#x20AC;&#x2122;s characteristics, challenges and capacity to implement monitoring activities; 2. to actively engage in capacity development and training on multiple aspects of SDG and UHC monitoring, for example data collection processes, flows and standards, data analysis, target setting and evidenced-informed policy-making; 3. to strengthen the national health information system by creating a national coordinating body able to harmonize monitoring-related aspects and activities with other ministries, provincial or district-level governments, agencies and the private sector; and

The way forward

WHO in the Western Pacific Region will: 1. provide technical support and assistance to countries on multiple aspects of SDG and UHC monitoring by: a. guiding all technical work related to indicator development, selection and analysis, including guidance on effective methods to capture information on those at risk of being left behind; b. facilitating the adoption of common standards and a common framework to enable comparative analysis and sharing of lessons learnt; c. undertaking analysis of available data related to the SDGs and UHC and using this analysis to inform technical assistance to countries as well as for regional and comparative reporting; d. providing training to countries and producing training materials, including a minimum set of indicators for which data should be collected (for example, tracer indicators), guidelines on data analysis, target setting and reporting to support policy-making, and reporting templates; e. continually updating indicator metadata and the communication and dissemination of its use; and f. guiding the use of global estimates vs. country reported values in SDG and UHC monitoring; and 2. provide more effective country support through: a. better partner and interagency coordination and collaboration; b. higher-level advocacy and awareness; and c. better communication among the WHO Regional Office for the Western Pacific, WHO country offices and ministries of health and ministries of foreign affairs.

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

APPENDICES Appendix 1. Baseline values – SDG 3 and health-related indicators of the other SDGs Table A. Baseline values for the indicators in Sustainable Development Goal 3, mapped to the SDGs and UHC Regional Monitoring Framework

Health impact through the life course Mortality 3.1.1 Member State

3.2.1

3.2.2

Maternal Under-5 Neonatal mortality mortality mortality rateb ratioa rateb (per (per 100 (per live 000 live 1000 live 1000 births) births) births) 2015 6 23 161 27 30 5 90 197 40 100 44 11 215 114 11 51 10 114 124 78 54 41 216

2016 3.7 9.9 30.6 9.9 7.8 22.0 2.7 54.3 63.9 8.3 35.4 33.3 17.9 34.6 5.4 22.2 15.9 54.3 27.1 3.4 17.3 2.8 25.8 16.4 25.3 27.6 21.6 12.9 40.8

2016 2.2 4.4 16.2 5.1 4.1 8.8 0.9 22.6 28.7 4.4 16.4 17.2 9.7 22.2 3.0 11.6 8.4 23.5 12.6 1.5 9.2 1.1 10.4 6.8 17.2 11.8 11.5 6.5 18.6

3.4.1

3.4.2

3.6.1

Probability of dying from any of cardiovascular disease, cancer, diabetes, chronic respiratory disease between age 30 and exact age 70 c (%)

Suicide mortality rateb (per 100 000 population)

Road traffic mortality rated (per 100 000 population)

2015 8.9 12.6 23.3 18.1 31.4 8.8 28.2 25.8 17.1 25.9 29.9 10.4 36.1 28.6 8.3 22.0 10.1 26.4 24.1 22.3 17.3 17.1 18.8

2015 11.8 1.3 11.9 10.0

11.2 28.3

2013 5.4 8.1 17.4 18.8 24.2 5.8 4.7 2.9 14.3 24.0 5.7 1.9 21.0

12.6

6.0

10.3 3.4 28.3 5.7 9.9 7.9 3.5

4.8 16.8 10.5 12.0 15.8 3.6 19.2 7.6

5.8 7.4 10.8 10.7

16.6 24.5 17.3 17.4

8.5 19.7 14.3 12.3 5.8

3.9.1

3.9.2

3.9.3

Mortality rate Mortality attributed to Mortality rate exposure to rate from attributed to unsafe water, unintenhousehold sanitation and tional and ambient hygiene (WASH) poisoningc air pollutione f services (per 100 000 (per 100 000 (per 100 000 population) population) population) 2012 0.4 0.2 71.4 161.1 95.1 24.2 108.3 21.6 132.4 0.5 46.3 88.7 23.2 20.7 54.3 83.2 133.5 92.4

2012 <0.1 <0.1 5.6 0.4 3.0 0.1 13.9 0.4 3.1 0.6 12.4 5.1 0.2 0.1 10.4 2.0 0.8 12.4

2015 0.5 0.2 0.9 1.6 0.5 0.5 2.0 1.3 0.6 1.1 2.2 0.3 2.0 0.2 0.6 0.7 0.1 1.3 1.4 0.9 1.0 1.4 1.5

WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. Trends in maternal mortality: 1990 to 2015. Estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. Geneva: World Health Organization; 2015 (http://www.who.int/reproductivehealth/publications/monitoring/maternal-mortality-2015/en/, accessed 17 March 2017). WHO Member States with a population of less than 100 000 in 2015 were not included in the analysis. b World Health Statistics [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http:// www.who.int/gho/en/, accessed 03 November 2017). c Global Health Estimates 2015: Deaths by cause, age, sex, by country and by region, 2000–2015. Geneva, World Health Organization; 2016. (http://www.who.int/healthinfo/global_burden_disease/estimates/en/index1.html, accessed 22 March 2017). WHO Member States with a population of less than 90 000 in 2015 were not included in this analysis. d Global status report on road safety 2015. Geneva: World Health Organization; 2015 (http://www.who.int/violence_injury_ prevention/road_safety_status/2015/en/, accessed 22 March 2017). WHO Member States with a population of less than 90 000 in 2015 who did not participate in the survey for the report were not included in the analysis. e Public health and environment [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who.int/gho/phe/en/). WHO Member States with a population of less than 250 000 population in 2012 were not included in the analysis. f Preventing disease through healthy environments. A global assessment of the burden of disease from environmental risks. Geneva: World Health Organization; 2016 (http://apps.who.int/iris/bitstream/10665/204585/1/9789241565196_eng.pdf?ua=1, accessed 23 March 2017); and: Preventing diarrhoea through better water, sanitation and hygiene. Exposures and impacts in low- and middleincome countries. Geneva: World Health Organization; 2014 (http://apps.who.int/iris/bitstream/10665/150112/1/9789241564823_ eng.pdf?ua=1&ua=1, accessed 23 March 2017). WHO Member States with a population of less than 250 000 in 2012 were not included in the analysis. a

Appendices

Table A. Baseline values for the indicators in Sustainable Development Goal 3, mapped to the SDGs and UHC Regional Monitoring Framework (continued) Health impact through the life course

Determinants of health Life expectancy and well-being

Morbidity

Individual characteristics and behaviours

3.3.1

3.3.2

3.3.3

3.3.4

3.7.2

3.5.2

3.a.1

New HIV infections among adults 15–49 years oldg (per 1000 uninfected population)

Tuberculosis (TB) incidenceh (per 100 000 population)

Malaria incidenceh (per 1000 population at risk)

Infants receiving three doses of hepatitis B vaccinei (%) (proxy)

Adolescent birth ratej (per 1000 women aged 15–19 years)

Total alcohol per capita (>15 years of age) consumption (litres of pure alcohol)k, projected estimates

Age-standardized prevalence of tobacco smoking among persons 15 years and older l (%)

Year

2015

2016

2015

2016

2005–2014

2016

Australia

0.1

14.2

11.2

16.6

1.3

29.3

3.1

0.1

345

13.0

57.0

5.3

44.1

2.8

China

0.0

6.2

7.8

47.6

1.8

Cook Islands

56.0

5.1

Fiji

27.5

3.3

38.7

12.4

Japan

4.4

7.8

33.7 m

10.6 m

Kiribati

566

49.9

2.7

63.9

40.9

Member State

Brunei Darussalam Cambodia

Lao People’s Democratic Republic Malaysia Marshall Islands Micronesia (Federated States of) Mongolia

Male 16.7

2015 Female 13.1

175

20.9

94.0

7.3

56.6

9.1

0.3

1.9

12.7

1.5

43.0

1.4

422

85.0

177

32.6

2.4

0.0

183

26.7

7.8

47.7

5.3

Nauru

112

105.3

3.6

43.0

52.0

New Zealand

19.1

10.1

17.2

15.4

Niue

14.3

7.1

20.3

11.4

Palau

123

27.0

Papua New Guinea

0.5

432

122.2

Philippines

0.1

554

0.4

57.0

Republic of Korea

0.8

1.7

2.4

5.6

43.0

11.9

49.8

8.5 4.2 m

Samoa

44.0

2.8

41.0

18.9

Singapore

2.7

1.9

28.0

5.0

Solomon Islands

67.0

62.0

1.4

Tonga

30.0

1.4

47.3

13.0

Tuvalu

207

42.0

1.9

Vanuatu

3.3

78.0

1.3

Viet Nam

0.3

133

0.3

36.0

8.6

47.1

Western Pacific Region

0.1

3.1

15.3

7.8

Global

0.5

140

94.0

44.1

6.4

UNAIDS/WHO estimates; 2016. (http://www.who.int/gho/hiv/epidemic_status/incidence/en/) World Health Statistics [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http:// www.who.int/gho/en/, accessed 13 November 2017). i World Health Statistics [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http:// www.who.int/gho/en/, accessed 03 November 2017). This indicator is used here as a proxy for the SDG indicator. j World Fertility Data 2015. New York (NY): United Nations, Department of Economic and Social Affairs, Population Division; 2015. (http://www.un.org/en/development/desa/population/publications/dataset/fertility/wfd2015.shtml) Regional aggregates are the average of two five-year periods, 2010–2015 and 2015–2020, taken from: World Population Prospects: The 2015 Revision. DVD Edition. New York (NY): United Nations, Department of Economic and Social Affairs, Population Division; 2015 (http://esa.un.org/ unpd/wpp/Download/Standard/Fertility/, accessed 13 April 2016). k WHO Global Information System on Alcohol and Health [online database]. Geneva: World Health Organization; 2017 (http://apps. who.int/gho/data/node.main.GISAH?showonly=GISAH). l WHO global report on trends in prevalence of tobacco smoking 2015. Geneva: World Health Organization; 2015 (http://apps.who. int/iris/bitstream/10665/156262/1/9789241564922_eng.pdf, accessed 22 March 2017). m Cigarette smoking only g

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Table A. Baseline values for the indicators in Sustainable Development Goal 3, mapped to the SDGs and UHC Regional Monitoring Framework (continued) Universal health coverage Health service coverage (UHC)

Member State

3.3.5

3.5.1

Reported number of people requiring interventions against neglected tropical diseases (NTDs)n

Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and aftercare services) for substance use disorders

2015 17 476 9239 5 610 240 26 100 630 765 898 821 10 33 294 2 183 066 174 457 239 476 72 590 43 2 3 0 15 6 425 746 43 430 927 2 61 325 10 473 534 850 36 871 10 550 266 041 4 468 764 90 710 965 1 591 109 130

3.7.1

3.8.1

Proportion of married or in-union women Index–coverage of reproductive age UHC health who have their need of essential services for family planning p satisfied with modern (target=100) methodso (%)

3.b.1

3.1.2

Three doses of diphtheria tetanus- Proportion of births pertussis (DTP3) attended by skilled immunization health personnelr coverage among (%) 1-year-olds (%)q (proxy)

2005–2015

2002–2015

2016

2005–2016

56.4 35.8 61.3 80.5 68.3 42.5 40.6 51.5 39.4 60.0 47.9 41.0 50.7 69.7 89.7 76.7

>80.0 >80.0 55.4 76.4 40.5 65.8 79.6 39.9 47.6 69.6 40.4 59.7 62.6 50.8 >80.0 64.5 69.1 41.3 58.0 >80.0 55.7 >80.0 49.9 62.2 63.9 55.9 72.7

94 99 90 99 99 99 99 81 82 98 71 69 99 91 92 99 98 72 86 98 62 97 99 78 94 64 96 97 86

99s 100s 89s 100 100s 99 100s 98 40 99s 90 100s 99s 97s 97s 100s 100 53s 73 100s 83s 100s 86 96 93 89 94 96 78

Neglected tropical diseases [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http:// www.who.int/gho/neglected_diseases/en/). o World Contraceptive Use 2016 [online database]. New York (NY): United Nations, Department of Economic and Social Affairs, Population Division; 2016. Regional aggregates are estimates for the year 20165 from: United Nations, Department of Economic and Social Affairs, Population Division (2016). Model-based Estimates and Projections of Family Planning Indicators 2016. New York: United Nations. (http://www.un.org/en/development/desa/population/theme/family-planning/cp_model.shtml) p Defined as the average coverage of essential services based on tracer interventions that include reproductive, maternal, newborn and child health, infectious diseases, noncommunicable diseases and service capacity and access. Values for tracer indicators used to compute the index are based on publically available data mostly from 2010–2015, including existing WHO/UN agency estimates, country data reported to WHO, and published results from household surveys. The inputs have been selected for comparability. In cases where no country estimates are available, regional default values have been used as placeholders to allow for the calculation of the index. q World Health Statistics [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http:// www.who.int/gho/en/, accessed 03 November 2017). This indicator is used here as a proxy for the SDG indicator. r WHO/UNICEF joint Global Database 2017. (http://www.who.int/gho/maternal_health/en/ and https://data.unicef.org/topic/ maternal-health/delivery-care). The data are extracted from public available sources and have not undergone country consultation. WHO regional and global figures are for the period 2010–2016. s Non-standard definition. For more details see the WHO/UNICEF joint Global Database 2017. (http://www.who.int/gho/maternal_ health/en/ and https://data.unicef.org/topic/maternal-health/delivery-care) n

Appendices

Table A. Baseline values for the indicators in Sustainable Development Goal 3, mapped to the SDGs and UHC Regional Monitoring Framework (continued)

Member State

Universal health coverage Financial protection 3.8.2

Proportion of population with large household expenditures on health as a share of total household consumption expenditure or incomet (%)

2005–2015 (>10%) 3.2

(>25%) 1.1

13.8 17.7

4.8 4.8

0.9 7.6

0.2 4.2

3.0 0.7

0.7 0.0

6.5

1.7

6.3 21.8

1.4 3.9

18.7

5.0

Health system resources and capacity Resources and infrastructure Availability and readiness 3.b.2 3.c.1 3.b.3 3.d.1 Total net official development Proportion of assistance to health facilities that Average of 13 Skilled health medical research have a core set of International professionals and basic health relevant essential Health Regulations v density (per 10 per capita available (2005) core 000 population) medicines (constant 2014 and affordable on a capacity scores w US$), by recipient sustainable basis country u 2014

2005–2015

2010–2016

4.3 0.1 2.9 12.0 8.2 5.7 0.0 3.2 4.1 2.4 9.8 6.2 1.4 3.4 0.6 5.5 9.4 6.5 11.1 22.3 1.1 0.2 1.2

157.2 96.6 11.2 31.5 69.5 27.3 130.9 48.2 10.4 46.8 40.1 38.0 65.6 78.8 135.7 116.3 72.8 5.9 79.0 23.6 75.6 22.1 44.1 77.5 24.0 24.1 42.0 45.6

100 92 55 98 56 98 100 60 75 100 51 86 86 42 96 61 92 64 87 100 75 99 57 74 89 43 99 79 73

Provisional estimates in consultation based on primary household survey data obtained from government statistical agencies directly or indirectly by the World Health Organization or the World Bank. u United Nations’ SDG indicators global database (https://unstats.un.org/sdgs/indicators/database/?indicator=3.b.2, accessed 6 April 2017). Based on the Creditor Reporting System database of the Organisation for Economic Co-operation and Development, 2016. v Skilled health professionals refer to the latest available values (2005–2015) in the WHO Global Health Workforce Statistics database (http://who.int/hrh/statistics/hwfstats/en/) aggregated across physicians and nurses/midwives. Refer to the source for the latest values, disaggregation and metadata descriptors. w World Health Statistics [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http:// www.who.int/gho/en/, accessed 03 November 2017). t

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Table B. Baseline values for health-related indicators in other SDGs mapped to the SDGs and UHC Regional Monitoring Framework

Health impact through the life course Mortality Member State

Morbidity

1.5.1/ 11.5.1 /13.1.1

16.1.1

16.1.2

2.2.1

Average death rate due to natural disastersx (per 100 000 population)

Mortality rate due to homicidex (per 100 000 population)

Estimated direct deaths from major conflicts x, y (per 100 000 population)

Prevalence of stunting in children under 5z (%)

Prevalence of wasting in children under 5z (%)

Prevalence of overweight in children under 5z (%)

2011–2015

2015

2011–2015

2005–2016

0.1 0.0 0.7 0.1 0.4 4.2 0.0 0.2 <0.1 1.3 0.0 0.9 0.2 2.5 0.3 2.4 0.0 2.0 0.0 0.9 0.1 0.5 0.3

0.9 1.3 2.2 0.9

<0.1 0.0 <0.1 <0.1 0.0 <0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.2 1.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 2.0

2.0 19.7 32.4 9.4 7.1 43.8 17.7 10.8 24.0 49.5 30.3 2.5 32.8 8.1 10.0 28.5 24.6 7.0 22.9

0.0 2.9 9.6 2.3 2.3 6.4 8.0 1.0 1.0 14.3 7.9 1.2 4.3 5.2 3.3 4.4 6.4 2.4 7.7

7.7 8.3 2.0 6.6 1.5 2.0 7.1 10.5 2.8 13.8 5.0 7.3 2.5 17.3 6.3 4.6 5.3 5.2 6.0

2.5 0.3 9.1 6.9 3.8 4.7 8.2 1.2

12.2 11.6 2.0 3.1 2.7 4.1 3.8 2.1 3.9 1.7 6.4

2.2.2

Global Health Estimates 2015: Deaths by cause, age, sex, by country and by region, 2000–2015. Geneva, World Health Organization; 2016. (http://www.who.int/healthinfo/global_burden_disease/estimates/en/index1.html, accessed 22 March 2017). WHO Member States with a population of less than 90 000 in 2015 were not included in this analysis. y Conflict deaths include deaths due to collective violence and exclude deaths due to legal intervention. The death rate is an average over the five year period. z United Nations Children’s Fund, World Health Organization, the World Bank Group. Levels and trends in child malnutrition. UNICEF/WHO/World Bank Group Joint Child Malnutrition Estimates. UNICEF, New York; WHO, Geneva; the World Bank Group, Washington (DC); May 2017. WHO regional and global estimates are for the year 2016. x

Appendices

Table B. Baseline values for health-related indicators in other SDGs mapped to the SDGs and UHC Regional Monitoring Framework (continued)

Determinants of health Social environment factors 5.2.1

Member State

5.2.2

16.1.3

16.2.1

Proportion of children Proportion aged 1–17 of the years who population experienced subjected any physical to physical, psychological punishment and/or or sexual violence in psychological the previous byaggression caregivers 12 months in the past month

16.2.2

16.2.3

Number of victims of human trafficking per 100 000 population, by sex, age and form of exploitation

Percentage of women who reported experiencing sexual abuse before the age of 15 (proxy)aa

Percentage of women subjected to physical and/ or sexual violence by intimate partner, in the last 12 months (proxy)aa

Percentage of women subjected to physical and/ or sexual violence by intimate partner, in their lifetime (proxy)aa

Percentage of women subjected to sexual violence by non-partner, in the last 12 months (proxy)aa

Percentage of women subjected to sexual violence by non-partner, in their lifetime (proxy)aa

2000–2015

2002–2014

2002–2009

2000–2015

4.0 7.7 9.1 23.7 3.8* 36.1 18.2 24.1 22.1 6.0** 8.4 7.1

34.0 20.9 33.0 64.1 15.4* 67.6 50.9 32.8 48.1 34–42** 25.2 16.9

6.1 41.8 18.9 44.0 9.0

22.1 63.5 39.6 60.0 34.4

3.0 0.5 0.8 2.7 12.2 3.4 0.2

27.0 3.3

3.8 7.4 8.5 3.5 9.8 47.3 15.1 10.6 18.0 6.3 33.0 2.3

Gender-based Violence. Health Information and Intelligence Platform. World Health Organization Western Pacific Region (www. hiip.wpro.who.int, accessed 14 July 2017). This indicator is used here as a proxy for the SDG indicator. * Yokohama. ** Auckland, North Waikato

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Table B. Baseline values for health-related indicators in other SDGs mapped to the SDGs and UHC Regional Monitoring Framework (continued)

6.1.1

6.2.1

7.1.2

11.6.2

Universal health coverage Financial protection 1.3.1

Proportion of population using improved drinkingwater sources ab (%) (proxy)

Proportion of population using improved sanitation ab (%) (proxy)

Proportion of population with primary reliance on clean fuels ac (%)

Annual mean concentrations of fine particulate matter (PM2.5) in urban areas ae (µg/m3)

Social health protection coverage as a per cent of total population af (proxy)

Year

2015

2014

Australia Brunei Darussalam Cambodia China Cook Islands Fiji Japan Kiribati Lao People’s Democratic Republic Malaysia Marshall Islands Micronesia (Federated States of) Mongolia Nauru New Zealand Niue Palau Papua New Guinea Philippines Republic of Korea Samoa Singapore Solomon Islands Tonga Tuvalu Vanuatu Viet Nam Western Pacific Region Global

100 76 96 100 96 100 67 76 98 95 89 64 97 100 99 40 92 99 100 81 100 98 95 98 95 91

100 42 77 98 91 100 40 71 96 77 57 60 66 100 100 19 74 100 92 100 30 91 58 78 79 68

>95 >95ad 13 57 80 37 >95ad <5 <5 >95 41 25 32 >95 >95ad 91 58 31 45 >95 27 >95ad 9 63 30 16 51 61 57

5.8 5.4 25.0 59.5 6.0 12.9 33.5 16.6 6.0 32.1 5.3 12.0 27.1 27.8 17.0 5.0 7.0 27.6 49.2 38.4

Determinants of health Physical environment factors

Member State

ad ae

Health system resources and capacity Resources and Responsiveness and infrastructure patient centredness 16.9.1 17.19.2 (b) 5.6.2 Number of countries with laws and regulations that Civil guarantee full and registration Completeness cause-of- equal access to women coverage of ofdeath data and men aged 15 years births ag (%) (%) ah and older to sexual and (proxy) reproductive health care, information and education

2009–2011 2007–2013 2005–2015 100 100 26.1 96.9 100 100 11.6 100 81.9 100 82.0 100 100 100 61.0

100 >90 73.3 >90 >90 100 93.5 74.8 >90 95.9 99.3 82.6 100 >90 90.2 >90 58.6 >90 93.4 49.9 43.4 96.1

100.0 100.0 62.0 100.0 100.0 100.0 56.0 58.0 95.0 100.0 95.0 82.0 100.0 68.0 64.0 48.0

Health financing 1.a.2 General government health expenditure as % of general government expenditure ai 2014 17.3 6.5 6.1 10.4 6.1 9.2 20.3 5.8 3.4 6.4 23.8 21.2 6.7 5.2 23.4 5.9 18.1 9.5 10.0 12.3 15.1 14.1 12.5 13.5 16.9 17.9 14.2 14.3 15.5

Progress on sanitation and drinking water – 2015 update and MDG assessment. New York (NY): UNICEF; and Geneva: World Health Organization; 2015 (http://apps.who.int/iris/bitstream/10665/177752/1/9789241509145_eng.pdf?ua=1, accessed 23 March 2017). Burning opportunity: clean household energy for health, sustainable development, and wellbeing of women and children. Geneva: World Health Organization; 2016 (http://apps.who.int/iris/bitstream/10665/204717/1/9789241565233_eng.pdf, accessed 23 March 2017). For high-income countries with no information on clean fuel use, usage is assumed to be >95%. World Health Statistics [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http:// www.who.int/gho/en/, accessed 03 November 2017). Social protection [online database]. International Labour Organization (ILO) Stat (http://www.ilo.org/ilostat, accessed 19 July 2017). This indicator is used here as a proxy for the SDG indicator. Demographic and Socioeconomic Statistics[online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who.int/gho/en/, accessed 19 July 2017). This indicator is used here as a proxy for the SDG indicator. Global Health Estimates 2015: Deaths by cause, age, sex, by country and by region, 2000–2015. Geneva, World Health Organization; 2016. (http://www.who.int/healthinfo/global_burden_disease/estimates/en/index1.html, accessed 22 March 2017). Completeness was assessed relative to the de facto resident populations. WHO regional and global figures are for 2015 World Health Statistics [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http:// www.who.int/gho/en/, accessed 03 November 2017). This indicator reflects the health-related portion of the SDG indicator.

Appendices

Appendix 2.

Baseline value for additional indicators of UHC

Baseline value for additional indicators of UHC mapped to the SDGs and UHC Regional Monitoring Framework Health impact through the life course Mortality

Life expectancy and well-being

Morbidity

Number of reported deaths due to dengue fever and dengue haemorrhagic fever a (proxy)

Stillbirth rate (per 1000 total births) b

Incidence of low birth weight among newborns (%) c

Prevalence of anaemia among women aged 15–49 years (%) b

Prevalence of anaemia in children under 5 d

Congenital syphilis rate per 100 000 live births e

Life expectancy at birth (years) both sexes f

Year

2010

2015

2004–2013

2016

2013–2015

2006–2015

0 2 38 0 0 0 0 46 134 1 0 793 0 6 0 0 0 55 1075

2.7 6.5 11.9 7.2 8.7 11.9 2.1 16.3 23.7 5.8 15.6 17.8 7.3 15.5 2.3 9.7 8.4 15.9 10.9 2.1 11.1 2.6 17.6 8.6 13.8 13.9 10.1

6 12 11 2 4 10 10 8 15 11 18 11 5 27 6 7 11 21 4 10 10 13 3 6 10 5 16*

9.1 16.9 46.8 26.4

13.9 16.1 54.4 21.4

31.0 21.5 26.1 39.7 24.9 26.6 23.3 19.5

37.5 13.2 39.1 43.8 30.8 36.1 38.2 30.3

11.6

13.0

36.6 15.7 22.7 31.3 22.2 38.9 21.3

48.4 17.5 12.3 43.0 16.9 42.9 37.9

24.0 24.2 25.3 32.8

28.3 33.9 22.4 41.7

1.7 40.7 87.9 4.5 419.0 64.3 0.0 0.0

82.8 77.7 68.7 76.1 76.4** 69.9 83.7 66.3 65.7 75.0 71.8** 69.4 68.8 61.2** 81.6 73.2** 62.9 68.5 82.3 74.0 83.1 69.2 73.5 69.6** 72.0 76.0 76.6 71.4

Member State

Annual Dengue Data in Western Pacific Region 2010. (http://www.wpro.who.int/emerging_diseases/annual.dengue.data.wpr/ en/, accessed 11 August 2017). This indicator is used here as a proxy for the UHC indicator dengue mortality rate. b Global Strategy for Women’s, Children’s and Adolescents’ Health [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who.int/gho/en/, accessed 11 July 2017). c Child Nutrition [online database]. UNICEF global databases, based on DHS, MICS, other national household surveys, data from routine reporting systems, UNICEF and WHO. (https://data.unicef.org, accessed 11 July 2017). d Child malnutrition [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www. who.int/gho/en/, accessed 03 November 2017). e Sexually Transmitted Infections [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who.int/gho/en/, accessed 08 August 2017). f WHO life expectancy. http://www.who.int/gho/mortality_burden_disease/life_tables/en/ a

* Excludes China. ** National Minimum Development Indicator [online database].Secretariat of the Pacific Community (http://www.spc.int/nmdi, accessed 14 November 2017).

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Baseline value for additional indicators of UHC mapped to the SDGs and UHC Regional Monitoring Framework (continued) Determinants of health Individual characteristics and behaviours Member State

Age-standardized prevalence of raised blood glucose level (≥7.0 mmol/L or on medication) among adults 18+ years g **

Year

Age-standardized prevalence of raised Age-standardized Age-standardized blood pressure (systolic prevalence of overweight prevalence of obesity blood pressure ≥140 mass index ≥25) (body mass indexI≥ 30) mmHg or diastolic blood (body in persons aged 18+ in persons aged 18+ pressure≥90 mmHg) years g ** years g ** among persons aged g 18+ years **

2014

2015

2016

Age-standardized prevalence of insufficiently physically active persons aged 18+ years g **

2016

2010

Male

Female

Male

Female

Male

Female

Male

Female

Male

Female

6.8 9.2 7.4 9.9 28.3 15.9 8.4 22.0 7.7 11.4 20.8 20.5 12.2 30.1 7.9 26.8 24.8 15.4 7.1 9.3

5.0 9.7 6.9 7.6 26.7 18.9 5.0 22.6 7.6 10.7 21.5 23.4 11.2 28.4 6.0 27.3 21.6 14.3 7.3 6.7

18.0 22.0 26.3 21.5 24.9 22.4 22.5 24.0 24.5 25.3 23.8 26.6 32.3 23.8 19.3 26.1 25.7 25.1 24.1 13.8

12.3 15.8 25.5 16.8 19.5 20.7 12.6 19.0 24.9 20.8 18.6 23.2 25.6 17.2 13.3 22.1 20.0 25.8 21.0 8.2

70.9 41.0 18.6 34.5 83.7 59.9 32.5 76.6 22.5 42.0 82.1 72.1 55.5 88.3 70.6 77.6 84.3 47.4 26.1 34.0

58.1 41.4 24.2 30.1 85.8 67.7 21.8 80.9 27.9 43.0 84.9 79.8 55.5 88.7 60.8 82.5 85.9 58.1 28.9 26.4

29.6 12.5 2.7 5.9 52.6 25.1 4.8 41.6 3.7 13.0 48.4 40.1 17.5 58.7 30.1 44.8 51.8 16.6 5.2 4.4

28.4 15.7 4.8 6.5 59.2 35.3 3.7 50.4 6.7 17.9 57.3 51.5 23.2 63.3 31.4 55.1 58.8 25.8 7.5 4.8

20.1

27.6

9.7 22.5 62.7 10.7 31.1 33.9 4.7 46.7 38.0 31.1 19.6 36.4 35.8 6.7

10.9 25.6 67.3 23.2 36.5 48.2 16.0 58.0 51.1 40.9 23.2 45.0 43.7 4.6

11.8 13.1 28.9

17.5 18.6 37.9

Samoa Singapore Solomon Islands Tonga Tuvalu Vanuatu Viet Nam Western Pacific Region Global

22.7 9.4 12.6 21.9 23.2 15.7 5.5 9.5

26.6 6.5 15.1 26.4 24.3 16.0 5.1 7.3

26.6 17.8 20.4 25.4 26.1 24.2 25.0 24.1

21.0 11.3 23.6 21.8 21.2 24.1 21.6 20.1

73.6 36.3 49.6 74.8 80.0 52.2 15.8 33.7 38.5

82.0 27.4 60.5 82.2 83.8 62.0 20.5 29.6 39.2

39.9 5.8 17.9 41.4 47.0 20.2 1.6 6.0 11.1

55.0 6.3 27.1 54.5 56.2 30.1 2.6 6.7 15.1

10.9 30.9 30.2 13.3

21.5 35.3 39.9 30.0

7.4 22.1 23.1 19.8

9.4 25.8 27.3 26.8

Noncommunicable Diseases [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who.int/gho/en/, accessed 11 July 2017). ** Confidence intervals available in the Global Health Observatory. g

Appendices

Baseline value for additional indicators of UHC mapped to the SDGs and UHC Regional Monitoring Framework (continued) Determinants of health Individual characteristics and behaviours Member State

Seat-belt wearing rate (%) h

Motorcycle helmet wearing rate (% ) h

2013

2010–2014

Year

Front seat

Rear seat

Drivers

All

All riders

Drivers

Passengers

97.0 97.9 76.7 96.0 84.4

96.0 68.2 12.5 90.0 19.4

36.7 99.4 87.2 42.1 95–97 79.7 86.7

94.2 96.0 69.9

20.0 51.3 73.8

63.8 97.4 98.0 6.6 86.7 100.0 50.0 96.0

6.4 88.7 98.0 100.0 50.0 83.0

Infants Percentage of children exclusively under 5 years of age with breastfed for suspected pneumonia the first six who were taken to a months of health facility i life (%) j 2006–2014

2000–2014

68.8 81.1 54.4 70.3 69.0 63.0 64.0 77.8 73.0 72.1 81.1

65.2 27.6 39.8 69.0 40.4 31.3 60.0 47.1 67.2 56.1 34.0 51.3 73.7 52.2 34.7 72.6 24.3

Road Safety [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who.int/ gho/en/, accessed 12 July 2017). Child Health [online database]. UNICEF Global Databases 2016 based on MICS, DHS and other national household surveys. (https://data.unicef.org/, accessed 11 July 2017) Child malnutrition [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www. who.int/gho/en/, accessed 11 July 2017).

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Baseline value for additional indicators of UHC mapped to the SDGs and UHC Regional Monitoring Framework (continued) Universal health coverage Use/Accessibility

Member State

Health service coverage

People aged 15 Treatment success years and over who Estimated rate for patients Doctor consultations received Cervical cancer HIV testing antiretroviral treated for per capita (in screening rate and counselling, among women aged therapy coverage multidrug-resistant all settings) – estimated per 1000 people living tuberculosis (MDRoutpatient visits k 20–69 years (%)k among adult population with HIV (%)m TB) (%)n l (proxy) (proxy)

Proportion of deliveries in health facilities o

2012–2016

2013–2014

2013–2016

2016

2014

2006–2015

7.6 12.7

49 56 17 62

56.4 42.1

76 41

100

99.3 99.9 83.2 99.6 99.6 98.7 99.8 65.9

3.7 16.0

13 64 50 107 42 8 85 108 29 24

76.1 57.7

41 37

67 32

66 33

52 32

100 52 46 63 50

47 55 53

75 52 54

37.5 98.9 85.1 87.0 98.4 98.7 96.6 100.0 43.0 61.1 100.0 81.9 99.6 84.5 98.0 93.0 88.5 93.6

Health Statistics [online database]. Organisation for Economic Co-operation and Development (OECD) Stat. (http://stats.oecd. org, accessed 13 July 2017). l HIV/AIDS [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who.int/ gho/en/, accessed 12 July 2017). This indicator is used here as a proxy for the UHC indicator HIV testing coverage among people living with HIV. m HIV/AIDS [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who.int/ gho/en/, accessed 08 August 2017) n Tuberculosis [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who.int/ gho/en/, accessed 03 November 2017). This indicator is used here as a proxy for the UHC indicator second-line treatment coverage among MDR-TB cases. o UNICEF Global databases 2016 based on MICS, DHS and other national household surveys. k

Appendices

Baseline value for additional indicators of UHC mapped to the SDGs and UHC Regional Monitoring Framework (continued) Health system resources and capacity Effectiveness

Member State

Quality and safety

Three doses Measles of diphtheria (measlesCataract tetanuscontaining surgical pertussis vaccine) coverage (DTP3) of adults immunization immunization coverage aged 50 coverage among and over among 1-year-olds (%)r 1-year-olds q (%) p (%) 2016

2016

2007– 2014

94 99 90 99 99 99 99 81 82 98 71 69 99 91 92 99 98 72 86 98 62 97 99 78 94 64 96 97 86

95 98 81 99 90 94 96 80 76 96 75 70 98 98 92 99 96 70 80 98 68 95 99 84 96 53 99 96 85

24 22 66 36 39

30-day mortality after admission to hospital for acute myocardial infarctionk

Postoperative sepsis ratek

2011–2014 2013–2014 4.0

12.2

6.6

8.3 11.0

1457.6 256.4

Efficiency and sustainability

Health financing General government health expenditure as percentage of total health expenditure (%)t (proxy)

Occupancy rate of curative (acute) care bedsk

Hospital average length of stay (in days)k

Total expenditure on health as a percentage of gross domestic products

2012

2014–2015

2014

75.9

5.3 4.3 10.0

9.4 2.6 5.7 5.5 3.4 4.5 10.2 10.2 1.9 4.2 17.1 13.7 4.7 3.3 11.0 7.4 9.0 4.3 4.7 7.4 7.2 4.9 5.1 5.2 16.5 5.0 7.1

67.0 93.9 22.0 55.8 90.1 65.8 83.6 81.2 50.5 55.2 84.3 90.7 55.4 86.2 82.3 98.4 72.4 81.3 34.3 54.1 90.6 41.7 91.9 82.4 99.2 89.8 54.1

World Health Statistics [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http:// www.who.int/gho/en/, accessed 03 November 2017) q Immunization [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who. int/gho/en/, accessed 03 November 2017). r Cataract [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who.int/gho/ en/, accessed 12 July 2017). s Health Systems [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who. int/gho/en/, accessed 12 July 2017). t Health Systems [online database]. Global Health Observatory (GHO) data. Geneva: World Health Organization (http://www.who. int/gho/en/, accessed 12 July 2017). This indicator is used here as a proxy for the UHC indicator current expenditure on health by general government and compulsory schemes as a percentage of total current expenditure on health. p

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Appendix 3. Coverage of essential health services and an alternative health expenditure measure (as proxy for financial risk protection) SDG 3.8.1 (target=100)

Member State

Universal health coverage UHC UHC tracer (UHC) tracer tracer index for nonindex for index for communicable reproductive, infectious diseases a maternal, diseases a newborn and child health a

Health expenditure indicators

UHC Out-ofGross tracer pocket domestic OOPS/ OOPS per GDP in index for expenditure product GDP per capita in current service (OOPS) (GDP) in current US$ per capacity per capita current capita (%) US$ b capita b and in current US$ per a b b access US$ capita

2004– 2015

2002– 2015

Australia Brunei Darussalam

90.5 91.8

81.6 73.2

69.2 71.7

99.9 97.0

1134.8 64 008.9 57.5 36 161.1

1.8 0.2

1178.0 66 837.0 79.0 39 153.0

1.8 0.2

4357.3 1777.8

Cambodia China Cook Islands Fiji Japan Kiribati Lao People’s Democratic Republic Malaysia Marshall Islands Micronesia (Federated States of) Mongolia Nauru New Zealand Niue Palau Papua New Guinea Philippines Republic of Korea Samoa Singapore Solomon Islands Tonga Tuvalu Vanuatu Viet Nam

72.3 85.9 78.0 81.6 85.7 66.0 58.8 77.7 70.2 67.2 81.8 62.2 89.9 72.4 76.5 59.1 64.7 89.3 60.8 88.7 71.3 67.4 71.8 61.4 81.7

58.8 63.1 15.9 59.1 69.2 48.4 43.2 56.0 61.5 55.8 39.6 61.6 80.1 70.2 58.8 36.8 54.1 81.8 64.5 71.1 45.4 69.3 53.5 53.9 62.3

67.3 63.0 42.4 55.6 67.8 12.9 58.8 60.2 14.2 48.5 53.6 40.3 70.1 67.0 53.1 40.0 65.2 69.2 37.6 75.2 48.8 44.8 60.2 64.9 65.5

32.9 99.8 51.3 70.0 99.8 61.5 34.2 89.4 43.4 70.1 88.4 43.1 99.4 50.8 95.6 33.3 49.5 99.9 65.0 99.8 39.2 71.4 72.2 45.6 84.0

45.5 1079.8 134.3 7565.2 51.1 15 324.4 46.9 4546.2 515.1 36 201.4 1509.6 12.7 1745.9 160.9 10 933.5 73.7 3648.5 37.6 3027.6 81.3 4129.4 9.3 15 524.4 540.8 44 392.8 19.1 15 607.6 176.6 12 750.6 2166.2 72.6 2870.5 743.5 27 942.7 4173.1 55 909.7 4.7 2024.2 4114.1 3826.9 3135.4 52.3 2014.7

4.2 1.8 0.3 1.0 1.4 0.0 0.7 1.5 2.0 1.2 2.0 0.1 1.2 0.1 1.4 0.0 2.5 2.7

44.0 127.0 50.0 38.0 550.0 0.5 13.0 154.0 73.0 38.0 82.0 9.0 508.0 19.0 177.0 10.0 72.0 658.0 18.0 1466.0 5.0 26.0 5.0 9.0 49.0

4.3 1.8 0.3 0.9 1.4 0.0 0.8 1.5 2.0 1.3 1.9 0.1 1.2 0.1 1.5 0.5 2.6 2.5 0.4 2.6 0.2 0.6 0.1 0.3 2.6

183.2 730.5 486.4 364.1 3726.7 183.6 98.5 1040.2 679.6 472.6 565.1 511.5 4018.3 886.7 1428.9 109.5 328.9 2530.6 417.8 4047.0 107.6 269.8 585.0 150.4 390.5

Year

2008–2015 2004– 2015

Per capita OOPS/ total health GDP per expenditure capita (in PPP (%) int. $)b

2014

2013

0.2

2.6

1019.0 6966.0 14 624.0 4378.0 38 646.0 1556.0 1635.0 10 628.0 3618.0 3037.0 4388.0 15 100.0 41 722.0 15 449.0 11 760.0 2109.0 2788.0 25 985.0 4181.0 55 920.0 1890.0 4117.0 3910.0 3167.0 1874.0

2014

Values for tracer indicators used to compute the index are based on publicly available data mostly from 2010–2015, including existing WHO/UN agency estimates, country data reported to WHO, and published results from household surveys. The inputs have been selected for comparability. In cases where no country estimates are available, regional default values have been used as placeholders to allow for the calculation of the index. b Global Health Expenditure Database [online database]. Geneva. World Health Organization. (http://apps.who.int/nha/database/ Select/Indicators/en, accessed 11 August 2016). a

Appendices

Fig. A. Overall progress towards the delivery of universal health coverage (UHC) in reproductive, maternal newborn and child health, 11 Western Pacific countries

Financial risk protection (SDG 3.8.2)*

VNM

KHM

CHN JPN

KOR

3% 2%

PHL

MNG AUS

LAO

FJI

MYS

0% 20

100

UHC tracer index for reproductive, maternal newborn and child health (target=100) -(SDG3.8.1)** AUS = Australia, KHM = Cambodia, CHN = China, FJI = Fiji, JPN = Japan, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MNG = Mongolia, PHL = Philippines, KOR = Republic of Korea, VNM = Viet Nam. * Proportion of population with out-of-pocket health spending exceeding 25% of total household consumption or income (%), 2005–2015. The 2% threshold is not a target. It was arbitrarily selected to map countries in a way that allows cross-country comparison and a baseline position for future trend analysis. ** It measures the extent to which those in need for family planning, pregnancy and delivery care, child immunization and treatment receive the care they need, 2004–2015. Source: WHO

Fig. B. Overall progress towards the delivery of universal health coverage (UHC) in infectious diseases, 11 Western Pacific countries

Financial risk protection (SDG 3.8.2)*

VNM CHN

KHM

JPN

KOR

3% 2% MNG

PHL AUS

LAO MYS

FJI

0% 20

50 60 70 80 UHC tracer index for infectious diseases (target=100) -(SDG 3.8.1)**

100

AUS = Australia, KHM = Cambodia, CHN = China, FJI = Fiji, JPN = Japan, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MNG = Mongolia, PHL = Philippines, KOR = Republic of Korea, VNM = Viet Nam. * Proportion of population with out-of-pocket health spending exceeding 25% of total household consumption or income (%), 2005–2015. The 2% threshold is not a target. It was arbitrarily selected to map countries in a way that allows cross-country comparison and a baseline position for future trend analysis. ** It measures: (i) the extent to which those in need for TB and HIV treatment and malaria prevention receive the care and services they need; and (ii) access to improved sanitation, 2002–2015. Source: WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Fig. C. Overall progress towards the delivery of universal health coverage (UHC) in noncommunicable diseases, 11 Western Pacific countries

6% VNM

KHM

Financial risk protection (SDG 3.8.2)*

CHN

JPN KOR

4% 3% 2% MNG

PHL AUS

LAO FJI

MYS

0% 20

100

UHC tracer index for noncommunicable diseases (target=100) -(SDG 3.8.1)** AUS = Australia, KHM = Cambodia, CHN = China, FJI = Fiji, JPN = Japan, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MNG = Mongolia, PHL = Philippines, KOR = Republic of Korea, VNM = Viet Nam. * Proportion of population with out-of-pocket health spending exceeding 25% of total household consumption or income (%), 2005–2015. The 2% threshold is not a target. It was arbitrarily selected to map countries in a way that allows cross-country comparison and a baseline position for future trend analysis. ** It measures the current status of NCD risk factors in the population, including blood pressure, glucose level and tobacco consumption, as a proxy indicator of success of both prevention efforts and screening and treatment programmes, 2008–2015. Source: WHO

Fig. D. Overall progress towards the delivery of universal health coverage (UHC) in service capacity and access, 11 Western Pacific countries

Financial risk protection (SDG 3.8.2)*

VNM

KHM

CHN JPN KOR

4% 3% 2% MNG

PHL

AUS

LAO FJI

MYS

0% 20

40 50 60 70 80 UHC tracer index for service capacity and access (target=100) -(SDG 3.8.1)**

100

AUS = Australia, KHM = Cambodia, CHN = China, FJI = Fiji, JPN = Japan, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MNG = Mongolia, PHL = Philippines, KOR = Republic of Korea, VNM = Viet Nam. * Proportion of population with out-of-pocket health spending exceeding 25% of total household consumption or income (%), 2005–2015. The 2% threshold is not a target. It was arbitrarily selected to map countries in a way that allows cross-country comparison and a baseline position for future trend analysis. ** It measures general features of service capacity and access to care within a health system. Measures include hospital beds and health professionals per capita, and a measure of health security for responding to epidemics and other health threats, 2004–2015. Source: WHO

Appendices

Fig. E. Overall progress towards the delivery of universal health coverage (UHC) in reproductive,

maternal newborn and child health, using an alternative health expenditure measure, 27 Western Pacific countries

6% 5% Proxy measure for financial protection (OOPS/GDP per capita, %)*

KHM 4% 3%

PHL

VNM

MHL

MNG MYS

FSM

LAO PNG NRU 60

0% 20

WSM VUT

TON KIR

SGP KOR

SLB TUV NIU 70

CHN

PLW FJI

AUS

JPN

NZL

COK

BRN

100

UHC tracer index for reproductive, maternal newborn and child health (target=100) -(SDG3.8.1)** AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. * OOPS: out-of-pocket expenditure per capita in US$, 2013; GDP: gross domestic product in current US$ per capita, 2013. This indicator does not necessarily measure financial risk protection and is not a replacement for the UHC financial risk protection indicator (3.8.2). The 2% threshold is not a target. It was arbitrarily selected to map countries in a way that allows cross-country comparison and a baseline position for future trend analysis. ** It measures the extent to which those in need for family planning, pregnancy and delivery care, child immunization and treatment receive the care they need, 2004–2015. Source: WHO

Fig. F. Overall progress towards the delivery of universal health coverage (UHC) in infectious diseases, using an alternative health expenditure measure, 27 Western Pacific countries

Proxy measure for financial protection (OOPS/GDP per capita, %)*

5% KHM

4% 3%

SGP

VNM

PHL

KOR

MHL

MNG

MYS

LAO

PNG

SLB

0% 20

CHN

PLW

WSM KIR

AUS JPN

FSM FJI VUT TUV

NRU

NZL

TON NIU

BRN

50 60 70 80 UHC tracer index for infectious diseases (target=100) -(SDG 3.8.1)**

100

AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. * OOPS: out-of-pocket expenditure per capita in US$, 2013; GDP: gross domestic product in current US$ per capita, 2013. This indicator does not necessarily measure financial risk protection and is not a replacement for the UHC financial risk protection indicator (3.8.2). The 2% threshold is not a target. It was arbitrarily selected to map countries in a way that allows cross-country comparison and a baseline position for future trend analysis. ** It measures: (i) the extent to which those in need for tuberculosis (TB) and HIV treatment and malaria prevention receive the care and services they need; and (ii) access to improved sanitation, 2002–2015. Source: WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Fig. G. Overall progress towards the delivery of universal health coverage (UHC) in

noncommunicable diseases, using an alternative health expenditure measure, 27 Western Pacific countries

Proxy measure for financial protection (OOPS/GDP per capita, %)*

5% KHM

4% 3% PHL

VNM KOR

SGP

MNG

PLW CHN FJI LAO

FSM

1% WSM

PNG

TON COK

SLB

NRU

0% 20

MYS JPN

AUS NZL

VUT NIU

TUV

BRN

100

UHC tracer index for noncommunicable diseases (target=100) - (SDG 3.8.1)** AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. * OOPS: out-of-pocket expenditure per capita in US$, 2013; GDP: gross domestic product in current US$ per capita, 2013. This indicator does not necessarily measure financial risk protection and is not a replacement for the UHC financial risk protection indicator (3.8.2). The 2% threshold is not a target. It was arbitrarily selected to map countries in a way that allows cross-country comparison and a baseline position for future trend analysis. ** It measures the current status of noncommunicable disease (NCD) risk factors in the population, including blood pressure, glucose level and tobacco consumption, as a proxy indicator of success of both prevention efforts and screening and treatment programmes, 2008–2015. Source: WHO

Fig. H. Overall progress towards the delivery of universal health coverage (UHC) in service capacity and access, using an alternative health expenditure measure, 27 Western Pacific countries

Proxy measure for financial protection (OOPS/GDP per capita, %)*

5% KHM

4% 3%

SGP

VNM

PHL MHL

MNG

PLW

FSM LAO

1% PNG

0% 20

SLB

NRU

VUT

COK NIU

WSM KIR

MYS

FJI TON

KOR CHN AUS JPN NZL

BRN

TUV

100

UHC tracer index for service capacity and access (target=100) - (SDG 3.8.1)** AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. * OOPS: out-of-pocket expenditure per capita in US$, 2013; GDP: gross domestic product in current US$ per capita, 2013. This indicator does not necessarily measure financial risk protection and is not a replacement for the UHC financial risk protection indicator (3.8.2). The 2% threshold is not a target. It was arbitrarily selected to map countries in a way that allows cross-country comparison and a baseline position for future trend analysis. ** It measures general features of service capacity and access to care within a health system. Measures include hospital beds and health professionals per capita, and a measure of health security for responding to epidemics and other health threats, 2004–2015. Source: WHO

Appendices

Appendix 4. Equity analysis for reproductive, maternal, newborn and child health Table A. List of Indicators from the SDGs and UHC Regional Monitoring Framework that relate

to reproductive, maternal, newborn and child health (RMNCH), grouped according to the indicator domain of the Framework

Indicator

SDG and UHC regional monitoring framework indicator domain

Adolescent fertility rate (per 1000 women aged 15â&#x20AC;&#x201C;19 years) Births attended by skilled health personnel (in the two or three years preceding the survey) (%) Children aged <5 years with pneumonia symptoms taken to a health facility (%)

Life expectancy and well-being

SDG 3.7.2

Health service coverage

SDG 3.1.2

Health service coverage

SDG 3.8.1

Individual characteristics and behaviours

Demand for family planning satisfied with modern methods (%)

Health service coverage

Additional indicators to monitor universal health coverage (UHC) SDG 3.8.1

DTP3 immunization coverage among 1-year-olds (%)*

Health service coverage

SDG 3.7.1 SDG 3.8.1

Effectiveness Measles immunization coverage among 1-year-olds (%)

Effectiveness

Neonatal mortality rate (deaths per 1000 live births) Stunting prevalence in children aged <5 years (%) Under-5 mortality rate (deaths per 1000 live births) Wasting prevalence in children aged <5 years (%)

Mortality Morbidity Mortality Morbidity

*Percentage of infants receiving three doses of diphtheria-tetanus-pertussis-containing vaccine. Source: WHO

Reference

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Additional indicators to monitor UHC Additional indicators to monitor UHC SDG 3.2.2 SDG 2.2.1 SDG 3.2.1 SDG 2.2.2

Table B. Indicators related to reproductive, maternal, newborn and child health disaggregated by five stratifiers, Cambodia, 2014

Stratifier Economic status Quintile 1 (poorest) Quintile 2 Quintile 3 Quintile 4 Quintile 5 (richest) Education No education Primary school Secondary school + Place of residence Rural Urban Sex Female Male Subnational region 01 Banteay Mean Chey 02 Kampong Cham 03 Kampong Chhnang 04 Kampong Speu 05 Kampong Thom 06 Kandal 07 Kratie 08 Phnom Penh 09 Prey Veng 10 Pursat 11 Siem Reap 12 Svay Rieng 13 Takeo 14 Otdar Mean Chey 15 Battambang & Pailin 16 Kampot & Kep 17 Preah Sihanouk & Kaoh Kong 18 Preah Vihear & Steung Treng 19 Mondol Kiri & Rattanak Kiri

Indicators (Ind.) on reproductive, maternal, newborn and child health* Ind. 1 Ind. 2 Ind. 3 Ind. 4 Ind. 5 Ind. 6 Ind. 7 Ind. 8 Ind. 9 Ind. 10 91.8 63.4 62.9 44.4 33.0

67.9 64.9 78.1 67.3 66.5

71.6 78.3 83.2 94.3 96.2

95.3 97.7 97.4 97.8 98.3

65.9 71.7 77.7 87.6 94.7

26.4 22.8 24.1 17.4 11.8

79.0 90.9 95.3 97.9 98.7

41.9 37.1 31.7 29.1 18.4

74.9 57.0 40.9 32.9 18.4

11.0 11.4 8.4 9.3 7.4

126.2 83.6 36.6

66.1 66.8 74.9

69.0 80.2 94.2

96.5 97.0 98.3

65.5 75.3 88.0

22.0 21.9 18.6

76.0 91.6 97.6

39.2 34.0 25.6

79.8 45.4 29.5

11.7 9.5 9.4

64.7 21.7

68.6 69.6

82.2 92.9

97.3 97.4

76.5 90.7

22.8 9.7

90.6 98.5

33.8 23.7

52.0 17.7

9.9 7.5

75.9 62.2

84.3 83.3

78.1 79.1

20.0 21.9

31.9 32.9

41.2 53.3

9.3 9.9

59.0 91.3 32.5 44.0 58.5 48.5 90.1 14.5 76.2 50.3 45.3 57.5 53.2 66.3 61.6 72.8 42.0 67.1 112.7

94.6

59.6 62.8

75.0

78.4

94.0 71.4 86.3 78.2 82.0 81.5 72.8 93.1 76.0 83.3 90.9 88.8 97.9 83.4 95.4 80.0 92.0 80.0

97.6 95.5 97.6 98.0 98.6 97.2 96.1 97.8 98.4 98.6 96.3 98.1 98.5 96.4 97.3 96.4 97.6 95.1

93.4 64.1 74.6 66.5 74.1 75.2 79.7 91.0 63.2 88.9 85.1 86.7 94.2 85.3 89.6 81.1 86.4 62.8

19.1 25.6 26.6 19.5 29.3 16.7 29.7 13.1 32.6 14.2 16.1 20.1 15.8 16.9 12.3 20.5 19.9 25.7

96.7 94.3 100.0 91.5 82.9 96.3 57.0 96.8 99.4 92.3 97.8 96.6 97.0 93.3 98.3 94.4 97.2 61.2

28.6 33.5 42.8 40.5 36.4 28.1 38.4 17.9 32.7 38.8 35.9 32.8 30.7 36.3 24.7 25.2 33.4 44.3

31.3 45.3 55.2 30.2 59.8 40.6 79.4 22.5 74.1 35.0 55.9 63.4 31.7 41.9 37.1 44.2 41.2 79.3

7.8 8.1 11.2 11.5 13.0 9.2 6.5 8.4 8.6 12.3 9.5 7.6 14.6 15.1 8.0 8.2 10.5 13.8

55.9

98.0

56.1

36.4

55.7

39.8

81.6

8.2

Indicator Definition Ind. 1 Adolescent fertility rate (per 1000 women aged 15â&#x20AC;&#x201C;19 years) Ind. 2 Children aged <5 years with pneumonia symptoms taken to a health facility (%) Ind. 3 Three doses of diphtheria tetanuspertussis (DTP3) immunization coverage among 1-year-olds (%) Ind. 4 Demand for family planning satisfied with modern methods (%) Ind. 5 Measles immunization coverage among 1-yearolds (%) Ind. 6 Neonatal mortality rate (deaths per 1000 live births) Ind. 7 Births attended by skilled health personnel (in the two or three years preceding the survey) (%) Ind. 8 Stunting prevalence in children aged <5 years (%) Ind. 9 Under-5 mortality rate (deaths per 1000 live births) Ind. 10 Wasting prevalence in children aged <5 years (%)

Appendices

Table B. Indicators related to reproductive, maternal, newborn and child health (RMNCH) disaggregated by five stratifiers, Lao Peopleâ&#x20AC;&#x2122;s Democratic Republic, 2011 (continued)

Stratifier Economic status Quintile 1 (poorest) Quintile 2 Quintile 3 Quintile 4 Quintile 5 (richest) Education No education Primary school Secondary school + Place of residence Rural Urban Sex Female Male Subnational region 01 Vientiane Capital 02 Phongsaly 03 Luangnamtha 04 Oudomxay 05 Bokeo 06 Luangprabang 07 Huaphanh 08 Xayabury 09 Xiengkhuang 10 Vientiane 11 Borikhamxay 12 Khammuane 13 Savannakhet 14 Saravane 15 Sekong 16 Champasack 17 Attapeu

Indicators (Ind.) on reproductive, maternal, newborn and child health* Ind. 1 Ind. 2 Ind. 3 Ind. 4 Ind. 5 Ind. 6 Ind. 7 Ind. 8 Ind. 9 Ind. 10 42.1 48.7 63.6 69.7 85.5

36.8 46.7 59.9 67.9 81.4

50.5 55.7 69.4 72.5 81.9

10.8 23.9 45.0 64.3 90.7

60.6 50.2 41.9 31.7 19.7

6.4 6.4 5.8 5.2 5.1

40.4 53.5 76.7

33.6 57.1 76.5

45.3 66.2 79.9

16.1 34.8 75.3

57.9 43.2 29.1

5.8 5.9 6.1

50.6 79.0

51.8 67.7

61.5 71.7

30.7 79.6

48.6 27.4

6.1 5.4

55.9 53.2

55.5 55.7

66.1 61.7

42.6 45.7

5.4 6.4

66.5 23.8 67.9 54.4 37.6 59.1 53.3 91.8 36.5 68.7 65.6 67.1 34.0 68.0 40.3 62.9 49.6

71.3 42.4 78.0 57.9 53.2 64.6 54.4 88.2 48.6 74.8 75.1 73.3 40.4 81.5 74.8 74.0 58.7

19.3 61.1 53.2 54.9 46.0 45.6 61.1 39.0 52.9 42.6 40.8 40.8 40.8 54.4 62.7 36.7 39.7

7.2 5.1 21.2 4.6 4.7 3.1 1.9 5.5 2.0 4.6 6.2 7.1 5.0 8.6 7.3 6.8 10.6

43.8

51.1

51.5 38.9 54.9

85.4 18.7 44.4 22.2 32.1 36.7 24.5 44.0 36.7 54.4 56.3 35.1 42.2 31.1 24.6 39.9 19.7

Indicator Definition Ind. 1 Adolescent fertility rate (per 1000 women aged 15â&#x20AC;&#x201C;19 years) Ind. 2 Children aged <5 years with pneumonia symptoms taken to a health facility (%) Ind. 3 Three doses of diphtheria tetanuspertussis (DTP3) immunization coverage among 1-year-olds (%) Ind. 4 Demand for family planning satisfied with modern methods (%) Ind. 5 Measles immunization coverage among 1-year-olds (%) Ind. 6 Neonatal mortality rate (deaths per 1000 live births) Ind. 7 Births attended by skilled health personnel (in the two or three years preceding the survey) (%) Ind. 8 Stunting prevalence in children aged <5 years (%) Ind. 9 Under-5 mortality rate (deaths per 1000 live births) Ind. 10 Wasting prevalence in children aged <5 years (%)

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Table B. Indicators related to reproductive, maternal, newborn and child health (RMNCH) disaggregated by five stratifiers, Mongolia, 2010 (continued)

Indicators (Ind.) on reproductive, maternal, newborn and child health* Ind. 1

Ind. 2

Ind. 3

Ind. 4

Ind. 5

Ind. 6

Ind. 7

Ind. 8

Ind. 9

Ind. 10

91.2 92.5 92.7 91.6 96.2

87.5 81.8 85.5 88.3 88.9

97.7 99.0 98.7 99.8 99.3

25.2 18.4 11.4 11.9 6.5

1.2 1.5 2.3 2.3 0.8

87.4

90.4 93.2 92.8

79.9 89.7 86.4

97.5 97.7 99.0

28.2 21.1 14.1

1.0 2.0 1.6

89.9

91.0 93.8

84.4 87.8

98.0 99.4

19.9 11.9

1.3 1.9

90.9 82.9

92.5 92.9

89.5 83.3

13.5 17.1

1.3 1.9

92.0

87.8 93.7 89.3 94.8 95.0

75.9 93.1 83.4 88.4 87.0

24.5 18.0 12.9 15.5 10.8

1.4 1.7 0.8 1.0 2.2

97.8 99.2 98.7 99.0 99.0

Indicator Definition Ind. 1 Adolescent fertility rate (per 1000 women aged 15â&#x20AC;&#x201C;19 years) Ind. 2 Children aged <5 years with pneumonia symptoms taken to a health facility (%) Ind. 3 Three doses of diphtheria tetanuspertussis (DTP3) immunization coverage among 1-year-olds (%) Ind. 4 Demand for family planning satisfied with modern methods (%) Ind. 5 Measles immunization coverage among 1-year-olds (%) Ind. 6 Neonatal mortality rate (deaths per 1000 live births) Ind. 7 Births attended by skilled health personnel (in the two or three years preceding the survey) (%) Ind. 8 Stunting prevalence in children aged <5 years (%) Ind. 9 Under-5 mortality rate (deaths per 1000 live births) Ind. 10 Wasting prevalence in children aged <5 years (%)

Appendices

Table B. Indicators related to reproductive, maternal, newborn and child health (RMNCH) disaggregated by five stratifiers, Philippines, 2013 (continued)

Stratifier Economic status Quintile 1 (poorest) Quintile 2 Quintile 3 Quintile 4 Quintile 5 (richest) Education No education Primary school Secondary school + Place of residence Rural Urban Sex Female Male Subnational region 01 National Capital Region 02 Cordillera Admin Region 03 I – Ilocos Region 04 II – Cagayan Valley 05 III – Central Luzon 06 IVA – Calabarzon 07 IVB – Mimaropa 08 V – Bicol 09 VI – Western Visayas 10 VII – Central Visayas 11 VIII – Eastern Visayas 12 IX – Zamboanga Peninsula 13 X – Northern Mindanao 14 XI – Davao 15 XII – Soccsksargen 16 XIII – Caraga 17 Autonomous Region in Muslim Mindanao (ARMM)

Indicators (Ind.) on reproductive, maternal, newborn and child health* Ind. 1 Ind. 2 Ind. 3 Ind. 4 Ind. 5 Ind. 6 Ind. 7 Ind. 8 Ind. 9 Ind. 10 107.5 73.0 64.8 49.9 22.7

56.2 55.1 68.7 71.5 82.8

78.5 83.7 89.1 91.6 93.0

72.1 79.5 80.8 79.6 74.7

72.9 85.9 87.4 88.8 89.2

19.5 13.1 8.3 14.9 8.6

46.4 74.2 85.7 94.5 97.0

52.4 32.9 21.8 22.6 15.8

144.7 49.7

60.3 64.9

33.8 80.0 88.8

55.5 76.3 78.1

36.1 77.5 86.4

21.6 18.3 12.0

19.5 51.9 83.0

59.0 52.8 24.5

67.1 52.3

59.7 69.6

84.6 87.9

76.2 78.8

82.2 85.6

17.7 8.9

67.5 84.8

38.2 25.0

64.3 63.4

85.4 87.0

84.9 82.8

13.9 13.4

83.8

91.3 96.4 81.3 78.8 86.4 89.7 76.8 80.3 89.8 86.0 98.3 84.6 85.4 92.1 86.6 92.6

82.8 85.1 74.8 80.0 83.5 77.4 71.7 64.3 75.4 76.9 85.2 70.8 74.6 76.7 79.6 81.7

86.3 92.7 81.1 78.8 87.3 89.9 78.8 82.9 89.8 87.1 80.8 76.9 81.4 88.2 77.6 85.1

6.9

36.3

47.3

43.5

48.5 56.4 68.4 77.1 62.2 57.3 80.4 55.7 55.9 50.8 54.4 48.6 50.8 73.1 69.5 85.5 60.9

67.0

66.7 60.6 40.7

57.7 57.8

30.4 33.7

15.2 16.4 13.9 11.3 17.4 16.9 14.6 18.4 10.5 11.2 15.7 11.5 28.9 18.1

91.6 88.4 94.2 68.3 89.5 86.0 44.1 72.9 70.7 86.7 73.4 55.3 64.5 71.2 57.6 66.8

22.0 25.9 21.6 30.5 22.4 42.3 32.4 30.8 33.9 32.4 35.6 46.8 38.0 51.4 38.3

10.8

21.3

53.9

Indicator Definition Ind. 1 Adolescent fertility rate (per 1000 women aged 15–19 years) Ind. 2 Children aged <5 years with pneumonia symptoms taken to a health facility (%) Ind. 3 Three doses of diphtheria tetanuspertussis (DTP3) immunization coverage among 1-year-olds (%) Ind. 4 Demand for family planning satisfied with modern methods (%) Ind. 5 Measles immunization coverage among 1-year-olds (%) Ind. 6 Neonatal mortality rate (deaths per 1000 live births) Ind. 7 Births attended by skilled health personnel (in the two or three years preceding the survey) (%) Ind. 8 Stunting prevalence in children aged < 5 years (%) Ind. 9 Under-5 mortality rate (deaths per 1000 live births) Ind. 10 Wasting prevalence in children aged <5 years (%)

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Table B. Indicators related to reproductive, maternal, newborn and child health (RMNCH) disaggregated by five stratifiers, Vanuatu, 2007 (continued)

Indicators(Ind.) on reproductive, maternal, newborn and child health* Ind. 1 Ind. 2 Ind. 3 Ind. 4 Ind. 5 Ind. 6 Ind. 7 Ind. 8 Ind. 9 Ind. 10

52.8

66.5

47.9 70.9 67.3 73.4 72.5

41.5 63.7 55.7 54.5 54.9

55.0 78.0 72.7 86.9 89.9

28.6 26.0 26.1 23.7 24.2

5.8 7.2 3.8 4.9 7.9

36.9 66.1 73.8

28.2 59.9 50.9

51.4 71.5 86.2

30.3 26.1 24.0

8.1 5.2 6.8

63.9 74.4

54.3 55.2

71.6 86.8

25.9 26.0

5.2 8.9

64.5 66.7

53.0 55.7

20.0 31.2

5.5 6.2

56.3 85.4 75.8 51.4 52.0 30.3 75.8 70.5

50.0 61.0 66.7 48.6 42.3 43.8 56.3 52.3

25.8 22.0 29.2 27.5 26.8 17.8 27.5 19.5

1.1 4.4 2.7 7.4 10.7 8.5 9.0 8.7

66.3 94.1 71.8 78.9 59.1 32.0 94.7 69.2

Indicator Definition Ind. 1 Adolescent fertility rate (per 1000 women aged 15â&#x20AC;&#x201C;19 years) Ind. 2 Children aged <5 years with pneumonia symptoms taken to a health facility (%) Ind. 3 Three doses of diphtheria tetanuspertussis (DTP3) immunization coverage among 1-year-olds (%) Ind. 4 Demand for family planning satisfied with modern methods (%) Ind. 5 Measles immunization coverage among 1-year-olds (%) Ind. 6 Neonatal mortality rate (deaths per 1000 live births) Ind. 7 Births attended by skilled health personnel (in the two or three years preceding the survey) (%) Ind. 8 Stunting prevalence in children aged <5 years (%) Ind. 9 Under-5 mortality rate (deaths per 1000 live births) Ind. 10 Wasting prevalence in children aged <5 years (%)

Appendices

Table B. Indicators related to reproductive, maternal, newborn and child health (RMNCH) disaggregated by five stratifiers, Viet Nam, 2013 (continued)

Stratifier Economic status Quintile 1 (poorest) Quintile 2 Quintile 3 Quintile 4 Quintile 5 (richest) Education No education Primary school Secondary school + Place of residence Rural Urban Sex Female Male Subnational region 01 Red River Delta 02 Northern Midlands and Mountain area 03 North Central and Central Coastal area 04 Central Highlands 05 South East 06 Mekong River Delta

Indicators (ind.)on reproductive, maternal, newborn and child health* Ind. 1

Ind. 2

Ind. 3

68.0

83.3 86.7 90.7 91.3 91.8

82.6 93.8 95.5 93.7 88.8

73.4 96.8 99.7 99.0 100.0

84.6

66.4 87.8 90.4

70.7 87.7 92.7

36.8 88.1 97.8

81.1 81.2

89.2 88.6

92.1 88.9

91.6 99.0

75.8 85.2

90.1 88.0

92.7 89.6

96.0 84.2 90.2 76.4 84.7 90.9

97.2 90.4 94.0 83.9 82.1 91.3

76.3

Ind. 4

Ind. 5

Ind. 6

Ind. 7

97.6 77.5 98.5 81.0 98.1 99.4

Ind. 8

Ind. 9 Ind. 10

Indicator Definition Ind. 1 Adolescent fertility rate (per 1000 women aged 15â&#x20AC;&#x201C;19 years) Ind. 2 Children aged <5 years with pneumonia symptoms taken to a health facility (%) Ind. 3 Three doses of diphtheria tetanuspertussis (DTP3) immunization coverage among 1-year-olds (%) Ind. 4 Demand for family planning satisfied with modern methods (%) Ind. 5 Measles immunization coverage among 1-year-olds (%) Ind. 6 Neonatal mortality rate (deaths per 1000 live births) Ind. 7 Births attended by skilled health personnel (in the two or three years preceding the survey) (%) Ind. 8 Stunting prevalence in children aged <5 years (%) Ind. 9 Under-5 mortality rate (deaths per 1000 live births) Ind. 10 Wasting prevalence in children aged <5 years (%)

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Fig. A. DTP3 immunization coverage among 1-year-olds (%) by education, place of residence and sex

Education (three levels)

100

L3 L1

90 L3 (Secondary school +)

L2 (Primary school)

Lao People‘s Democratic Republic

Phillipines

Cambodia

Place of residence

100

Urban Rural

Urban

Rural Urban Rural

Rural

80 Coverage (%)

Viet Nam

L1 (No education)

Vanuatu

Mongolia

Coverage (%)

Urban Urban

Urban Rural

60 Rural

Viet Nam

Sex

100 90

F M

M F

F M

80 Coverage (%)

Vanuatu

Phillipines

Mongolia

Lao People‘s Democratic Republic

Cambodia

M F

Viet Nam

Vanuatu

Phillipines

Mongolia

Cambodia

Lao People‘s Democratic Republic

DTP3 = Three doses of diphtheria tetanus-pertussis Source: Health Equity Assessment Toolkit (HEAT): Software for exploring and comparing health inequalities in countries. Built-in database edition. Version 1.1. Geneva, World Health Organization, 2017: Cambodia (DHS, 2014), Lao People’s Democratic Republic (MICS, 2011), Mongolia (MICS, 2010), Philippines (DHS, 2013), Vanuatu (MICS, 2007), Viet Nam (MICS, 2013).

Appendices

Fig. B. Under-5 mortality rate (deaths per 1000 live births) by subnational region and economic status

Subnational region

100

Economic status

80 70

Deaths per 1000 live births

Q1 (poorest)

60 50 40

40 30 20

Q5 (richest)

10 Cambodia

Philippines

Cambodia

Philippines

Source: Health Equity Assessment Toolkit (HEAT): Software for exploring and comparing health inequalities in countries. Built-in database edition. Version 1.1. Geneva, World Health Organization, 2017: Cambodia (DHS, 2014), Lao Peopleâ&#x20AC;&#x2122;s Democratic Republic (MICS, 2011), Mongolia (MICS, 2010), Philippines (DHS, 2013), Vanuatu (MICS, 2007), Viet Nam (MICS, 2013).

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Appendix 5.

Equity analysis – NCD risk factors

Table A. List of indicators from the SDGs and UHC Regional Monitoring Framework that relate to noncommunicable disease (NCD) risk factors

SDG and UHC regional monitoring framework indicator domain

Indicator Prevalence of tobacco use

Reference SDG 3.a.1 SDG 3.8.1 SDG 3.5.2

Percentage of current alcohol drinkers engaging in hazardous and harmful drinking in the last seven days Prevalence of low physical activity Prevalence of overweight Prevalence of obesity Prevalence of raised blood pressure, excluding those on medications

Additional indicators to monitor universal health coverage (UHC) Additional indicators to monitor UHC Additional indicators to monitor UHC SDG 3.8.1

Individual characteristics and behaviours

Additional indicators to monitor UHC SDG 3.8.1

Prevalence of raised blood glucose or currently on medications for diabetes

Additional indicators to monitor UHC

Note: All indicators are estimated for the adult population only. Source: WHO

Table B. Indicators related to noncommunicable disease (NCD) risk factors, disaggregated by sex, age and place of residence

Cambodia, 2010

Stratifier

Prevalence of tobacco use (percentage of current smokers, aged 25–64)

Sex Male 54.1 Female 5.9 Age 25–34 24.3 35–44 33.7 45–54 29.3 55–64 34.2 Place of residence Urban 21.4 Rural 31.1

Percentage of current (last 30 days) drinkers engaging in hazardous and harmful drinking in the last 7 days, aged 25–64*

Prevalence of raised blood pressure, Prevalence of aged raised blood 25 –64 (systolic glucose or blood pressure ≥140 currently on and/or diastolic medications blood pressure for diabetes, ≥90 mmHg, aged excluding those on 25 –64**** medications)

Prevalence of low physical activity, aged 25–64**

Prevalence of overweight, aged 25–64, (body mass index 25.0 to 29.9)***

Prevalence of obesity, aged 25–64 (body mass index ≥30.0)

11.6 2.2

10.9 10.3

10.5 16.3

1.1 2.7

11.7 7.2

2.5 3.3

5.9 9.0 7.3 3.7

10.1 9.4 11.1 13.6

8.9 15.2 17.5 15.7

0.9 2.4 2.4 2.7

3.9 9.4 13.8 18.7

1.1 2.2 4.8 6.0

4.8 7.2

14.8 9.7

23.1 11.5

3.6 1.5

12.8 8.7

5.6 2.3

*Harmful drinking is defined as 60 g of pure alcohol on average per day for men and 40 g for women. Hazardous drinking is defined as 40–59.9 g of pure alcohol on average per day for men and 20–39.9 g for women. A standard drink contains approximately 10 g of pure alcohol. **The methodology incorporates activities related to work, travel to and from places, and recreation. ***BMI: Body Mass Index=weight/height2 ****Raised blood glucose is defined as either: plasma venous value: ≥7.0 mmol/L (126 mg/dl), or capillary whole blood value: ≥6.1 mmol/L (110 mg/dl) Source: Ministry of Health and University of Health Sciences (2010). Prevalence of Noncommunicable Disease Risk Factors in Cambodia. STEPS Survey, Country Report. http://www.who.int/chp/steps/reports/en/

Appendices

Table B. Indicators related to noncommunicable disease risk (NCD) factors, disaggregated by sex and age (continued)

Lao People’s Democratic Republic, 2008 Percentage of current (last 30 Prevalence of days) drinkers tobacco use engaging in (percentage hazardous of current and harmful smokers, aged drinking in the 25–64) last 7 days, aged 25–64* Sex Male Female Age 25–34 35–44 45–54 55–64

Prevalence of low physical activity, aged 25–64**

Prevalence of overweight, aged 25 to 64 (BMI 25.0 –29.9***

Prevalence of obesity, aged 25–64 (BMI ≥30.0)

Prevalence of raised blood pressure, aged 25 –64 (SBP ≥140 and/ or DBP ≥90 mmHg, excluding those on medications)

43.2 2.0

20.6 34.8

10.4 16.7

19.4 23.3

4.5 6.6

23.4 16.8

11.9 18.7 23.8 24.1

33.6 24.1 23.9 21.3

14.1 12.7 11.8 20.9

11.9 23.1 25.4 29.4

2.9 7.2 6.7 6.4

8.9 14.3 23.0 40.9

Prevalence of raised blood glucose or currently on medications for diabetes, aged 25 –64****

Source: Lao’s People Democratic Republic (2010). Report on STEPS Survey on Non Communicable Diseases Risk Factors in Vientiane Capital city, the Lao People’s Democratic Republic. http://www.who.int/chp/steps/reports/en/

Niue, 2011 Percentage of current (last 30 Prevalence of days) drinkers tobacco use engaging in (percentage hazardous of current and harmful smokers, aged drinking in the 15+) last 7 days, aged 15+* Sex Male Female Age 15–24 25–34 35–44 45–54 55–64 65+

Prevalence of low physical activity, aged 15+**

Prevalence of raised blood pressure, aged Prevalence of Prevalence 15+ (SBP ≥140 overweight, of obesity, and/or DBP aged 15+ (BMI aged 15+ (BMI ≥90 mmHg, ex25.0 to 29.9*** ≥30.0) cluding those on medications)

Prevalence of raised blood glucose or currently on medications for diabetes, 15+****

22.6 13.0

4.9 2.3

16.8 17.4

25.8 24.1

59.2 62.7

20.1 15.9

42.1 34.9

13.7 20.7 22.7 19.4 18.6 12.0

3.0 6.1 3.7 5.2 2.8 0.7

13.5 16.8 14.4 16.9 12.7 29.3

26.2 28.9 18.9 23.2 22.3 29.5

45.3 59.3 74.9 68.1 67.5 54.6

4.2 14.9 14.7 23.8 28.5 42.5

16.1 23.4 34.3 51.6 53.4 57.3

*Harmful drinking is defined as 60 g of pure alcohol on average per day for men and 40 g for women. Hazardous drinking is defined as 40–59.9 g of pure alcohol on average per day for men and 20–39.9 g for women. A standard drink contains approximately 10 g of pure alcohol. **The methodology incorporates activities related to work, travel to and from places, and recreation. ***BMI: Body Mass Index=weight/height2. ****Raised blood glucose is defined as either plasma venous value: ≥7.0 mmol/L (126 mg/dl), or capillary whole blood value: ≥6.1 mmol/L (110 mg/dl) Source: Niue Health Department and the World Health Organization (2013). Niue NCD Risk Factors. STEPS Report. http://www.who. int/chp/steps/reports/en/

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Table B. Indicators related to noncommunicable disease (NCD) risk factors disaggregated by sex and age (continued)

Papua New Guinea, 2007–2008 Prevalence of tobacco use (percentage of current smokers, aged 15–64)

Percentage of current (last 30 days) drinkers engaging in hazardous and harmful drinking in the last 7 days, aged 15–64*

Prevalence of low physical activity, aged 15–64**

Prevalence of overweight, aged 15–64 (BMI 25.0 to 29.9***

Prevalence of obesity, aged 15 to 64 (BMI ≥30.0)

60.3 27.0

4.9 3.5

9.0 10.9

25.3 25.3

5.1 8.7

9.9 7.2

14.7 14.0

42.3 46.2 46.2 44.1 37.4

3.0 5.6 7.1 4.1 0.0

9.5 8.1 6.8 13.0 24.0

26.8 27.1 26.1 18.9 18.0

4.3 8.0 9.9 7.8 4.1

7.6 6.7 7.2 13.3 17.2

15.3 13.6 12.6 16.6 13.7

Sex Male Female Age 15–24 25–34 35–44 45–54 55–64

Prevalence of raised blood Prevalence of pressure, aged raised blood 15 to 64 (SBP glucose or ≥140 and/ currently on or DBP ≥90 medications for mmHg, exclud- diabetes, aged ing those on 15–64**** medications)

Source: Papua New Guinea National Department of Health (2014). Papua New Guinea NCD Risk Factors. STEPS Report. http://www. who.int/chp/steps/reports/en/

Vanuatu, 2013

Sex Male Female Age 25–34 35–44 45–54 55–64

Prevalence of tobacco use (percentage of current smokers, aged 25–64)

Percentage of current (last 30 days) drinkers engaging in hazardous and harmful drinking in the last 7 days, aged 25–64*

Prevalence of low physical activity, aged 25–64**

Prevalence of overweight, aged 25–64 (BMI 25.0 to 29.9***

Prevalence of obesity, aged 25–64 (BMI ≥30.0)

Prevalence of raised blood pressure, aged 25 –64 (SBP ≥140 and/ or DBP ≥90 mmHg, excluding those on medications)

45.8 4.0

2.2 7.3

10.1 13.2

31.6 32.6

13.9 23.3

29.8 25.7

21.4 21.0

29.3 23.0 17.5 16.2

2.4 7.1 0.0 1.5

11.3 10.5 11.8 15.7

26.8 37.4 35.3 32.5

12.5 20.1 28.0 21.3

15.8 26.5 38.6 53.8

14.9 22.5 26.2 31.5

Prevalence of raised blood glucose or currently on medications for diabetes, aged 25 –64****

*Harmful drinking is defined as 60 g of pure alcohol on average per day for men and 40 g for women. Hazardous drinking is defined as 40–59.9 g of pure alcohol on average per day for men and 20–39.9 g for women. A standard drink contains approximately 10 g of pure alcohol. **The methodology incorporates activities related to work, travel to and from places, and recreation. ***BMI: Body Mass Index=weight/height2 ****Raised blood glucose is defined as either plasma venous value: ≥7.0 mmol/L (126 mg/dl), or capillary whole blood value: ≥6.1 mmol/L (110 mg/dl) Source: Vanuatu Ministry of Health and World Health Organization (2013). Vanuatu NCD Risk Factors. STEPS Report. http://www. who.int/chp/steps/reports/en/

Appendices

Fig. A. Prevalence of tobacco use and overweight by sex and age

Tobacco use Sex

Prevalence (%)

F M

25–34

55–64

Papua New Guinea

Niue

Vanuatu

Niue

45–54

Lao People‘s Democratic Republic

Cambodia

35–44

35–44 25–34 45–54 55–64 15–24

35–44

55–64 45–54

Cambodia

25–34

55–64

Lao People‘s Democratic Republic

55–64 35–44 45–54

45–54 15–24

Papua New Guinea

Prevalence (%)

Age

Vanuatu

Source: World Health Organization. STEPS Country Reports. http://www.who.int/chp/steps/reports/en/

Overweight Sex

45–54 35–44

20 15

45–54 55–64 35–44

25–34

Vanuatu

0 Papua New Guinea

Niue

Cambodia

25–34 15–24 45–54 55–64

25–34 15–24 35–44

35–44

45–54 55–64

Source: World Health Organization. STEPS Country Reports. http://www.who.int/chp/steps/reports/en/

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

45–54 55–64 25–34

25–34

Papua New Guinea

55–64

Niue

M F

Lao People‘s Democratic Republic

Prevalence (%)

M F

Lao People‘s Democratic Republic

Prevalence (%)

35–44

Vanuatu

F M

Age

Cambodia

Fig. B. Prevalence of raised blood pressure by sex and age Sex

M F

5 0

30 20

55–64

45–54 35–44

Cambodia

Vanuatu

Papua New Guinea

Niue

Lao People‘s Democratic Republic

45–54

55–64 45–54

35–44

25–34 35–44

35–44

55–64 45–54 15–24 35–44 25–34

25–34 15–24

25–34

0 Cambodia

45–54

25–34

Vanuatu

55–64

Papua New Guinea

55–64

Niue

Lao People‘s Democratic Republic

Age

Prevalence (%)

Source: World Health Organization. STEPS Country Reports. http://www.who.int/chp/steps/reports/en/

Appendices

Appendix 6.

Equity analysis – Papua New Guinea

Fig. A. Antenatal coverage: percentage of pregnant women that attended at least one antenatal

visit at hospital, health centre or outreach clinic during the pregnancy, stratified by province, Papua New Guinea, 2011–2015, 22 provinces

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2010

2011

2012

2013

2014

2015

2016

Year Source: Papua New Guinea (2016). 2015 Sector Performance Annual Review. (http://www.health.gov.pg/publications/2015_SPAR. pdf )

Fig. B. The percentage of children under 5 years of age who were admitted to the health centre with pneumonia and died during that admission, stratified by province, Papua New Guinea, 2011–2015, 22 provinces

9% 8% 7% 6% 5% 4% 3% 2% 1% 0% 2010

2011

2012

2013

2014

2015

2016

Year Source: Papua New Guinea (2016). 2015 Sector Performance Annual Review. (http://www.health.gov.pg/publications/2015_SPAR. pdf )

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Appendix 7. Reference list of 88 SDG and UHC indicators listed according to health system results chain (logic model) Inputs and Processes

Outputs

Outcomes

Impact

• Total net official development assistance to the medical research and basic health sectors • Health worker density and distribution • Proportion of children under 5 years of age whose births have been registered with a civil authority • Proportion of countries that have achieved 100% birth registration and 80% death registration • Total current expenditure on health as percentage of gross domestic product • Current expenditure on health by general government and compulsory schemes as percentage of total current expenditure on health • Proportion of health-care facilities with basic water supply • Proportion of health-care facilities with basic sanitation • Proportion of total government spending on essential services (education, health and social protection)

• International Health Regulations (2005) capacity and health emergency preparedness • Outpatient service utilization rate • Postoperative sepsis rate • Bed occupancy rate • 30-day hospital case fatality rate – acute myocardial infarction • Patient experience (to be defined) • Hospital average length of stay • Hospital readmission rate

• Proportion of births attended by skilled health personnel • Number of people requiring interventions against neglected tropical diseases • Coverage of treatment for substance use disorders • Harmful use of alcohol • Proportion of women reproductive age (aged 15–49 years) who have their need for family planning satisfied with modern methods • Adolescent birth rate • Coverage of essential health services • Proportion of population with large household expenditure on health as a share of total household expenditure or income • Age-standardized prevalence of current tobacco use among persons aged 15 years and older • Proportion of the target population covered by all vaccines included in their national programme • Proportion of population covered by social protection floors/systems • Prevalence of stunting among children under 5 years of age • Prevalence of malnutrition among children under 5 years of age, by type (wasting and overweight) • Proportion of population using safely managed drinkingwater services • Proportion of population using safely managed sanitation services, including a handwashing facility with soap and water • Annual mean levels of fine particulate matter (e.g. PM2.5 and PM10) in cities (population weighted) • Proportion of population with primary reliance on clean fuels and technology • Proportion of ever-partnered women and girls aged 15 years and older subjected to physical, sexual or psychological violence by a current or former intimate partner in previous 12 months • Seat belt-wearing rate • Motorcycle helmet-wearing rate • Immunization coverage for DTP3 (diphtheria-tetanuspertussis) • Immunization coverage rate for measles • Exclusive breastfeeding rate in infants 0–5 months of age • Incidence of low birth weight among newborns • Prevalence of anaemia in children aged 6–59 months • Anaemia prevalence in women of reproductive age (aged 15–49 years) • Age-standardized prevalence of raised blood glucose level among adults 18+ years • Age-standardized prevalence of overweight and obesity in persons aged 18+ years • Age-standardized prevalence of raised blood pressure among persons aged 18+ years • Age-standardized prevalence of insufficiently physically active persons aged 18+ years • Percentage of children under 5 years of age with suspected pneumonia who were taken to a health facility • Antiretroviral therapy (ART) coverage • Second-line treatment coverage among multidrugresistant tuberculosis (MDR-TB) cases • Cervical cancer screening (rate) • Coverage of services for severe mental health disorders • Rate of use of assistive devices among people with disabilities • Proportion of newborns receiving essential newborn care • Proportion of deliveries in health facilities • Age-standardized prevalence of current tobacco use among persons aged 13–15 years • Cataract surgical rate and coverage • Proportion of population utilizing the rehabilitation services they require • HIV testing coverage among people living with HIV • Viral suppression rate among people on ART

• Maternal mortality ratio • Under-5 mortality rate • Neonatal mortality rate • Number of new HIV infections per 1000 uninfected population • Malaria incidence per 1000 population • Hepatitis B incidence per 100 000 population • Suicide mortality rate • Death rate due to road traffic injuries • Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease • Tuberculosis incidence per 100 000 population • Mortality rate attributed to household and ambient air pollution • Mortality rate attributed to unsafe water, unsafe sanitation, and lack of hygiene • Mortality rate attributed to unintentional poisoning • Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basis • Number of deaths, missing persons and directly affected persons attributed to disasters per 100 000 population • Proportion of women and girls aged 15 years and older subjected to sexual violence by persons other than an intimate partner in the previous 12 months • Number of countries with laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education • Number of victims of intentional homicide per 100 000 population • Conflict-related deaths per 100 000 population • Proportion of population subjected to physical, psychological or sexual violence in the previous 12 months • Proportion of children aged 1–17 years who experienced any physical punishment and/or psychological aggression by caregivers in the past month • Number of victims of human trafficking per 100 000 population • Proportion of young women and men aged 18–29 years who experienced sexual violence by age 18 • Life expectancy at birth • Stillbirth rate (per 1000 total births) • Case rate of congenital syphilis (per 100 000 live births) • Mortality rate attributable to HBV and HCV infections • Dengue mortality rate

Source: WHO

Appendices

Appendix 8.

Regional relationship analysis

A. Reproductive, maternal, newborn and child health Inputs

Outputs 1

Proportion of deliveries in health facilities (%), 2006–2015

120

VUT

COK

FJI

TON

100

VNM KHM

FSM

SLB

CHN

MNG

NRU

MYS

PLW

BRN

KOR

JPN

SGP NZL

TUV

AUS

MHL

WSM KIR

PHL

PNG LAO

40 20

Asia Pacific

0 0

500

Proportion of births attended by skilled health personnel (%), 2005–2016

120

FSM KIR

100

1000

COK

VUT TON VNM KHM SLB WSM

2000 2500 3000 3500 Per capita total health expenditure (in PPP int. $), 2014

4000

4500

5000

NRU MNG CHN NIU

FJI

1500

TUV

MYS

PLW

BRN

KOR

MHL

JPN

SGP NZL

AUS

PHL

60 PNG

LAO

20 Asia Pacific

0 0

500

1000

1500 2000 2500 3000 3500 Per capita total health expenditure (in PPP int. $), 2014

4000

4500

5000

Source: WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Inputs

Outputs 1

Proportion of deliveries in health facilities (%) , 2006–2015

120 100 KHM

SLB

MHL

VUT

MNG

FJI

COK

NRU

WSM

TON TUV FSM

KOR JPN SGP CHN NZL AUS

BRN MYS

VNM

PLW

KIR

PHL

PNG LAO

40 20

Asia Pacific

0 20

40 50 60 70 80 UHC tracer index for service capacity and access (target=100)*, 2004–2015

100

Proportion of births attended by skilled health personnel (%), 2005–2016

120 COK

NRU

100

MHL

KHM

MNG FJI

VNM

TON

MYS

PLW BRN

TUV

WSM

VUT

SLB

FSM KIR

NIU

KOR JPN SGP CHN AUS NZL

PHL

PNG

LAO

Asia Pacific

0 20

100

UHC tracer index for service capacity and access (target=100)*, 2004–2015 AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. 1 Inputs: service capacity and access Outputs: institutional deliveries, skilled birth attendance * It measures general features of service capacity and access to care within a health system. Measures include hospital beds and health professionals per capita, and a measure of health security for responding to epidemics and other health threats.

Source: WHO

Appendices

Inputs

Outcomes 1

UHC Tracer index for reproductive, maternal newborn and child health (target=100)*, 2004–2015

100 BRN

90 FJI

VNM

MNG COK TUV

KHM

SLB KIR

LAO

TON PHL VUT PNG

NZL

KOR

CHN MYS MHL

FSM

AUS

SGP

JPN PLW

NIU

NRU

WSM

50 40 30

Asia Pacific

20 0

500

1000

1500

2000 2500 3000 3500 Per capita total health expenditure (in PPP int. $), 2014

4000

4500

UHC tracer index for reproductive, maternal newborn and child health (target=100)*, 2004–2015

100

5000

BRN

90 COK

KHM

SLB

70 60

PNG

LAO

NIU

MHL NRU

VUT

VNM

FJI

PHL

KIR

FSM WSM

TUV TON

MNG MYS

AUS NZL KOR SGP JPN CHN

PLW

50 40 30 20 10

Asia Pacific

0 20

40 50 60 70 80 UHC tracer index for service capacity and access (target=100)**, 2004–2015

100

AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. 1 Inputs: health expenditure, service capacity and access Outcomes: coverage of essential health services for reproductive, maternal, newborn and child health * It measures the extent to which those in need for family planning, pregnancy and delivery care, child immunization and treatment receive the care they need. ** It measures general features of service capacity and access to care within a health system. Measures include hospital beds and health professionals per capita, and a measure of health security for responding to epidemics and other health threats. Source: WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Inputs

Impacts 1

Neonatal mortality rate (per 1000 live births), 2016

Asia Pacific

LAO

KIR

NRU

PNG

KHM

PHL SLB

FSM MHL VUT

TUV

VNM WSM

5 0 20

MNG FJI PLW TON CHN MYS BRN COK NZL KOR AUS SGP JPN

100

Proportion of deliveries in health facilities (%), 2006–2015 70

Asia Pacific

LAO

Under-5 mortality rate (per 1000 live births), 2016

KIR

PNG

MHL

PHL

NRU

FSM VUT

KHM

TUV

FJI

SLB

VNM WSM

10 0 20

MNG TON

PLW CHN BRN MYS COK NZL KOR JPN AUS SGP

100

Proportion of deliveries in health facilities (%), 2006–2015 250

Asia Pacific

PNG

Maternal mortality ratio (per 100 000 live births), 2015

200 LAO KHM

150 100

TON

SLB

PHL

FSM

KIR WSM

VUT

MNG MYS CHN FJI SGP BRN KOR NZL JPN AUS

0 20

50 60 70 Proportion of deliveries in health facilities (%), 2006–2015

VNM

100

Appendices

Outputs

Impacts 1

40 Asia Pacific

Neonatal mortality rate (per 1000 live births), 2016

35 30

LAO

PNG

KIR

20 KHM

PHL

SLB

NIU MNG PLW CHN COK MYS BRN NZL KOR SGP AUS JPN FJI TON

WSM

0 20

FSM

VNM

VUT

NRU

MHL TUV

100

Proportion of births attended by skilled health personnel (%), 2005–2016 70

LAO

Under-5 mortality rate (per 1000 live births), 2016

Asia Pacific

PNG

KIR

50 40

MHL

NRU

KHM

PHL

SLB VUT

FSM TUV

WSM

VNM FJI

NIU MNG PLW CHN BRN MYS COK NZL KOR SGP AUS JPN

TON

10 0 20

100

Proportion of births attended by skilled health personnel (%), 2005–2016 250 PNG

Maternal mortality ratio (per 100 000 live births), 2015

200 LAO KHM

150 PHL

TON

SLB

FSM

100

VUT WSM

KIR VNM

MNG FJI

NZL AUS

0 0

40 60 80 Proportion of births attended by skilled health personnel (%), 2005–2016

MYS CHN BRN KOR SGP JPN

100

Asia Pacific

120

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

Outcomes

Impacts 1

Prevalence of stunting in children under 5 (%), 2005–2016

60 PNG

LAO

40 SLB

KHM

PHL

VUT

VNM BRN

NRU

MYS

MNG

TON

TUV

CHN JPN KOR

0 40

Asia Pacific

AUS

60 70 80 90 UHC tracer index for reproductive, maternal, newborn and child health (target=100)*, 2004–2015

100

Neonatal mortality rate (per 1000 live births), 2016

35 30

LAO

PNG KIR

NRU

FSM

TUV KHM

PHL

VUT

MHL

NIU SLB

WSM

MNG FJI

PLW

TON

VNM

MYS

JPN

BRN

NZL

Under-5 mortality rate (per 1000 live births), 2016

CHN

COK SGP

KOR

AUS

Asia Pacific

60 70 80 90 UHC tracer index for reproductive, maternal, newborn and child health (target=100)*, 2004–2015

100

LAO

60 PNG

50 40

KIR

NRU

MHL

FSM

VUT

SLB PHL

WSM

FJI

NIU TON

KHM TUV

PLW MYS

VNM MNG CHN JPN

0 40

BRN NZL

COK SGP

KOR

60 70 80 90 UHC tracer index for reproductive, maternal, newborn and child health (target=100)*, 2004–2015

AUS

Asia Pacific

100

AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. 1 Outcomes: coverage of essential health services for reproductive, maternal, newborn and child health Impacts: child mortality, children stunting * It measures the extent to which those in need for family planning, pregnancy and delivery care, child immunization and treatment receive the care they need. Source: WHO

Appendices

Outcomes

Impacts 1

250

Maternal mortality ratio (per 100 000 live births), 2015

PNG

200

LAO KHM

150 PHL TON

SLB FSM

100

VUT

KIR VNM

WSM

MNG

MYS

FJI

0 40

CHN JPN

SGP

BRN NZL KOR AUS

60 70 80 90 UHC tracer index for reproductive, maternal, newborn and child health (target=100)*, 2004–2015

Asia Pacific 100

Adolescent birth rate (per 1000 women aged 15–19 years), 2005–2014

120 NRU

100

LAO MHL VUT

SLB

PHL

KHM

COK

KIR

WSM

VNM FJI MNG

TUV

FSM

PLW

TON

NZL

NIU MYS

CHN JPN

0 40

BRN AUS

SGP

KOR

Asia Pacific

50 60 70 80 90 UHC tracer index for reproductive, maternal, newborn and child health (target=100)*, 2004–2015

100

Life expectancy at birth (years) both sexes, 2006 –2015

100 90 JPN

COK WSM VUT

TON

MHL

PHL

LAO

FSM

SLB

KIR

PNG

NIU

SGP KOR NZL

VNM

MYS

CHN

FJI

TUV KHM

AUS BRN

MNG

NRU

Asia Pacific

40 40

100

UHC tracer index for reproductive, maternal, newborn and child health (target=100)*, 2004–2015 AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. 1 Outcomes: coverage of essential health services for reproductive, maternal, newborn and child health Impacts: life expectancy, adolescent birth, maternal mortality * It measures the extent to which those in need for family planning, pregnancy and delivery care, child immunization and treatment receive the care they need. Source: WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

B. Infectious diseases Inputs

Outcomes 1

90 KOR

UHC Tracer index for infectious diseases (target=100)*, 2002 –2015

80 NIU

TON

WSM NRU CHN VNM MHL KHM FJI VUT TUV PHL FSM KIR SLB LAO MNG PNG

60 50 40

AUS

NZL

BRN

SGP

JPN

PLW

MYS

30 20

COK

Asia Pacific

10 0 0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Per capita total health expenditure (in PPP int. $), 2014 90 UHC tracer index for infectious diseases (target=100)*, 2002 –2015

80 WSM

NRU

KHM

MHL

FJI VUT

VNM

PHL

50 LAO

BRN

TON

NIU

KIR

SLB

NZL

FSM

TUV

MYS

PLW

KOR AUS SGP JPN CHN

MNG

PNG

30 20

COK

Asia Pacific

10 0 20

40 50 60 70 80 UHC tracer index for service capacity and access (target=100)**, 2004–2015

100

AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. 1 Inputs: health expenditure, service capacity and access Outcomes: coverage of essential health services for infectious diseases * It measures (i) the extent to which those in need for TB and HIV treatment and malaria prevention receive the care and services they need, and (ii) access to improved sanitation. ** It measures general features of service capacity and access to care within a health system. Measures include hospital beds and health professionals per capita, and a measure of health security for responding to epidemics and other health threats. Source: WHO

Appendices

Outcomes

Impacts 1

TB incidence (per 100 000 population), 2016

600

PHL KIR

500 PNG

MHL

400

KHM

300 200

TUV

LAO

FSM

MNG SLB

100

MYS

COK

VUT

0 0

VNM

PLW

NRU CHN

FJI

WSM

KOR SGP JPN

NIU TON

Asia Pacific

BRN NZL

AUS

100

UHC tracer index for infectious diseases (target=100)*, 2002–2015

Life expectancy at birth (years) both sexes, 2006–2015

100 90 JPN

COK

MYS

PNG

VUT

SLB

MNG

LAO

TUV KIR

FSM PHL

KHM

VNM CHN TON MHL WSM FJI

AUS

SGP BRN

KOR

NZL

NIU

NRU

Asia Pacific

40 0

30 40 50 60 70 UHC tracer index for infectious diseases (target=100)*, 2002–2015

100

AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. 1 Outcomes: coverage of essential health services for infectious diseases Impacts: life expectancy, TB incidence * It measures (i) the extent to which those in need for TB and HIV treatment and malaria prevention receive the care and services they need, and (ii) access to improved sanitation. Source: WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS

B. Noncommunicable diseases Inputs

Outcomes 1

UHC tracer index for noncommunicable diseases (target=100)*, 2008–2015

80 BRN

KHM

NIU

VUT

VNM

60 LAO

MNG

PLW

CHN

FSM COK

PNG

FJI

SLB

MYS

TUV

PHL

SGP NZL AUS KOR JPN

TON

WSM NRU

30 20

MHL

KIR

Asia Pacific

10 0 20

40 50 60 70 80 UHC tracer index for service capacity and access (target=100)**, 2004–2015

100

UHC Tracer index for noncommunicable diseases (target=100)***, 2008–2015

80 BRN

KHM PHL VUT VNM

FJI LAO SLB FSM TON

50 40

PNG

30 20

CHN

SGP

KOR

NIU

JPN

MYS

TUV MNG

AUS

NZL

PLW

COK NRU WSM

MHL

KIR

Asia Pacific

0 0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Per capita total health expenditure (in PPP int. $), 2014 AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. 1 Inputs: health expenditure, service capacity and access Outcomes: coverage of essential health services for noncommunicable diseases * It measures the current status of NCD risk factors in the population, including blood pressure, glucose level and tobacco consumption, as a proxy indicator of success of both prevention efforts and screening and treatment programmes. ** It measures general features of service capacity and access to care within a health system. Measures include hospital beds and health professionals per capita, and a measure of health security for responding to epidemics and other health threats. Source: WHO

Appendices

Outcomes

Impacts 1

Probability of dying from any of CVD, cancer, diabetes, CRD between age 30 and exact age 70 (%), 2015

PNG

35 30

FJI

MNG

KIR

SLB

WSM

TON

PHL

LAO

FSM

KHM

VUT

CHN

VNM

MYS

15 10

BRN JPN

NZL

SGP

AUS KOR

Asia Pacific

0 0

30 40 50 60 70 UHC tracer index for noncommunicable diseases (target=100)*, 2008–2015

100

Life expectancy at birth (years) both sexes, 2006–2015

100 90 JPN KOR

80 MHL

COK

WSM

MYS CHN VNM

TON FJI

SLB

70 KIR

TUV LAO

PHL

SGP NZL BRN

NIU

VUT

FSM MNG

PNG

AUS

KHM

NRU

Asia Pacific

40 0

20 30 40 50 60 UHC tracer index for noncommunicable diseases (target=100)*, 2008–2015

AUS = Australia, BRN = Brunei Darussalam, KHM = Cambodia, CHN = China, COK = Cook Islands, FJI = Fiji, JPN = Japan, KIR = Kiribati, LAO = Lao People‘s Democratic Republic, MYS = Malaysia, MHL = Marshall Islands, FSM = Micronesia (Federated States of ), MNG = Mongolia, NRU = Nauru, NZL = New Zealand, NIU = Niue, PLW = Palau, PNG = Papua New Guinea, PHL = Philippines, KOR = Republic of Korea, WSM = Samoa, SGP = Singapore, SLB = Solomon Islands, TON = Tonga, TUV = Tuvalu, VUT = Vanuatu, VNM = Viet Nam. 1 Outcomes: coverage of essential health services for noncommunicable diseases Impacts: life expectancy, premature mortality * It measures the current status of NCD risk factors in the population, including blood pressure, glucose level and tobacco consumption, as a proxy indicator of success of both prevention efforts and screening and treatment programmes. Source: WHO

MONITORING UNIVERSAL HEALTH COVERAGE AND HEALTH IN THE SUSTAINABLE DEVELOPMENT GOALS