Health Service Provision in Odisha: Assessing Facility Capacity, Costs of Care, and Patient Perspect by Institute for Health Metrics and Evaluation

H E A LT H SE RVI CE P ROVI SI O N IN ODIS HA

Assessing Facility Capacity, Costs of Care, and Patient Perspectives

INSTITUTE FOR HEALTH METRICS AND EVALUATION UNIVERSITY OF WASHINGTON

A B C E

CCESS, OTTLENECKS, OSTS, AND QUITY

PUBLIC HEALTH FOUNDATION OF INDIA

HE ALTH SERVICE PROVISION IN O D I SHA

Assessing Facility Capacity, Costs of Care, and Patient Perspectives

A B C E

CCESS, OTTLENECKS, OSTS, AND QUITY

Table of Contents 5 Acronyms

Terms and definitions

Introduction

Main findings Health facility profiles

Executive summary

ABCE project design

Facility capacity and characteristics Patient perspectives Efficiency and costs

48 Conclusions and policy implications 52 Annex

INSTITUTE FOR HEALTH METRICS AND EVALUATION UNIVERSITY OF WASHINGTON

PUBLIC HEALTH FOUNDATION OF INDIA

About Public Health Foundation of India

The Public Health Foundation of India (PHFI) is a public private initiative to build institutional capacity in India for

strengthening training, research, and policy development for public health in India. PHFI adopts a broad, integrative

approach to public health, tailoring its endeavors to Indian conditions and bearing relevance to countries facing similar

challenges and concerns. PHFI engages with various dimensions of public health that encompass promotive, preventive,

Collaborations

This project has immensely benefitted from the key inputs and support from Dr. Shridhar Kadam and

Dr. N. Srinivas from the Indian Institute of Public Health, Bhubaneshwar. Approvals and valuable support for this project

were received from the Odisha state government and district officials, which are gratefully acknowledged.

and therapeutic services, many of which are often lost sight of in policy planning as well as in popular understanding.

About IHME

About this report

The Institute for Health Metrics and Evaluation (IHME) is an independent global health research center at the University

of Washington that provides rigorous and comparable measurement of the worldâ&#x20AC;&#x2122;s most important health problems and

evaluates the strategies used to address them. IHME makes this information freely available so that policymakers have

the evidence they need to make informed decisions about how to allocate resources to best improve population health.

Assessing Facility Capacity, Costs of Care, and Patient Perspectives: Odisha provides a comprehensive assessment

of health facility performance in Odisha, including facility capacity for service delivery, efficiency of service delivery, and

patient perspectives on the service they received. Findings presented in this report were produced through the ABCE

project in Odisha, which aims to collate and generate the evidence base for improving the cost-effectiveness and equity

of health systems. The ABCE project is funded through the Disease Control Priorities Network (DCPN), which is a multi-

year grant from the Bill & Melinda Gates Foundation to comprehensively estimate the costs and cost-effectiveness of a range of health interventions and delivery platforms.

Acknowledgments

Acronyms

We especially thank all of the health facilities and their staff in Odisha, who generously gave of their time and facili-

ABCE

who participated in this work, as they too were giving of their time and were willing to share their experiences with the

ANM

tated the sharing of facility data that made this study possible. We are also most appreciative of patients of the facilities

field research team.

At PHFI, we wish to thank Rakhi Dandona and Lalit Dandona at PHFI who served as the principal investigators for ABCE

project in India. We also wish to thank Anil Kumar for guidance with data collection, management, and analysis. The quan-

tity and quality of the data collected for the ABCE project in India is a direct reflection of the dedication of the field team.

We thank the India field coordination team, which included, Md. Akbar, G. Mushtaq Ahmed, and S.P. Ramgopal. We also recognize and thank Venkata Srinivas, Simi Chacko, and Ranjana Kesarwani for data management and coordination with

ANC

Access, Bottlenecks, Costs, and Equity Antenatal care

Auxiliary nurse midwife

CHC

Community health centre

DCPN

Disease Control Priorities Network

DEA DH

DOTS

Confidence interval

Data envelopment analysis District Hospital

Directly observed therapy, short-course

field teams.

IHME

Institute for Health Metrics and Evaluation

also recognize and thank staff at IHME: Roy Burstein, Alan Chen, Emily Dansereau, Katya Shackelford, Alexander Woldeab,

NCD

Non-communicable disease

At IHME, we wish to thank Christopher Murray and Emmanuela Gakidou, who served as the principal investigators. We

IPHS

Alexandra Wollum, and Nick Zyznieuski for managing survey programming, survey updates, data transfer, and ongoing

Kumar, Herbie Duber, Kelsey Bannon, Aubrey Levine, and Nancy Fullman. Finally, we thank those at IHME who supported

PHC

verification at IHME during fieldwork. We are grateful to others who contributed to the project: Michael Hanlon, Santosh publication management, editing, writing, and design.

This report was drafted by Marielle Gagnier, Lauren Hashiguchi, and Nikhila Kalra of IHME and Rakhi Dandona of PHFI. Funding for this research comes from the Bill & Melinda Gates Foundation under the Disease Control Priorities

Network (DCPN).

Odisha

Odds ratio

Primary health centre

PHFI

Public Health Foundation of India

SFA

Stochastic frontier analysis

SDH SHC STI

WHO

Indian Public Health Standards

Sub-district hospital Sub health centre

Sexually transmitted infection

World Health Organization

ABCE IN ODISHA

TERMS AND DEFINITIONS

Terms and definitions

Definitions presented for key technical terms used in the report.

Table 1 defines the types of health facilities in Odisha; this report will refer to facilities according to these definitions.

Constraint

Table 1 Health facility types in Odisha1

a factor that facilitates or hinders the provision of or access to health services. Constraints exist as both “supply-side,” or

the capacity of a health facility to provide services, and “demand-side,” or patient-based factors that affect health-seeking behaviors (e.g., distance to the nearest health facility, perceived quality of care received by providers). Data Envelopment Analysis (DEA)

Health facility types in Odisha

an econometric analytic approach used to estimate the efficiency levels of health facilities.

District hospital (DH)

Efficiency

secondary health care services to the district’s population. DHs are sized according to the size of the district

a measure that reflects the degree to which health facilities are maximizing the use of the resources available in producing services.

These facilities are the secondary referral level for a given district. Their objective is to provide comprehensive population, so the number of beds varies from 75 to 500. Sub-district hospital (SDH)

Facility sampling frame

These facilities are sub-district/sub-divisional hospitals below the district and above the block-level hospitals

the list of health facilities from which the ABCE sample was drawn. This list was based on a 2012–2013 facility inventory

(CHC). As First Referral Units, they provide emergency obstetrics care and neonatal care. These facilities serve

published by the Odisha state government.

populations of 500,000 to 600,000 people, and have a bed count varying between 31 and 100 beds.

Inpatient visit

Community health centre (CHC)

facility, but the metric of a visit does not reflect the duration of stay.

specialist health care to the rural population. They act as the block-level health administrative unit and as the gate-

a visit in which a patient has been admitted to a facility. An inpatient visit generally involves at least one night spent at the

Inputs

tangible items that are needed to provide health services, including facility infrastructure and utilities, medical supplies

These facilities constitute the secondary level of health care, and were designed to provide referral as well as keeper for referrals to higher level facilities. Bed strength ranges up to 30 beds. Primary health centre (PHC)

and equipment, and personnel.

These facilities provide rural health services. PHCs serve as referral units for primary health care from Sub-

Outpatient visit

may be upgraded to provide 24-hour emergency hospital care for a number of conditions. A typical PHC covers a

a visit at which a patient receives care at a facility without being admitted.

population of 20,000 to 30,000 people and hosts about six beds.

Outputs

Sub health centre (SHC)

laboratory and diagnostic tests, and medications.

immunizations, and refer inpatient and deliveries to higher-level facilities.

Centres and refer cases to CHC and higher-order public hospitals. Depending on the needs of the region, PHCs

volumes of services provided, patients seen, and procedures conducted, including outpatient and inpatient care,

Along with PHCs, these facilities provide rural health care. SHCs typically provide outpatient care, which includes

Platform

a channel or mechanism by which health services are delivered. Stochastic Frontier Analysis (SFA)

1 Directorate General of Health Services, Ministry of Health & Family Welfare, and Government of India. Indian Public Health Standards (IPHS) Guidelines. New Delhi, India: Government of India, 2012.

an econometric analytic approach used to estimate the efficiency levels of health facilities.

EXECUTIVE SUMMARY

Executive summary

facilities reported providing a given service but lacked

reported fewer or the same number of nurses as doc-

full capacity to properly deliver it, for instance lacking

tors, and tended to employ more paramedical and

functional equipment or medications. For example,

non-medical staff than nurses or doctors.

while all sub-district hospitals and community health

• Staff numbers were concentrated at district hospitals

centres reported providing routine delivery care, none

with an average of 118 personnel. Sub-district hospitals

were fully equipped to do so. Additionally, only 11%

had the second highest number of personnel, but this

of district hospitals were fully equipped for this pur-

ith the aim of establishing universal health

and comparison of facility-level outputs, efficiency, capac-

coverage, India’s national and state gov-

ity and patient experiences. It is with this information that

ernments have invested significantly in

we strive to provide the most relevant and actionable in-

expanding and strengthening the public

formation for health system programming and resource

health care sector. This has included a particular com-

allocation in Odisha.

mitment to extending its reach to rural populations and reducing disparities in access to care for marginalized

Facility capacity for service provision

sary for the country to critically consider the full range of

While most facilities report providing key health services, significant gaps in capacity were identified between reported and functional capacity for care.

groups. However, in order to realize this goal, it is neces-

factors that contribute to or hinder progress toward it.

Since its inception in 2011, the Access, Bottlenecks,

Costs, and Equity (ABCE) project has sought to compre-

• Health facilities generally reported a high availability

hensively identify what and how components of health

service provision – access to services, bottlenecks in de-

of a subset of key services. Services such as antenatal

health system performance in several countries. Through

were widely available across facilities.

care, routine deliveries, immunization, and lab services

livery, costs of care, and equity in care received – affect the ABCE project, multiple sources of data, including

• Few facilities reported available services for non-com-

facility surveys and patient exit interviews, are linked to-

municable diseases (NCDs). Low numbers of district

gether to provide a nuanced picture of how facility-based

hospitals reported providing psychiatry (33%), cardi-

factors (supply-side) and patient perspectives (de-

ology (11%), or chemotherapy (11%), and availability

mand-side) influence optimal service delivery.

decreased at lower levels of the health system.

Led by the Public Health Foundation of In -

dia (PHFI) and the Institute for Health Metrics and

• Basic medical equipment such as scales, stethoscopes,

positioned to inform the evidence base for understand-

available at all health facility levels, but laboratory

of care. Derived from a state-representative sample of

analyzers were less readily available. For example, only

pose. This discordance has substantial programmatic

identify areas of success and targets for improving health

system, with particular implications for diagnosing and

treating NCDs.

service provision.

The main topical areas covered in this report move

• Gaps also emerged with regard to imaging equipment,

from an assessment of facility-reported capacity for care,

particularly at lower level health facilities. CT scans

to quantifying the services actually provided by facilities

were available in just 11% of district hospitals and no

and the efficiency with which they operate; tracking facil-

sub-district hospitals.

ity expenditures and the costs associated with different

• A service capacity gap emerged for the majority of

types of service provision; and comparing patient per-

health facilities across several types of services. Many

spectives of the care they received across different types of facility. Further, we provide an in-depth examination

There have been slight increases in outpatient and inpatient visits over time.

• Functional electricity was available at all hospital and

• Between 2009 and 2013, most facility types experi-

(97%) of primary health centres. 77% of sub health cen-

hospitals had nearly double the outpatient visits of

on figures from past government surveys.

tres had ten times the visits of sub health centres.

community health centres, and the large majority

enced slight increases in outpatient visits. Sub-district

tres had electricity, showing substantial improvement

community health centres, while primary health cen-

Outpatient visits accounted for the large majority

• Access to piped water was generally high at hospi-

of patients seen per staff member per day across all

tals, though much lower at primary and sub health

facility types.

centres (40% and 14% respectively). Similarly, there

was universal availability of flush toilets at hospitals,

• Inpatient visits also increased for all facility types

while they were available at less than half of primary

between 2009 and 2013.

health centres and less than a quarter of sub health

• The number of immunization doses administered

centres. These figures reflects investments into im-

between 2009 and 2013 remained stable for all

proving physical infrastructure at health facilities,

• No primary health centre had access to a computer,

limited capacity for testing throughout the health

Facility production of health services

Physical infrastructure of health facilities has improved, but gaps in transport and communication remain.

equipment such as glucometers and blood chemistry

partners alike with actionable information that can help

human resources for health.

range of services.

ing the country’s drivers of health care access and costs

to 20% at the primary health centre level. This shows

lation size, this also demonstrates relative shortages in

ities have all the supplies they need to provide a full

though discrepancies remain between high- and low-

governments, international agencies, and development

this variation is a result of service provision and popu-

highlighting continued challenges in ensuring facil-

and blood pressure apparatus were generally widely

108 facilities, the findings presented in this report provide

tres averaged between two and 26 staff. While some of

and policy implications for the health system in Odisha,

Evaluation (IHME), the ABCE project in Odisha is uniquely

56% of district hospitals had glucometers, dropping

was half of that at district hospitals, while health cen-

facility types.

level facilities.

Facilities showed capacity for larger patient volumes given observed resources.

and only 14% had access to a phone. Only 3% of pri-

• In generating estimates of facility-based efficiency, or

mary health centres had any access to a vehicle at all

the alignment of facility resources with the number of

and just 6% community health centres had access to

patients seen or services produced, we found a wide

an emergency vehicle. Given that these types of facil-

range of efficiency levels within and across facility

ities often play key referral functions, these findings

types. The average efficiency score of district hospi-

have serious implications for coordinating the care

tals ranged from 47% to 88%, with a platform average

and transportation of patients.

of 74%. Sub-district hospitals were between 49% and

80% efficient. Community health centres were be-

Nurses and doctors outnumbered paramedical staff at hospitals, while at health centres paramedical staff and auxiliary nurse midwives outnumbered both doctors and nurses.

tween 34% and 80% efficient; two facilities were 75% or more efficient. The range of efficiency scores was

widest for primary health centres, from 17% to 76%, with 21 facilities at less than 50% efficient.

• In general, hospitals reported that they staffed more

• If they operated at optimal efficiency, district hospitals

nurses than doctors. Most primary health centres

Patients gave higher ratings of health care providers than facility characteristics, particularly cleanliness

could provide 58,812 additional outpatient visits with

the same inputs (including physical capital and personnel), while primary health centres could produce

10,335 additional outpatient visits.

Introduction

• At hospitals, patients receiving care from doctors reported relatively higher levels of satisfaction than

• These efficiency scores indicate that there is consid-

those treated by nurses. The opposite was true of com-

erable room for health facilities to expand service

munity and primary health centres. Satisfaction with

production given their resources existing resources.

doctors was highest at district hospitals, while satis-

Future work on pin-pointing specific factors that

faction with nurses was highest (100% satisfaction) at

heighten or hinder facility efficiency, and how effi-

primary health centres.

ciency is related to the quality of service provision,

should be considered.

• Facility cleanliness received generally low ratings from

patients, with cleanliness at hospitals receiving partic-

Costs of care

ularly low marks. Similar proportions of patients were

Trends in average facility spending between 2009 and 2013 varied between facility types, though all platforms recorded higher spending in 2013 than 2009.

across facility type (63-72%).

satisfied with the privacy at the facility they visited

• Most patients received all drugs that they were prescribed during their visits. Proportions of patients

receiving all prescribed drugs ranged from 55%

• Spending on personnel accounted for the vast major-

of patients at sub-district hospitals to 75% at sub

ity of annual spending across facility types. Community

health centres.

health centres spent a slightly lower proportion of

he performance of a country’s health sys-

critical questions facing policymakers and health stake-

tem ultimately shapes the health outcomes

holders in each country or state for public sector health care

experienced by its population, influencing

service delivery:

the ease or difficulty with which individuals

• What health services are provided, and where

can seek care and facilities can address their needs. At a

are they available?

time when international aid is plateauing1 and the gov-

• What are the bottlenecks in provision of

ernment of India has prioritized expanding many health

these services?

programs,2,3 identifying health system efficiencies and

• How much does it cost to produce health services?

promoting the delivery of cost-effective interventions has

become increasingly important.

• How efficient is provision of these health services?

Assessing health system performance is crucial to opti-

Findings from each country’s ABCE work will pro-

mal policymaking and resource allocation; however, due

vide actionable data to inform their own policymaking

to the multidimensionality of health system functions,4

processes and needs. Further, ongoing cross-country

comprehensive and detailed assessment seldom occurs.

analyses will likely yield more global insights into health

Rigorously measuring what factors are contributing to

their total expenditures on personnel than other plat-

With its multidimensional assessment of health service

forms, while the proportion of expenditure on medical

provision, findings from the ABCE project in Odisha pro-

supplies was highest at primary health centres.

equity in service provision throughout a country provides

the health system. Odisha’s health provision landscape

population health outcomes.

evolve over time. This highlights the need for continuous

project was launched globally in 2011 to address these

critical for identifying areas of successful implementation

pronged, multi-partner ABCE project has taken place in

was markedly heterogeneous, and will likely continue to

Travel and wait times were generally shorter for patients visiting lower-level facilities than higher-level ones.

and timely assessment of health service delivery, which is

• Nearly 80% of patients at primary health centres re-

and quickly responding to service disparities or faltering

ported travelling less than 30 minutes to receive care, compared to 58% of patients at district hospitals. This ceive specialist treatment provided at hospitals. It is

longer for community health centres than sub-district

informed decisions for achieving optimal health system

• Nearly all patients seeking care at primary health

and capacity for health service provision, aiming to de-

velop data-driven and flexible policy tools that can be

adapted to the particular demands of governments, de-

velopment partners, and international agencies.

seven other countries (Bangladesh, Colombia, Ghana,

ity capacity, efficiencies, and costs of care. With regularly

program managers can yield the evidence base to make

hospitals.

contributes to the global evidence base on the costs of

gaps in information. In addition to India, the multi-

and Telangana, Gujarat, Madhya Pradesh, Odisha, and

health facilities, recipients of care, policymakers, and

private), and disease burden profiles. The ABCE project

The Access, Bottlenecks, Costs, and Equity (ABCE)

performance. Expanded analyses would also allow for

collected and analyzed data, capturing information from

worth nothing, though, that travel times tended to be

ching ABCE project as they capture the diversity of health

system structures, composition of providers (public and

crucial information for improving service delivery and

Kenya, Lebanon, Uganda, and Zambia). In India, the ABCE

an even clearer picture of the trends and drivers of facil-

reflects the greater distances people travel to re-

countries have been purposively selected for the overar-

vices, bottlenecks in service delivery, costs of care, and

vide an in-depth examination of health facility capacity, costs of care, and how patients view their interactions with

Patient perspectives

service delivery and costs of health care. These eight

or hindering health system performance — access to ser-

The Public Health Foundation of India (PHFI) and the

Institute for Health Metrics and Evaluation (IHME) com-

project was undertaken in six states – Andhra Pradesh

pose the core team for the ABCE project in India, and they

received vital support and inputs from the state Ministry

Tamil Nadu.

of Health and Family Welfare for data collection, analysis,

The ABCE project, with the goal of rigorously assess-

and interpretation. The core team harnessed information

ing the drivers of health service delivery across a range

from distinct but linkable sources of data, drawing from

of settings and health systems, strives to answer these

a state representative sample of health facilities to cre-

performance and the equitable provision of cost-effective

centres (90%) received care within 30 minutes. Wait

interventions throughout Odisha.

times were longer at district hospitals (37% of patients waited more than 30 minutes to receive care)

and sub-district hospitals (33%). Fewer than 2% of all patients waited more than hour hour to receive care

across all facilities.

ate a large and fine-grained database of facility attributes, expenditure, and capacity, patient characteristics and

1 Institute for Health Metrics and Evaluation (IHME). Financing Global Health 2015: Development assistance steady on the path to new Global Goals. Seattle, WA: IHME, 2016. 2 Planning Commission Government of India. Eleventh Five Year Plan (2007-12). New Delhi, India: Government of India, 2007. 3 Planning Commission Government of India. Twelfth Five Year Plan (2012-17). New Delhi, India: Government of India, 2012. 4 Murray CJL, Frenk J. A Framework for Assessing the Performance of Health Systems. Bulletin of the World Health Organization. 2000; 78 (6): 717-731.

outcomes. By capturing the interactions between facility characteristics and patient perceptions of care, we have

been able to piece together what factors drive or hinder optimal and equitable service provision in rigorous, data-driven ways.

ABCE IN ODISHA

We focus on the facility because health facilities are the

consider the factors that affect patient perceptions of and

the health system or receive care. Understanding the ca-

range of factors that influence health service delivery, we

main points through which most individuals interact with

experiences with a state’s health system. By considering a

pacities and efficiencies within and across different types

ABCE project design

have constructed a nuanced understanding of what helps

of public sector health facilities unveils the differences in

and hinders the receipt of health services through facili-

health system performance at the level most critical to

ties in the state of Odisha.

immensely valuable to governments and development

haustive; rather, they align with identified priorities for

patients – the facility level. We believe this information is

The results discussed in this report are far from ex-

partners, particularly for decisions on budget alloca-

health service provision and aim to answer questions

tions. By having data on what factors are related to high

about the costs of health care delivery in the respective

icymakers and development partners can then support

tion of health facility capacity across different platforms,

facility performance and improved health outcomes, pol-

state in India. This report provides an in-depth examina-

evidence-driven proposals and fund the replication of

specifically covering topics on human resource capacity,

these strategies at facilities throughout India.

facility-based infrastructure and equipment, health ser-

The ABCE project in India has sought to generate the

vice availability, patient volume, facility-based efficiencies,

equity of health service provision. In this report, we ex-

factors of health service delivery as captured by patient

efficiencies and costs associated with service provision for

Table 2 defines the cornerstone concepts of the ABCE

evidence base for improving the cost-effectiveness and

costs associated with service provision, and demand-side

amine facility capacity across platforms, as well as the

exit interviews.

each type of facility. Based on patient exit interviews, we

project: Access, Bottlenecks, Costs, and Equity.

ABCE Facility Survey

or the ABCE project in India, we conducted

primary data collection through a two-

Through the ABCE Facility Survey, direct data collec-

pronged approach:

tion was conducted from a state representative sample of

health service platforms and captured information on the

1. A comprehensive facility survey administered to a

following indicators for the five fiscal years (running from

representative sample of health facilities in select

April to March of the following year) prior to the survey:

states in India (the ABCE Facility Survey)

• Inputs: the availability of tangible items that are

2. Interviews with patients as they exited the

needed to provide health services, including in-

sampled facilities

frastructure and utilities, medical supplies and

Here, we provide an overview of the ABCE survey de-

equipment, pharmaceuticals, personnel, and

sign and primary data collection mechanisms. All

non-medical services.

ABCE survey instruments are available on line at

• Finances: expenses incurred, including spending on

http://www.healthdata.org/dcpn/india.

infrastructure and administration, medical supplies

and equipment, pharmaceuticals including vaccines,

Table 2 Access, Bottlenecks, Costs, and Equity

and personnel. Facility funding from different sources (e.g., central and state governments) and revenue

Access, Bottlenecks, Costs, and Equity

from service provision were also captured.

• Outputs: volume of services and procedures pro-

Access

duced, including outpatient and inpatient care,

Health services cannot benefit populations if they cannot be accessed; thus, measuring which elements are

emergency care, and laboratory and diagnostic tests.

driving improved access to – or hindering contact with – health facilities is critical. Travel time to facilities, user fees, and cultural preferences are examples of factors that can affect access to health systems.

• Supply-side constraints and bottlenecks: factors

that affected the ease or difficulty with which patients

Bottlenecks

received services they sought, including bed avail-

Mere access to health facilities and the services they provide is not sufficient for the delivery of care to

ability, pharmaceutical availability and stockouts,

outs, that prevent the receipt of proper care upon arriving at a facility.

service availability.

populations. People who seek health services may experience supply-side limitations, such as medicine stock-

cold-chain capacity, personnel availability, and

Costs

Table 3 provides more information on the specific

Health service costs can translate into very different financial burdens for consumers and providers of such

indicators included in the ABCE Facility Survey.

care. Thus, the ABCE project measures these costs at several levels, quantifying what facilities spend to provide services. Equity

Various factors influence how populations interact with a health system. The nature of these interactions either

facilitate or obstruct access to health services. In addition to knowing the cost of scaling up a given set of ser-

vices, it is necessary to understand costs of scale-up for specific populations and across population-related factors (e.g., distance to health facilities). The ABCE project aims to pinpoint which factors affect the access to and use of health services and to quantify how these factors manifest.

ABCE IN ODISHA

Table 3 Modules included in the ABCE Facility Survey in India SURVEY MODULE Module 1: Facility finances and inputs

SURVEY CATEGORY

KEY INDICATORS AND VARIABLES

Inputs

Input funding sources, managing authority, and maintenance information Availability and functionality of medical and non-medical equipment

Finances

Salary/wages, benefits, and allowances Total expenses for infrastructure and utilities; medical supplies and equipment; pharmaceuticals; administration and training; non-medical services, personnel (salaries and wages, benefits, allowances) Performance and performance-based financing questions

Revenue

User fees; total revenue and source

Personnel characteristics

Total personnel by cadre Funding sources of personnel Health services provided and their staffing; administrative and support services and their staffing

Module 2: Facility management and direct observation

Facility management and infrastructure characteristics

Characteristics of patient rooms; electricity, water, and sanitation Facility meeting characteristics Guideline observation

Direct observation

Latitude, longitude, and elevation of facility. Facility hours, characteristics, and location; waiting and examination room characteristics

Facility capacity

Lab-based tests available

Medical consumables and equipment

Lab-based medical consumables and supplies available

Module 4: Pharmaceuticals

Facility capacity

Drug availability and stockout information

Module 5: General medical consumables, equipment, and capacity

Medical consumables and equipment

Availability and functionality of medical furniture, equipment, and supplies

Module 6: Facility outputs

Facility capacity

Fund and vehicle availability for referral and emergency referral

General service provision

Inpatient care and visits; outpatient care and visits; emergency visits; home or outreach visits

Module 3: Lab-based consumables, equipment, and capacity

A B C E P R OJ E CT D E S I G N

Sample design

Figure 1 Sampled districts in Odisha

A total of nine districts in Odisha were selected for the

ABCE survey (Figure 1). The districts were selected using three strata to maximize heterogeneity: proportion of full

immunization in children aged 12â&#x20AC;&#x201C;23 months as an indicator of preventive health services; proportion of safe delivery (institutional delivery or home delivery assisted

by skilled person) as an indicator of acute health services;

and proportion of urban population as an indicator of

overall development. The districts were grouped as high

and low for urbanization based on median value, and into

three equal groups as high, medium and low for the safe

delivery and full immunization indicators. Eight districts

were selected randomly from each of the various combinations of indicators, and in addition the capital district

was selected purposively.

Within each sampled district, we then sampled pub-

lic sector health facilities at all levels of services based

on the structure of the state health system (Figure 2).

Figure 2 Sampling strategy for health facilities in a district in the ABCE survey in India

Inventory of procedures for sterilization, sharp items, and infectious waste Inventory of personnel

Laboratory and diagnostic tests Module 7: Vaccines

Facility procedures for vaccine supply, delivery and disposal

Source from vaccine obtained Personnel administering vaccine Procedures to review adverse events Disposal of vaccines

Vaccine availability, storage, and output

Stock availability and stockouts of vaccines and syringes Types and functionality of storage equipment for vaccines Temperature chart history; vaccine inventory and vaccine outputs; vaccine outreach and home visits Vaccine sessions planned and held

Selected facilities are in blue; unselected facilities from the sampling frame are in grey. DH: District hospital; SDH: Sub-district hospital; CHC: Community health centre; PHC: Primary health centre; SHC: Sub health centre

ABCE IN ODISHA

A B C E P R OJ E CT D E S I G N

Data collection for the ABCE survey in OD

Table 4 Types of questions included in the Patient Exit Interview Survey in India SURVEY CATEGORY

Data collection took place from September 2014 to

TYPES OF KEY QUESTIONS AND RESPONSE OPTIONS

Direct observation of patient

Sex of patient (and of patient’s attendant if surveyed)

Direct interview with patient

Demographic questions (e.g., age, level of education attained, caste)

June 2015. Prior to survey implementation, PHFI and

the data collection agency hosted a two-week training workshop for 31 interviewers, where they received

Scaled-response satisfaction scores (e.g., satisfaction with medical doctor)

extensive training on the electronic data collection soft-

Open-ended questions for circumstances and reasons for facility visit, as well as visit characteristics (e.g., travel time to facility) Reporting costs associated with facility visit (user fees, medications, transportation, tests, other), with an answer of “yes” prompting follow-up questions pertaining to amount

ware (DatStat and Surveybe), the survey instruments,

the Odisha health system’s organization, and interviewing techniques. Following this workshop, a one-week

pilot of all survey instruments took place at health facil-

ities. Ongoing training occurred on an as-needed basis

throughout the course of data collection.

All collected data went through a thorough verification

process between PHFI and IHME and the ABCE field team.

Table 5 Facility sample, by platform, for the ABCE project in Odisha

In each sampled district, one district hospital (DH); all

sub-district hospitals (SDH, from a total of zero to three)

for each sampled DH; two community health centres

(CHC, from a total of two to five) for each sampled SDH;

FACILITY TYPE

two primary health centres (PHC, from a total of two to

FINAL SAMPLE

four) for each sampled CHC; and one sub centre (SHC,

District hospital

randomly selected for the study. A CHC facility was ex-

Sub-district hospital

it, and a PHC was excluded from the sampling scheme if

Community health centre

Primary health centre

Sub health centre

Total health facilities

108

from a total or one to four) for each sampled PHC were cluded from the sampling scheme if no PHC reported to

no SHC reported to it.

Patient Exit Interview Survey

A fixed number patients or attendants of patients were

interviewed at each facility, based on the expected outpa-

tient density for the platform. A target of 30 patients were

Following data collection, the data were methodically cleaned and re-verified, and securely stored in databases

hosted at PHFI and IHME.

A total of 108 health facilities participated in the ABCE

project. Four PHCs were replaced as the reporting chain of the sampled facility was not correct.

interviewed at district hospitals, 20 at SDH, 15 at CHC, 10 at PHC and five at SHC. Patient selection was based on

a convenience sample. The main purpose of the Patient

Exit Interview Survey was to collect information on pa-

tient perceptions of the health services they received and other aspects of their facility visit (e.g., travel time

to facility, costs incurred during the facility visit, and satisfaction with the health care provider). Table 4 provides more information on the specific indicators included in

the exit survey. This information fed into quantifying the

“demand-side” constraints to receiving care (as opposed

to the facility-based, “supply-side” constraints and bottlenecks measured by the ABCE Facility Survey).

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Main findings Health facility profiles T

Table 6 Availability of services in health facilities, by platform DISTRICT HOSPITAL (DH)

he delivery of facility-based health ser-

100%

94%

Routine deliveries

100%

Emergency obstetrics

100%

50%

Antenatal care

100%

Surgical services

100%

67%

Cardiology

11%

ally offered fewer services than district hospitals but still

Psychiatric

33%

gynecology services, antenatal care, laboratory services,

Accident, trauma, and emergency

100%

91%

78%

89%

100%

17%

Pediatric

100%

82%

72%

General anesthesiology

78%

64%

17%

Blood bank

100%

Dentistry

100%

DOTS treatment

100%

91%

72%

STI/HIV

100%

82%

28%

Immunization

100%

concentrated in urban areas.2 The public health system

Internal / general medicine

100%

78%

sonnel. The number of primary and community health

Mortuary

89%

64%

17%

Burns

56%

45%

17%

few facilities reported available services for non-com-

resources, ranging from personnel to phys-

municable disease such as cardiology, psychiatry, and

ical infrastructure, that vary in their relative

chemotherapy. District hospitals reported a wide range of

importance and cost to facilities. Determining what fac-

services such as blood banks, surgical services, dentistry

tors support the provision of services at lower costs and

and emergency obstetrics. Sub-district hospitals gener-

higher levels of efficiency at health facilities is critical in-

formation for policymakers to expand health system

reported high coverages of services like obstetrics and

coverage and functions within constrained budgets.

Using the ABCE Odisha facility sample (Table 5),

and DOTS. Few community health centres reported pro-

we analyzed five key drivers of health service provision

viding services such as STI/HIV treatment, ophthalmology,

at facilities:

or general anesthesiology.

• Facility-based resources (e.g., human resources, in-

Human resources for health

frastructure and equipment, and pharmaceuticals),

A facility’s staff size and composition directly affects

which are often referred to as facility inputs.

the types of services it provides. In general, a greater

• Patient volumes and services provided at facilities

availability of health workers is related to higher service

(e.g., outpatient visits, inpatient bed-days), which are

utilization and better health outcomes.1 India has a severe

also known as facility outputs.

shortage of qualified health workers and the workforce is

• Patient-reported experiences, capturing “de-

has a shortage of both medical and paramedical per-

mand-side” factors of health service delivery.

• Facility alignment of resources and service production,

centres without adequate staff is substantially higher if

which reflects efficiency.

high health-worker absenteeism is taken into consider-

ation.3 The Indian Government is aware of the additional

• Facility expenditures and production costs for

requirements and shortages in the availability of health

service delivery.

workers for the future. The National Rural Health Mission,

These components build upon each other to create

for instance, recommends a vastly strengthened infra-

a comprehensive understanding of health facilities in

structure, with substantial increases in personnel at every

Odisha, highlighting areas of high performance and

tier of the public health system.4

areas for improvement.

COMMUNITY HEALTH CENTRE (CHC)

Total obstetrics and gynecology services

zations, and pharmacy were nearly universally available,

vices requires a complex combination of

SUB-DISTRICT HOSPITAL (SDH)

Based on the ABCE sample, we found substantial het-

erogeneity across facility types in OD by considering the

Facility capacity and characteristics

Ophthalmology

Orthopedics

89%

27%

Pharmacy

100%

83%

Chemotherapy

11%

Dermatology

56%

Alternative medicine

11%

67%

Diagnostic medical

100%

82%

17%

Laboratory services

100%

94%

44%

36%

39%

Outreach services

Figure 3 Composition of facility personnel, by platform

District Hospital

Sub District Hospital

Community Health Centre

Primary Health Centre

Sub Health Centre

1 Rao KD, Bhatnagar A, Berman P. So many, yet few: Human resources for health in India. Human Resources for Health. 2012; 10(19). 2 Rao M, Rao KD, Kumar AK, Chatterjee M, Sundararaman T. Human resources for health in India. The Lancet. 2011; 377(9765): 587-98. 3 Hammer J, Aiyar Y, Samji S. Understanding government failure in public health services. Economic and Political Weekly. 2007; 42: 4049–58. 4 National Rural Health Mission. Ministry of Health and Family Welfare, Government of India. Mission Document (2005-2012). New Delhi, India: Government of India, 2005.

Across and within district hospitals, sub-district hos-

pitals, and community health centres in OD (Table 6),

several notable findings emerged for facility-based

health service provision. While fundamental services

such as routine deliveries, general medicine, immuni-

LOWEST AVAILABILITY

Number of Staff

Doctors

Nurses

ANM

Para-medical staff

100

150

Non-medical staff

total number of staff in the context of to bed strength

(i.e., number of beds in the facility) and patient load (Fig-

ure 3). Overall, the most common medical staff at district

hospitals were non-medical staff (30) and nurses (30), fol-

lowed by doctors (26), while at lower levels, paramedical

staff and auxiliary nurse midwives (ANMs) outnumbered doctors and nurses. This is a reflection of the differential

service offerings between higher- and lower-level facili-

ties. Additionally, higher level facilities tended to have a greater number of health personnel overall; while a

degree of this variation is due to differences in service

provision and population size, some of this indicates rela-

tive shortages in human resources for health.

The greatest number of doctors, nurses, ANMs, para-

medical staff, and non-medical staff are concentrated at

the district hospitals (average of 118 total staff). Sub-district hospitals reported the second highest number of personnel; however, the total personnel at these facilities

was one-half of what was reported by district hospitals (average of 56 total staff). Community health centres

maintained a smaller body of health workers, an average

total of 26, with most of the medical staff being paramed-

NA: Not applicable to this platform according to standards.

Service availability

ical (five). Primary health centres reported, on average,

HIGHEST AVAILABILITY

five staff in total, most of which were paramedical staff. Finally, sub-health centres reported the lowest number

Note: All values represent the percentage of facilities, by platform that reported offering a given service at least one day during a typical week.

of staff, with only two paramedical and ANM personnel

who perform immunizations, simple outpatient care, and community outreach.

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Figure 4 Ratio of nurses and ANMs to doctors by platform

Figure 5 Ratio of nurses, ANMs, and doctors to paramedical and non-medical staff by platform

Vertical bars represent the platform average ratio.

Figure 6 Ratio of beds to doctors by platform

Figure 7 Ratio of beds to nurses by platform

Vertical bars represent the platform average ratio.

District Hospital

Sub District Hospital

District Hospital

Sub District Hospital

District Hospital

Sub District Hospital

District Hospital

Sub District Hospital

Community Health Centre

Primary Health Centre

Community Health Centre

Primary Health Centre

Community Health Centre

Primary Health Centre

Community Health Centre

Primary Health Centre

Nurses to doctors ratio

ratio of 2 indicates that there are two nurses, ANMs, and/

or doctors staffed for every one paramedical/non-medi-

The ratio of number of nurses and ANMs to number

cal staff. Alternatively, a ratio lower than 1 indicates that

of doctors is presented in Figure 4. A ratio greater than

paramedical and/or non-medical personnel outnumber

1 indicates that nurses and ANMs outnumber doctors; for instance, a ratio of 2 indicates that there are two nurses

nurses, ANMs, and/or doctors.

tio lower than 1 indicates that doctors outnumber nurses

1, ranging from 0.5 to 2, with only two facilities having

one nurse or ANM staffed for every two doctors.

ANMs, and doctors. All sub-district hospitals had a ratio of

Most district hospitals reported ratios greater than

and ANMs staffed for every one doctor. Alternatively, a ra-

more paramedical and non-medical staff than nurses,

and ANMs; for instance, a ratio of 0.5 indicates there is

nurses, ANMs, and doctors to paramedical and non-med-

In general, district hospitals reported a high ratio, indi-

cating that they staff more nurses and ANMs than doctors.

ical staff less than or equal to one; there was an average

ranged from 0.7 to 2.3. All sub-district hospitals reported

non-medical staff. Community health centres were more

and ANMs to doctors. There was heterogeneity among

ities reporting ratios that ranged from 0.1 to 0.7. The ratio

of 0.7 nurses, doctors, and ANMs to paramedical and

However, the ratio reported by various district hospitals

more nurses than doctors, with a ratio as high as 3 nurses

community health centres, with ratios ranging from 0.5

erage ratio of 0.5 nurses or ANMs to doctors.

Nurses and doctors to paramedical and non-medical staff

2012 is presented in Figure 6. A ratio greater than 1 indi-

The ratio of number of nurses, ANMs, and/or doc-

cates that beds outnumber doctors; for instance, a ratio

in 2012 is presented in Figure 5. A ratio greater than 1

tor staffed. Alternatively, a ratio lower than 1 indicates that

paramedical and non-medical personnel; for instance, a

The average ratio of beds to doctors is highest in sub

of 2 indicates that there are two beds for every one doc-

tors to number of paramedical and/or non-medical staff

doctors outnumber beds.

indicates that nurses, ANMs, and doctors outnumber

Further, some facilities may have much smaller patient

and with ratios ranging from 1.2 to 18.0. The average ratio

volumes than others, and thus “achieving” staffing tar-

among primary health centres was 0.8 due to many facili-

gets could leave them with an excess of personnel given

ties not reporting doctors on staff.

patient loads. While an overstaffed facility has a different

set of challenges than an understaffed one, each reflects

Beds to nurses ratio

a poor alignment of facility resources and patient needs.

The ratio of number of beds to number of nurses in

2012 is presented in Figure 7. A ratio greater than 1 indi-

To better understand bottlenecks in service delivery and

of 2 indicates that there are two beds for every one nurse

ty’s capacity (inputs) in the context of its patient volume

areas to improve costs, it is important to assess a facili-

cates that beds outnumber nurses; for instance, a ratio

and services (outputs). We further explore these find-

staffed. Alternatively, a ratio lower than 1 indicates that

to nurses was highest among sub district hosptials (av-

The ratio of number of beds to number of doctors in

get may be less important than having too few nurses.

among community health centres, at an average of 5.8

for primary health centres ranged from 0 to 2, with an av-

Beds to doctors ratio

administration, failing to achieve the doctor staffing tar-

The ratio of beds to doctors was most heterogeneous

nurses outnumber beds.

and non-medical staff.

the same number of nurses staffed as doctors, with an av-

cility mostly offers services that do not require a doctor’s

district hospitals (9.4), followed by district hospitals (7.3).

homogenous, reporting an average ratio of 0.4, with facil-

erage of 0.8 ANMS, doctors, and nurses to paramedical

to 2.5. Finally, all primary health centres reported fewer or

ings in the “Efficiency and costs” section. As part of the

Similar to the ratio of beds to doctors, the ratio of beds

ABCE project in India, we compare levels of facility-based

erage of 8.3, ranging from 3.2 to 23.3). The average ratio

services. In this report, we primarily focus on the delivery

hospitals (6.8 and 6.4, respectively). However, the range

include doctors, nurses, and other paramedical staff. It

than for district hospitals (3.3 to 10.2). Only two primary

vice provision, especially at lower levels of care, but the

staffing with the production of different types of health of health services by skilled medical personnel, which

among community health centres was similar to district

is possible that non-medical staff also contribute to ser-

for community health centres (2.0 to 16.0) was wider

ABCE project in India is not currently positioned to ana-

health centres had nurses, with an average ratio of beds

lyze these scenarios.

to nurses of 3.0.

In isolation, facility staffing numbers are less meaning-

Infrastructure and equipment

ful without considering a facility’s overall patient volume

Health service provision depends on the availability of

and production of specific services. For instance, if a fa-

adequate facility infrastructure, equipment, and supplies

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Table 7 Availability of physical capital, by platform DISTRICT HOSPITAL (DH)

Table 8 Availability of functional equipment, by platform

SUB-DISTRICT HOSPITAL (SDH)

COMMUNITY HEALTH CENTRE (CHC)

PRIMARY HEALTH CENTRE (PHC)

SUB HEALTH CENTRE (SHC)

Functional electricity

100%

97%

77%

Piped water

100%

91%

72%

40%

14%

Flush toilet

100%

67%

49%

23%

Hand disinfectant

100%

94%

83%

60%

89%

100%

94%

Emergency four-wheeled vehicle

100%

45%

Landline phone

100%

91%

78%

14%

Computer

100%

Any four-wheeled vehicle

NA: Not applicable to this platform according to standards. LOWEST AVAILABILITY

HIGHEST AVAILABILITY

Note: Values represent the percentage of facilities, by platform, that had a given type of physical capital

Water and sanitation

(physical capital). In this report, we focus on four essen-

tial components of physical capital: power supply, water

All district hospitals had availability of improved water

and sanitation, transportation, and medical equipment,

physical capital, excluding medical equipment, available

100%

89%

80%

94%

Child scale

100%

94%

51%

74%

Blood pressure apparatus

100%

94%

91%

Stethoscope

100%

91%

94%

97%

Glucometer

56%

45%

56%

20%

34%

Test strips for glucometer

56%

45%

33%

14%

37%

Hematologic counter

44%

55%

22%

Lab equipment

Blood chemistry analyzer

67%

55%

Incubator

89%

73%

11%

Centrifuge

100%

56%

Microscope

100%

23%

Slides

89%

91%

100%

83%

91%

Slide covers

67%

73%

78%

54%

80%

X-ray

100%

22%

Imaging equipment 6%

ble 7). All hospitals and 67% of community health centres

CT scan

11%

of primary health centres and 23% of sub health centres.

NA: Not applicable to this platform according to standards.

to piped water was less available as platforms lowered,

smaller facilities, just 3% of primary health centres and

Adult scale

82%

again was less available in sub health centres. Access

access to a functional electrical supply (Table 7). Among

Medical equipment

45%

tary sanitation method at most platform levels, though

All hospitals and community health centres reported

LOWEST AVAILABILITY

HIGHEST AVAILABILITY

Note: Availability of a particular piece of equipment was determined based on facility ownership on the day of visit. Data on the number of items present in a facility were not collected. All values represent the percentage of facilities, by platform, that had a given piece of equipment.

available in 91% of sub-district hospitals, 72% of commu-

23% of sub health centres lacked functional electric-

nity health centres, 40% of primary health centres, and

ity. Two facilities reported solely relying on a generator

14% of sub health centres. Among all facilities, 31% re-

for power.

ported a severe shortage of water at some point during

These results demonstrate clear improvement in

the year. These findings show a mixture of both notable

the availability of electricity at the lowest platform level

gains and ongoing needs for facility-based water sources

compared to 2007â&#x20AC;&#x201C;2008, when only 20% of sub health

and sanitation practices among primary care facilities.

centres had a regular electric supply.5 However, it should

Transportation and computers

be noted that inadequate access to consistent electric

power has substantial implications for health service pro-

Facility-based transportation and modes of commu-

vision, particularly for the effective storage of medications,

nication varied across platforms (Table 7). In general, the

vaccines, and blood samples.

availability of a vehicle, substantially decreased down the

levels of the health platform. Only 3% of primary health centres had any four-wheeled vehicles, which means

5 International Institute for Population Sciences (IIPS). District Level Household and Facility Survey (DLHS-3), 2007-08: India, Orissa. Mumbai, India: IIPS, 2010.

transferring patients under emergency circumstances

SUB-HEALTH CENTRE

78%

Hand disinfectant was broadly available as a supplemen-

Power supply

PRIMARY HEALTH CENTRE

78%

had flush toilets, though these were available in only 49%

across platforms.

COMMUNITY HEALTH CENTRE

ECG

with a functional sewer infrastructure with flush toilets (Ta-

other medical equipment. Table 7 illustrates the range of

SUB-DISTRICT HOSPITAL

Ultrasound

sources (functional piped water) and improved sanitation

with the latter composed of laboratory, imaging, and

DISTRICT HOSPITAL

ABCE IN ODISHA

from these facilities could be fraught with delays and

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

of equipment should be available in hospitals and pri-

possible complications. While 94% of community health

mary care facilities.6 Table 8 illustrates the distribution of

centres had any four-wheeled vehicles, only 6% had ded-

SARA scores across platforms. In general, hospitals had

icated emergency transportation. This transportation

greater availability of medical equipment, and notable

gap and the coordination of transport might be further

deficits in essential equipment availability were found in

exacerbated by the relatively low availability of landline

phones at lower-level facilities.

Testing availability

patient clinical data, but the large majority of facilities

across all platforms did carry these. One exception is that

For three main types of facility equipment – medical,

nearly half of primary health centres were not equipped

lab, and imaging – clear differences emerge across levels

with a functional child scale.

of health service provision, with Table 8 summarizing the

Microscopes and corresponding components were

availability of functional equipment by platform.

largely prevalent among all facilities, except at primary

We used WHO’s Service Availability and Readiness

health centres where most had slides but only one-quar-

Assessment (SARA) survey as our guideline for what types

the lower levels of care. Lacking scales and blood pressure cuffs can severely limit the collection of important

Equipment

Table 10 Availability of blood tests and functional equipment to perform routine delivery care, by platform

ter had a microscope itself. Additional testing capacity 6 World Health Organization (WHO). Service Availability and Readiness Assessment (SARA) Survey: Core Questionnaire. Geneva, Switzerland: WHO, 2013.

DISTRICT HOSPITAL

SUB-DISTRICT HOSPITAL

COMMUNITY HEALTH CENTRE

PRIMARY HEALTH CENTRE

100%

72%

17%

Glucometer and test strips

33%

36%

28%

11%

Cross-match blood

89%

100%

11%

Blood pressure apparatus

100%

94%

IV catheters

100%

89%

60%

Gowns

100%

91%

72%

26%

89%

82%

83%

54%

Masks

100%

73%

67%

17%

Sterilization equipment

100%

72%

29%

Adult bag valve mask

89%

73%

39%

Ultrasound

78%

45%

89%

91%

83%

23%

Needle holder

100%

80%

Speculum

100%

94%

26%

Dilation and curettage kit

100%

73%

56%

11%

Neonatal bag valve mask

100%

82%

72%

11%

Vacuum extractor

67%

82%

50%

Incubator

78%

82%

33%

Facilities reporting delivery services

100%

29%

Facilities fully equipped for delivery services based on above tests and equipment availability

11%

Hemoglobin

Medical equipment

Measuring tape

Delivery equipment Infant scale

Table 9 Availability of tests and functional equipment to perform routine antenatal care, by platform DISTRICT HOSPITAL

SUB-DISTRICT HOSPITAL

COMMUNITY HEALTH CENTRE

PRIMARY HEALTH CENTRE

SUB HEALTH CENTRE

Testing availability Urinalysis

100%

56%

54%

Hemoglobin

100%

72%

17%

86%

33%

36%

28%

11%

29%

100%

91%

33%

Blood pressure apparatus

100%

94%

91%

Adult scale

100%

89%

80%

94%

Ultrasound

78%

45%

100%

77%

83%

22%

27%

21%

Glucometer and test strips Blood typing Functional equipment

Service summary Facilities reporting ANC services Facilities fully equipped for ANC provision based on above tests and equipment availability

Service summary

NA: Not applicable to this platform according to standards. LOWEST AVAILABILITY

HIGHEST AVAILABILITY

Note: Availability of a given delivery item was determined by its availability at a facility on the day of visit. All values represent the percentage of facilities, by platform, that had the given delivery item. The service summary section compares the total percentage of facilities reporting that they provided routine delivery services with the total percentage of facilities that carried all of the recommended pharmaceuticals and functional equipment to provide routine delivery services.

NA: Not applicable to this platform according to standards. LOWEST AVAILABILITY

HIGHEST AVAILABILITY

Note: Availability of a given ANC item was determined by its availability at a facility on the day of visit. All values represent the percentage of facilities, by platform that had the given ANC item. The service summary section compares the total percentage of facilities reporting that they provided ANC services with the total percentage of facilities that carried all of the functional equipment to provide ANC services.

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Table 11 Availability of blood tests and functional equipment to perform general surgery, by platform DISTRICT HOSPITAL (DH)

SUB-DISTRICT HOSPITAL (SDH)

COMMUNITY HEALTH CENTRE (CHC)

PRIMARY HEALTH CENTRE (PHC)

Testing availability Hemoglobin Cross-match blood

hospitals had a blood chemistry analyzer, while this was

ensuring that these facilities carry the supplies they need

to provide a full range of services. Measuring the avail-

a functional glucometer, and half had test strips for the

specific deficits, but assessing a health facility’s full stock

no primary health centres. About half of hospitals had

72%

17%

89%

100%

community health centres and primary health centre

for carrying out the test. This indicates limited capacity for

ability of individual pieces of equipment sheds light on

glucometer but only one-third had both items. In both

of necessary or recommended equipment provides a

more precise understanding of a facility’s service capacity.

more facilities had glucometers than test strips essential

100%

94%

IV catheters

100%

89%

60%

Sterilization equipment

100%

72%

29%

Gowns

100%

91%

72%

26%

Masks

100%

73%

67%

17%

89%

73%

67%

Surgical equipment

Focus on service provision

For the production of any given health service, a

addressing non-communicable diseases (NCDs) such as diabetes, for which this equipment is necessary.

health facility requires a complex combination of the ba-

ing equipment, with the notable exception of CT scans

personnel who are adequately trained to administer nec-

hospitals show patchy availability of imaging equipment

it is important to consider this intersection of facility re-

scanners. Community health centres had poor availability

this report, we further examined facility capacity for a

Overall, these findings demonstrate gradual improve-

eral surgery, and laboratory testing. For these analyses

District hospitals had fairly good availability of imag-

sic infrastructure, equipment, and pharmaceuticals, with

which were available in only 11% of facilities. Sub-district

essary clinical assessments, tests, and medications. Thus,

sources to best understand facility capacity for care. In

as more than half had no ultrasound and none had CT

Thermometer

78%

91%

83%

43%

General anesthesia equipment

89%

73%

67%

Scalpel

89%

91%

83%

49%

Suction apparatus

100%

67%

14%

Retractor

100%

50%

11%

89%

55%

39%

Blood storage unit/refrigerator

78%

82%

50%

Intubation equipment

78%

45%

22%

100%

67%

51%

Blood typing

33%

18%

Table 12 Availability of laboratory tests, by platform DISTRICT HOSPITAL (DH)

Service summary

NA: Not applicable to this platform according to standards. LOWEST AVAILABILITY

HIGHEST AVAILABILITY

Note: Availability of a given surgery item was determined by its availability at a facility on the day of visit. All values represent the percentage of facilities, by platform, that had the given surgery item. The service summary section compares the total percentage of facilities reporting that they provided general surgery services with the total percentage of facilities that carried all of the recommended functional equipment to provide general surgery services.

subset of specific services – antenatal care, delivery, gen-

of essential imaging equipment such as x-rays and ECGs.

Nasogastric tube

Facilities fully equipped for general surgery services based on above tests and equipment availability

equipment in OD, as well as the continued challenge of

available in only 6% of community health centres and

100%

Blood pressure apparatus

Facilities reporting general surgery services

ments in equipping health facilities with basic medical

instance, 67% of district hospitals and 55% of sub-district

100%

Medical equipment

Adult bag valve mask

was poor in hospitals and community health centres. For

SUB-DISTRICT HOSPITAL (SDH)

COMMUNITY HEALTH CENTRE (CHC)

PRIMARY HEALTH CENTRE (PHC)

100%

91%

33%

Cross-match blood

89%

100%

Complete blood count

56%

27%

17%

Hemoglobin

100%

72%

17%

HIV

100%

44%

Liver function

33%

100%

97%

Renal function

56%

18%

Serum electrolytes

33%

Spinal fluid test

22%

Syphilis

89%

82%

17%

Tuberculosis skin

89%

27%

28%

100%

56%

Malaria

Urinalysis

NA: Not applicable to this platform according to standards. LOWEST AVAILABILITY

HIGHEST AVAILABILITY

Note: Availability of a given test was determined by its availability at a facility on the day of visit. All values represent the percentage of facilities, by platform, that had the given test.

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Figure 8 Number of outpatient visits, by platform

of coverage; moreover, it neither reflects what services

of service provision, we only included facilities that re-

were actually provided nor the quality of care received.

ported providing the specific service, excluding facilities

Note: Each line represents outpatient visits for an individual facility, with the bold line depicting the average for the platform. Scales are different for each platform.

Through the ABCE Facility Survey, we estimated what pro-

that were potentially supposed to provide a given service

portion of facilities that stocked the range of tests and

but did not report providing it in the ABCE Facility Sur-

100,000

â&#x20AC;&#x153;ceilingâ&#x20AC;? across platforms, as we are not reporting on the

important to note that this list was not exhaustive but rep-

have indicated otherwise on the ABCE Facility Survey.

provision of ANC.

2012

2013

In OD, according to the National Family Health Sur-

ANC services, few were adequately supplied for care. Dis-

(ANC) visits during their last pregnancy.7 This is a low level

trict hospitals critically lacked glucometer and test strips, resulting in only 22% of facilities having all the necessary

2011

2010

2009

OP visits by facility

2012

2013

OP visits average

30,000

PHC

7 International Institute for Population Sciences (IIPS) and Macro International. National Family Health Survey (NFHS-4), 2015-2016: Odisha Factsheet. Mumbai, India: IIPS, 2016.

Figure 9 Number of inpatient visits (excluding deliveries), by platform Note: Each line represents inpatient visits for an individual facility, with the bold line depicting the average for the platform. Scales are different for each platform.

20,000

Visits 20,000 40,000 60,000 80,000 100,000

munity health centres in this survey reported providing

vey-4, 62% of women had at least four antenatal care

OP visits average

CHC

ANC is presented in Table 9. While all hospitals and com-

OP visits by facility

2012

2013

2009

2010

2011

2012

2009

2013

PHC

600

2009

2010

2011

IP visits by facility

2013

200

2012 OP visits average

2012 IP visits average

2011

OP visits by facility

2011

Visits 400

10,000 2010

5,000

Visits

500 0

2009

2010

IP visits by facility

IP visits average

CHC

15,000

Visits 1,000 1,500

2,000

IP visits by facility

800

2,500

SHC

20,000

OP visits average

20,000

2011

2010

2009

2013

2012 OP visits average

Visits 40,000

2011

OP visits by facility

2010

Visits

2009

SDH

40,000

60,000

10,000

80,000

Visits

60,000

2011

OP visits by facility

The availability of tests and functional equipment for

Antenatal care services

40,000 20,000

2010

resented a number of relevant supplies necessary for the

facilities that likely should provide a given service but

Visits 60,000

Visits 200,000 100,000 0

2009

medical equipment to conduct a routine ANC visit. It is

vey. Thus, our findings reflect more of a service capacity

SDH

80,000

300,000

400,000

2012

2009

2013

2010

2011

IP visits by facility

IP visits average

2012 IP visits average

2013

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Figure 10 Number of deliveries, by platform

Figure 11 Number of immunization doses administered, by platform

Note: Each line represents deliveries for an individual facility, with the bold line depicting the average for the platform. Scales are different for each platform.

Note: Each line represents immunization doses for an individual facility, with the bold line depicting the average for the platform. Scales are different for each platform.

2011

Deliveries by facility

2013

2011

Deliveries by facility

2012

20,000 0

Immunization doses by facility

Immunization doses average

2010

2011

Deliveries by facility

2012

2013

Deliveries average

2009

2010

2011

2010

2009

2013

2012

2011

Immunization doses by facility

Immunization doses average

Immunization doses by facility

2,500

district hospitals to the lower levels of care, reported

paucity of both tests and equipment. No primary health

functional equipment needed to optimally address the

centres were adequately equipped for providing ANC

range of patient needs during an ANC visit. Lack of sim-

services. Urinalysis and hemoglobin testing were actually

ple tests or material for tests (such as glucometer and test

available in more sub health centres than primary health

strips) prevented most facilities from being listed as fully

many essential tests.

suggest that these platforms are entirely unable to pro-

centres, but facilities in both of these platforms lacked

equipped to provide ANC services. These findings do not

Across the levels of care, we found gaps between facil-

Doses administered 1,000 1,500 2,000

providing ANC, but then lacked at least one piece of

500

ultrasound. In community health centres, there was a

tals were equipped: for example, 55% had no available

service-capacity gap meant that many facilities, from

2009

2010

2011

Immunization doses by facility

vide adequate ANC services; it simply means that the vast

ity-reported capacity for ANC provision and the fraction

majority of facilities did not have the recommended diag-

of the facilities fully equipped to deliver ANC care. This

nostics and medical equipment for ANC.

2013

PHC

SHC

tests and equipment. Similarly, 27% of sub-district hospi-

2012

Immunization doses average

Doses administered 1,000 2,000

0 2009

2013

Deliveries average

2011

2010

2009

2013

2012

2011

Doses administered 5,000

100 0

2010

CHC

Deliveries 200

Deliveries 1,000 1,500 500 0

2009

Immunization doses by facility

300

2,000

2012 Deliveries average

PHC

400

CHC

2,500

2010

3,000

2009

2013

2012 Deliveries average

10,000

2011

Deliveries by facility

2010

SDH

Doses administered 5,000 10,000 15,000

40,000

2,000

Deliveries 4,000

Deliveries 4,000 6,000 2,000

2009

Doses administered 10,000 20,000 30,000

8,000

SDH

6,000

8,000

2012

2013

Immunization doses average

2012

2013

Immunization doses average

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Table 13 Characteristics of patients interviewed after receiving care at facilities

This finding is cause for concern, as not having access

SDH

CHC

PHC

TOTAL

Total patient sample

508

246

286

154

1194

Percent female

38%

34%

36%

45%

38%

<16

15%

12%

21%

25%

17%

16–29

29%

32%

20%

29%

30–39

20%

26%

16%

19%

20%

40–49

21%

15%

17%

15%

18%

>50

15%

13%

21%

16%

Scheduled caste/scheduled tribe

38%

41%

48%

55%

43%

Other backwards caste

20%

25%

24%

16%

22%

None

14%

17%

28%

16%

Classes 1 to 5

23%

30%

34%

36%

29%

Classes 6 to 9

29%

28%

26%

28%

Class 10 or higher

34%

28%

21%

11%

27%

Patient’s age group (years)

Education attainment

DH: District hospital; SDH: Sub-district hospital; CHC: Community health centre; PHC: Primary health centre Note: Educational attainment refers to the patient’s level of education or the attendant’s educational attainment if the interviewed patient was younger than 18 years old.

Delivery care services

Figure 12 Patient travel times to facilities, by platform

the exception of nasogastric tubes and intubation equip-

to adequate delivery equipment can affect both maternal

Eighty-five percent of deliveries in OD are in a health

facility, and 76% of deliveries are in a public facility. Avail8

and neonatal outcomes at all levels of care.

9,10

ment in sub-district hospitals. There were large gaps,

Again, we

particularly in testing and surgical equipment, in commu-

found a substantial gap between the proportion of facil-

nity health centres and primary health centres. Very few

ities, across platforms, that reported providing routine

primary health centres had essential medical equipment

delivery services and those that were fully equipped for

or surgical equipment, indicating a severe lack of capacity

their provision.

to provide surgical services. It is also crucial to consider

the human resources available to perform surgical proce-

General surgery services

dures, as assembling an adequate surgical team is likely

Availability of essential tests and equipment for gen-

to affect patient outcomes. Given the nature of documen-

eral surgery services is presented in Table 11. 33% of

tation of human resources in the records, such data could

district hospitals had all of the essential items; however,

not be captured, but future work on assessing surgical ca-

no single item was missing from more than one-quarter

pacity at health facilities should collect this information.

of district hospitals. Availability was substantially lower in

Laboratory testing

sub-district hospitals (18%) while no community health

centres or primary health centres were fully equipped.

The availability of laboratory tests is presented in Ta-

Essential medical equipment and testing was mostly

ble 12. While all district hospitals and sub-district hospitals

equipment was also relatively high among hospitals with

test availability. Availability was generally high in district

available in both types of hospitals. Availability of surgical

offer the range of laboratory services, there were gaps in

hospitals, and decreased at lower facility levels with par-

ticularly large gaps among primary health centres. Serum

9 Nyamtema AS, Urassa DP, van Roosmalen J. Maternal health interventions in resource limited countries: a systematic review of packages, impacts and factors for change. BMC Pregnancy and Childbirth. 2011; 11(30). 10 Wall SN, Lee ACC, Carlo W, Goldenberg R, Niermeyer S, Darmstadt GL, et al. Reducing intrapartum-related neonatal deaths in low- and middle-income countries — what works? Seminars in Perinatology. 2010; 34: 395–407.

electrolyte tests, useful as part of a metabolic panel and to

measure symptoms of heart disease and high blood pressure, had very low availability in district hospitals (33%),

sub-district hospitals (9%), and community health cen-

Figure 13 Patient wait times at facilities, by platform

Figure 14 Patient scores of facilities, by platform

ability of essential equipment is necessary for providing

high-quality delivery care; these results are presented in

Table 10. Availability was generally highest in district hos-

pitals, declining at lower levels with notable gaps among

SDH

primary health centres. While most sub-district hospitals

SDH

services, none had all essential tests and equipment avail-

CHC

An ultrasound machine was absent from 55% of sub-dis-

PHC

SDH

and community health centres offered routine delivery

CHC

able and only 11% of district hospitals were fully equipped.

PHC

60 Percent (%)

< 30 min. >1 hr.

trict hospitals despite them being an essential item for

100

service provision. Cross-match blood tests and equip-

30 min.-1 hr.

ment such as bag valve masks and incubators were not

widely available outside of hospitals.

DH: District hospital; SDH: Sub-district hospital; CHC: Community health centre; PHC: Primary health centre 8 International Institute for Population Sciences (IIPS) and Macro International. National Family Health Survey (NFHS-4), 2015-2016: Odisha Factsheet. Mumbai, India: IIPS, 2016.

PHC

0 0

60 Percent (%)

< 30 min.

100

60 Percent (%) <6 8-9

> 30 min.

80 6-7 10

Patients were asked to score the facility on a scale from 1-10, with 10 being the highest score. DH: District hospital; SDH: Sub-district hospital; CHC: Community health centre; PHC: Primary health centre Note: Facility ratings were reported along a scale of 0 to 10, with 0 as the worst facility possible and 10 as the best facility possible.

DH: District hospital; SDH: Sub-district hospital; CHC: Community health centre; PHC: Primary health centre

100

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Table 14 Proportion of patients satisfied with facility visit indicators, by platform DISTRICT HOSPITAL

SUB-DISTRICT HOSPITAL

COMMUNITY HEALTH CENTRE

PRIMARY HEALTH CENTRE

Nurse/ANM Doctor

Medical provider respectfulness

84%

27%

82%

100%

Clarity of provider explanations

76%

23%

82%

100%

Time to ask questions

84%

45%

91%

100%

Medical provider respectfulness

90%

85%

84%

85%

Clarity of provider explanations

90%

84%

75%

90%

Time to ask questions

89%

86%

80%

93%

Cleanliness

21%

37%

53%

Privacy

72%

68%

63%

Facility characteristics

present at only 22% of district hospitals and 33% of dis-

trict hospitals, respectively. Most facilities were equipped

to test for malaria, though fewer than half of community

health centres could test for HIV and tuberculosis; only 3%

of primary health centres had tests for either of these conditions available.

SDH

Facility outputs

Measuring a facility’s patient volume and the number

CHC

of services delivered, which are known as outputs, is crit-

ical to understanding how facility resources align with

PHC

patient demand for care. The number of outpatient visits

60 Percent (%)

Got none/some of the drugs

erage of 8,552–10,067 visits per year) than sub-health

visits per year), with one facility reporting more than 350

Inpatient visits generally entail more service demands

The reported number of deliveries, by platform

centres (average of 580–764 visits per year).

inpatient visits per year.

than outpatient visits, including ongoing occupancy

and over time, is presented in Figure 10. District hos-

of facility resources such as beds. The reported num-

pitals reported an average between 3,492 and 4,656

presented in Figure 9. Over time, the average number

hospitals reported an average of 2,310–2,558 deliveries

District hospitals provided care for an average of 27,802–

in the number of deliveries over time, several hospitals

provided care for an average of 16,029–18,158 visits per

servation. Community health centres reported an annual

deliveries in each year of observation, while sub-district

ber of inpatient visits (other than deliveries) by year are

per year. While many hospitals experienced an increase

of inpatient visits has slightly increased for all platforms.

32,254 inpatient visits per fiscal year. Sub-district hospitals

reported decreasing numbers over the five years of ob-

year, while community health centres provided much

average number of deliveries between 479 and 685. Few

66%

tres (6%). Spinal fluid tests and liver function tests were

substantially fewer inpatient visits (on average 30–46

reported more than 10 times more outpatient visits (av-

Figure 16 Determinants of satisfaction with doctors

HIGHEST AVAILABILITY

Figure 15 Availability of prescribed drugs at facility, by platform

patient visits per year). Primary health centres reported

of 27,446–29,102 visits per year). Primary health centres

Staff interactions

LOWEST AVAILABILITY

fewer visits (an average between 2,378 and 3,038 in-

number reported by community health centres (average

Female Male >=40 years 16-39 years Other castes Backwards caste Any schooling No schooling Not given all prescribed drugs Given all prescribed drugs Wait time <30 min Wait time >=30 min DH PHC CHC SDH

by fiscal year, by platform, is presented in Figure 8. In gen-

100

Odds Ratio

eral, the average number of outpatient visits increased

Got all perscribed drugs

slightly over five fiscal years. Patient volume was high-

DH: District hospital; SDH: Sub-district hospital; CHC: Community health centre; PHC: Primary health centre

est in district hospitals (average of 175,621–203,342 visits

Dotted vertical line represents an odds ratio of one. Black points represent the reference groups, which all carry an odds ratio of one. Compared to the referent category, significant odds ratios and 95% confidence intervals are represented with blue points and horizontal lines, respectively. Odds ratios that are not significant are represented by green points, and their 95% confidence intervals with a green horizontal line. Any confidence intervals with an upper bound above 3 were truncated for ease of interpretation.

57,895–62,716 visits per year, which was near double the

DH: District hospital; SDH: Sub-district hospital; CHC: Community health centre; PHC: Primary health centre

per year). Sub-district hospitals reported an average of

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Patient perspectives

deliveries were reported in primary health centres (an average of 19–27 deliveries per year). The ratio of deliveries

Table 15 Input-output model specifications

the closest health facilities for many patients, particularly those in rural areas. It also reflects longer distances that

A facility’s availability of and capacity to deliver ser-

to inpatient visits is higher among the lower platforms.

vices is only half of the health care provision equation; the

CATEGORY

other half depends upon patients seeking those health

Immunization

Inputs

services. Many factors can affect patients’ decisions to

The number of immunization doses administered over

tients view the care they receive. These “demand-side”

number of doses administered remained stable over the

constraints can be more quantifiable (e.g., distance from

five fiscal years. District hospitals reported double the

Model 1

Outputs

facility) or intangible (e.g., perceived respectfulness of

number of immunization doses administered (annual

Inputs

or have contact with the health system at all.

Community health centres reported providing an average

who presented at health facilities and their perspectives

delivery; primary health centres reported an average of

on the care they received. Table 13 provides an overview

50–164 doses per year while sub health centres reported

of the interviewed patients (n=1,194) or their attendants

more, with an average of 750–1,261 doses per year.

primary health centres (90%) received care within 30 min-

Inpatients visits (excluding deliveries)

utes. Wait times were longer at district hospitals (37% of patients waited more than 30 minutes to receive care)

and sub-district hospitals (33%). Fewer than 2% of all pa-

Number of beds

tients waited more than one hour to receive care.

Number of doctors

Patient satisfaction ratings

Number of ANMs

Surveys, we examined the characteristics of patients

ties at the PHC and SHC level are central to immunization

forms (Figure 13), and nearly all patients seeking care at

Outpatient visits

Number of nurses

Using data collected from the Patient Exit Interview

number of doses between 698 and 2,338 per year. Facili-

waited less than 30 minutes to receive care at all plat-

Immunization visits

pact on whether patients seek care at particular facilities

hospitals (annual averages between 7,040 and 11,798).

In terms of wait time, the large majority of patients

Expenditure on pharmaceuticals

Deliveries

the health care provider), but each can have the same im-

averages between 14,736 and 27,336) than sub-district

district hospitals.

Expenditure on personnel All other expenditure

seek care, ranging from associated visit costs to how pa-

time, by platform, is presented in Figure 11. The average

patients travel to receive the specialized care offered at

VARIABLES

Number of paramedical staff

We report primarily on factors associated with patient

Number of non-medical staff

Model 2 Outputs

satisfaction with provider care and perceived quality of

Outpatient visits

services by patients on medicine availability, and hospital

Inpatients visits (excluding deliveries)

infrastructure as these have been previously identified to

Immunization visits

health services in India.11

be of significance in the patient’s perception of quality of

Deliveries

Ratings of patient satisfaction were based on a rating

from 1-10, with 10 being the highest score, are presented

Figure 17 Determinants of satisfaction with nurses/ANMs

in Figure 14. Overall, patients were satisfied with the care

at public facilities. The majority of patients were male

they received and, in general, ratings were higher for

caste/scheduled tribe, and nearly one-quarter identified

ing of 10, and the majority rated the facility they attended

ucation (84%), though lower facility levels tended to see

at district hospitals, only 9% rated the facility below a 6;

were under the age of 30.

this proportion was 24%.

higher-level platforms. Very few patients (1%) gave a rat-

(64%). 43% of patients identified as part of a scheduled

Female Male >=40 years 16-39 years Other castes Backwards caste Any schooling

as another backwards caste. Most patients had some ed-

a 6 or 7 (66% of all patients). Among patients seeking care

patients with less education. Nearly half (46%) of patients

among patients seeking care at primary health facilities, Table 14 provides a more in-depth examination of

Travel and wait times

No schooling

patient ratings of facility characteristics and visit expe-

riences. Patients gave considerably low ratings to the

The amount of time patients spend traveling to facili-

Not given all prescribed drugs Given all prescribed drugs Wait time <30 min Wait time >=30 min DH CHC SDH

ties and then waiting for services can substantially affect

facility cleanliness and privacy of facilities with fewer than

were interviewed, we found that travel time to a facility

health centre and up.

shorter travel time for patients seeking care at lower-level

across all platforms, most notably at district hospitals

their care-seeking behaviors. Among the patients who

half of patients satisfied with these at the level of primary

for care (Figure 12) differed by platform with generally

Most patients were unsatisfied with facility cleanliness

facilities than at one higher-level. It is important to note

(72%) and sub-district hospitals (79%).

facilities, not the time needed for round-trip visits. Most

faction with health providers – being respectfully treated

cility for care (Figure 12). 58% of patients who went to

provider, and that provider gave enough time to ask

Three parameters were assessed to document satis-

that patients only reported on the time spent traveling to

Odds Ratio

Dotted vertical line represents an odds ratio of one. Black points represent the reference groups, which all carry an odds ratio of one. Compared to the referent category, significant odds ratios and 95% confidence intervals are represented with blue points and horizontal lines, respectively. Odds ratios that are not significant are represented by green points, and their 95% confidence intervals with a green horizontal line. Any point estimates or confidence intervals with an upper bound above 3 were truncated for ease of interpretation. DH: District hospital; SDH: Sub-district hospital; CHC: Community health centre; PHC: Primary health centre

by the provider, clarity of explanation provided by the

patients had travel times of less than 30 minutes to a fadistrict hospitals travelled fewer than 30 minutes, and

30% travelled between 30 minutes and one hour. At primary health centres these proportions were 78% and 14%,

11 Rao KD, Peters DH, Bandeen-Roche K. Towards patient-centered health services in India—a scale to measure patient perceptions of quality. International Journal for Quality in Health Care. 2006; 18(6):414-421.

respectively. This finding is not unexpected, as these are

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

46,693,763 (18,330,256– 107,593,472)

16,464,210 (4,486,110– 30,161,732)

6,835,128 (1,996,990– 903,975 (65,014– 23,716,390) 1,907,726)

1,823,509 (524,772– 4,818,518)

893,316 (188,576– 2,633,315)

5,140,975 Pharmaceutical expenditure (INR) (1,025,286– 15,160,016)

Inputs

236,159 (37,103– 847,457)

18,598,004 (5,456,885– 43,136,000)

6,500,680 (1,414,770– 3,596,773 (146,435– 13,724,573) 17,549,452)

77,482 (0–625,373)

179 (92–264)

65 (48–90)

18 (6–54)

1 (0–7)

25 (11–40)

8 (3–15)

3 (1–12)

2 (0–3)

29 (14–56)

11 (3–20)

2 (0–9)

0 (0–1)

4 (0–13)

3 (0–5)

2 (0–6)

1 (0–2)

19 (6–37)

12 (5–20)

5 (1–18)

2 (1–4)

37 (6–73)

21 (13–34)

12 (3–25)

1 (0–4)

Outpatient visits

190,976 (43,615– 381,645)

59,692 (30,134– 99,345)

28,329 (9,384– 102,904)

9,572 (257–29,084)

Inpatient visits (excluding deliveries)

30,272 (5,233– 83,418)

16,811 (4,295–53,712)

2,676 (71–14,460)

36 (0–703)

4,117 (1,527–7,170)

2,421 (359–8,084)

583 (33–2,362)

20 (0–348)

21,121 (4,395– 36,801)

9,363 (1,707–18,713)

1,560 (0–11,147)

108 (0–3,047)

Other expenditure (INR) Number of beds Number of doctors Number of nurses Number of ANMs Number of paramedical staff Number of non-medical staff

Outputs

PRIMARY HEALTH CENTRE

Deliveries

DISTRICT HOSPITAL

SUB-DISTRICT HOSPITAL

COMMUNITY HEALTH CENTRE

PRIMARY HEALTH CENTRE

District 1

51,991,672

19,479,492

905,239

10,985,098

District 2

94,958,336

28,882,890

1,121,225

6,953,366

District 3

65,530,600

1,446,575

6,949,017

District 4

55,868,844

915,720

22,873,122

District 5

52,630,144

1,330,357

9,989,852

District 6

44,933,876

1,269,001

14,538,471

District 7

130,038,864

32,412,556

1,646,256

8,019,957

District 8

52,692,340

12,589,253

1,222,105

7,701,607

District 9

85,250,008

23,320,612

1,164,355

13,916,464

Empty cells were either dropped from analysis due to data availability, or there were no facilities to sample of that platform.

Figure 18 Average total and type of expenditure, by platform 2009-2013 DISTRICT HOSPITALS

SUB-DISTRICT HOSPITALS

200

Immunization doses

DISTRICT

300

COMMUNITY HEALTH CENTRE

Expenditure in 100,000 Rupees 100 200

SUB-DISTRICT HOSPITAL

1,000

Personnel expenditure (INR)

DISTRICT HOSPITAL

Table 17 Average annual cost in INR, by platform, last fiscal year. INR denotes Indian Rupees.

Expenditure in 100,000 Rupees 400 600 800

Table 16 Average and range of inputs and outputs, by platform. INR denotes Indian Rupees.

2009

2010

2011

2013

2012

2009

Personnel

2010

2011

2013

2012

Personnel

Pharmaceuticals and consumables

Other

Pharmaceuticals and consumables

Other

Access to to affordable drugs has been interpreted to

questions about health problem or treatment – using a

be part of the right to health. Among 1,161 patients that

levels of satisfaction about respectfulness, clarity, and

trict hospitals to more than 75% of patients at primary

time than those receiving care from nurse and ANMs. This

health centres.

mary health centres, where patients were more satisfied

satisfaction with the medical care they receive. Given

There are many complex factors which affect patient

trend was reversed in community health centres and priwith nurses and ANMs. There is a significant gap in satis-

this, a multivariate logistic regression was conducted in

of patients were satisfied with nurses and ANMs as with

istics were associated with patient satisfaction with both

(Figure 15). This ranged from 55% of patients at sub dis-

drugs during the visit, 715 received all prescribed drugs

PRIMARY HEALTH CENTRES

Expenditure in 100,000 Rupees 5 10 15

tals, patients receiving care from doctors reported higher

as not satisfied. At district hospitals and sub-district hospi-

COMMUNITY HEALTH CENTRES 150

and very good responses combined as satisfied, and rest

were prescribed drugs and attempted to obtain those

Expenditure in 100,000 Rupees 50 100

five-point Likert scale, with the highest ratings of good

medical doctors (Figure 16) and nurses/ANMs (Figure

doctors. Generally, satisfaction was highest at primary

17). For each characteristic – for example, the age or sex

health centres.

order to determine which patient and facility character-

faction at the sub-district hospital level, where near half

2009

2010

2011

2013

2012

2009

Pharmaceuticals and consumables

2010

2011

2013

2012

Personnel

Pharmaceuticals and consumables

Other

ABCE IN ODISHA

in-hand. An efficient health facility uses resources well, producing a high volume of patient visits and services

Community Health Centre

without straining its resources. Conversely, an inefficient health facility is one where the use of resources is

Primary Health Centre

100

3000 2500

2011

2012

2009

2013

2010

cal staff seeing very few patients per day. We present

2011

2012

2013

OP visits per staff by facility OP visits per staff average

technical efficiency analysis for district hospitals, sub-

An ensemble model approach was used to quantify

technical efficiency in health facilities, combining results

of the patient – the odds ratio (OR) is presented. The OR

represents the odds that a patient is satisfied given a par-

from two approaches – the restricted versions of Data

being satisfied in the absence of that characteristic. An

Function (rSDF).12 Based on this analysis, an efficiency

dicates that there are greater odds of being satisfied with

use of its resources. Relating the outputs to inputs, the

ticular characteristic, compared to the odds of the patient

Envelopment Analysis (rDEA) and Stochastic Distance

OR and 95% confidence interval (CI) greater than 1.0 in-

score was estimated for each facility, capturing a facility’s

care as compared to the reference group. An OR and 95%

rDEA and rSDF approaches compute efficiency scores

satisfied with care than the reference group.

ing that a facility achieved the highest level of production

6000

8000

PHC

Visits 4000

Analytical approach

CHC

2000

health centres.

district hospitals, community health centres and primary

Other

3000

Pharmaceuticals and consumables

2000

Personnel

Visits

2010

1000

60 40 Percent of Total Expenditure

2009

not maximized, leaving usable beds empty or medi-

Visits 1500 2000

with which care is delivered by health facilities go hand-

Sub District Hospital

1000

The costs of health service provision and the efficiency

SDH

500

Efficiency and costs

District Hospital

4000

(OR: 0.03, 95% CI: 0.004–0.16).

3000

hospitals had lower satisfaction with nurses and ANMs

Figure 20 Outpatient load per staff by platform

Visits 2000

district hospitals, those who sought care at sub district

1000

1.59–50.79). Compared to patients who sought care at

Figure 19 Average percentage of expenditure type, by platform in 2013

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

2009

2010

2011

2012

2009

2013

2010

2011

2012

OP visits per staff by facility OP visits per staff average

ranging from 0% to 100%, with a score of 100% indicat-

CI below 1.0 indicates that there are lower odds of being

relative to all facilities in that platform.

For example, while the OR for male patients being sat-

This approach assesses the relationship between in-

isfied with care from a doctor is 0.91 (95% CI: 0.65–1.26) as

DH: District hospital; SDH: Sub-district hospital; CHC: Community health centre; PHC: Primary health centre Note: Each line represents an individual facility, with the bolded line depicting the average for the platform. Scales are different for each platform type.

puts and outputs to estimate an efficiency score for each

compared to female patients, it is not statistically different

from an OR of 1.0 (Figure 16). This means that, consider-

facility. Recognizing that each type of input requires a

less satisfied with care from doctors than female patients.

an inpatient visit uses more resources and more com-

are signified by blue points, with blue horizontal bars

visit), we applied weight restrictions to rescale each fa-

statistically significant are represented with green points

of additional weight restrictions is widely used in order

different amount of facility resources (e.g., on average,

ing all other characteristics, male patients are not more or

plex types of equipment and services than an outpatient

In Figures 16 and 17, ORs that are statistically significant

representing their confidence interval. ORs that are not

cility’s mixture of inputs and outputs. The incorporation

and green confidence bars.

to improve the discrimination of the models. Weight re-

slightly lower satisfaction with doctors for patients of

about the importance of individual inputs and outputs, or

strictions are most commonly based upon the judgment

Compared to patients of another group, there was

backwards caste (Figure 16, OR: 0.64, 95% confidence

interval [CI]: 0.45–0.93). Controlling for all other factors,

there was no difference in satisfaction by platform.

12 Di Giorgio L, Flaxman AD, Moses MW, Fullman N, Hanlon M, Conner RO, et al. Efficiency of Health Care Production in Low-Resource Settings: A Monte-Carlo Simulation to Compare the Performance of Data Envelopment Analysis, Stochastic Distance Functions, and an Ensemble Model. PLOS ONE. 2016; 11(2): e0150570.

Longer wait time was associated with higher satisfac-

tion with nurses and ANMs (Figure 17, OR: 8.99, 95% CI:

2013

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Figure 21 Inpatient load per staff by platform

Figure 22 Deliveries per staff by platform DH

200

Deliveries 100 150

2012

2009

2013

2010

CHC

2012

2013

2009

2011

2010

2012

2009

2013

2010

PHC

2011

2012

2013

Deliveries per staff by facility Deliveries per staff average

CHC

PHC

2009

2010

2011

2012

2009

2013

100

Deliveries

Deliveries 40 60

Visits 40

Visits 200

300

400

2011

IP visits per staff by facility IP visits per staff average

2011

IP visits per staff by facility IP visits per staff average

100

2010

500

Deliveries 30 40

Visits 1000

400 Visits 200 0

2009

SDH

250

SDH 1500

600

2010

2011

2012

2013

IP visits per staff by facility IP visits per staff average

2009

2011

2010

2012

2009

2013

2010

2011

2012

DH: District hospital; SDH: Sub-district hospital; CHC: Community health centre; PHC: Primary health centre

Note: Each line represents an individual facility, with the bolded line depicting the average for the platform. Scales are different for each platform type.

Costs of care

reflect cost or price considerations. The resulting ensemble efficiency scores were averaged over five years and between the two input models.

For these models, service provision was categorized

into outpatient visits, inpatient visits, delivery and immuni-

zation. Two input-output specifications were used with the outputs are listed in Table 15. The detailed data utilized

age and range of inputs and outputs for the variables are

Total expenditure, by district and platform, is pre-

trends in average facility spending varied by platform be-

It is important to note that data availability on the in-

outpatient visits per staff, though the ratio ranged greatly.

sented in Table 17. In terms of annual total expenditures,

est at primary health centres.

tween 2009 and 2013 (Figure 18). All platforms recorded

puts and output indicators varied across the facilities and

The average ratio for sub-district hospitals was 1,123 visits

than in 2009, which appeared to be largely driven by in-

with five years of missing data for any input or output vari-

for primary health centres. This gradient differed for inpa-

Figure 19 shows the average composition of expendi-

were smoothed where necessary based on the trends

visits per staff, 342 for sub-district hospitals, 85 for com-

To further illustrate the production of outputs per in-

The range of inpatient visits per staff was low for primary

ture types across platforms for 2013. Notably, community

presented in Table 16.

health centres spent a slightly lower proportion of their

(Figure 20), inpatient visits (Figure 21), deliveries (Figure

22), and immunization doses (Figure 23) per staff are pre-

creased spending on medical supplies and personnel.

for this analysis are documented in the annex. The aver-

total expenditures on personnel than other platforms. The

proportion of expenditure on medical supplies was high-

slightly higher levels of average expenditures in 2013

inputs being different in the two models. The inputs and

2013

Deliveries per staff by facility Deliveries per staff average

sented. District hospitals produced an average of 1,781

platforms, with more non-availability for PHCs. Facilities

per staff, 631 for for community health centres, and 2,007

able were dropped from analysis. In addition, the data

tient visits with district hospitals providing 276 inpatient

seen in inputs or outputs for that facility.

munity health centres, and 15 for primary health centres.

puts â&#x20AC;&#x201C; in this case, staff â&#x20AC;&#x201C; a simple ratio of outpatient visits

health centres, where inpatient visits are rare. Overall, as

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Figure 23 Immunizations per staff per day by platform

Figure 24 Range of efficiency scores across platforms SDH

2010

2011

2012

100 80 2009

2013

2011

2010

CHC

2013

PHC

Doses administered 100 200 300

400

2012

Immunization doses per staff by facility Immunization doses per staff average

2009

100

Doses administered 100 200 300

Doses administered 200 300 400

400

500

Sub District Hospital

Community Health Centre

Primary Health Centre

District Hospital

2009

2010

2011

2012

2009

2013

2011

2010

2012

2013

Immunization doses per staff by facility Immunization doses per staff average

District hospital

Sub-district hospital

Community health centre

Primary health centre

Mean: 74.3

Mean: 62.8

Mean: 57.9

Mean: 46.7

Median: 75.8

Median: 58.8

Median: 57.4

Median: 46.2

IQR: 72.7-84.4

IQR: 56.2-74.3

IQR: 52.4-67.4

IQR: 34.2-58.0

Note: Each circle represents the five-year facility average efficiency score; IQR refers to intra-quartile range.

expected, outpatient visits accounted for the overwhelm-

between the average facility and facilities with the highest

was quite a bit of variation of these ratios within a platform

ingly large majority of the patients seen per staff per day

and over time, however.

across the platforms.

is variation in facility efficiency both between and within

The five-year average efficiency of district hospitals

tres were in the same district as the most-efficient district

ciency scores for all facilities, two main findings emerged.

74%. Sub-district hospitals were between 49% and 80%

2). While one primary health centre in District 6 was 63%

facilities, with 74.3% being highest mean across platforms.

and 80% efficient; 2 facilities were 75% or more efficient.

Given observed levels of facility-based resources

Efficiency results

Fewer deliveries were performed per staff than other

Using the five fiscal years of data to estimate the effi-

services, with an average of 37 deliveries per staff in dis-

trict hospitals, 48 per staff in sub-district hospitals, 23 per

First, efficiency scores were relatively low across all health

staff in community health centres, and three per staff in

primary health centres. For immunization doses, 202 per

staff in district hospitals, 179 per staff in sub-district hos-

Second, the range between the facilities with highest and

health, and 18 per staff in primary health centres. There

suggesting that a substantial performance gap may exist

lowest efficiency scores was quite large within platforms

pitals, 58 doses were administered per staff in community

Efficiency by district is presented in Table 18. There

efficiency scores. Figure 24 depicts this range of facility ef-

ficiency scores across platforms for OD.

districts. Some of the least-efficient primary health cen-

ranged from 47% to 88%, with a platform average of

hospitals and sub district hospitals (for example, District

efficient. Community health centres were between 34%

efficient, another was only 19% efficient.

The range of efficiency scores was widest for primary

(beds and personnel), it would appear that many facilities

health centres, from 17% to 76%, with 21 facilities at less

had the capacity to handle much larger patient volumes

than 50% efficient.

than they reported. Figure 25 displays this gap in poten-

ABCE IN ODISHA

M A I N F I N D I N G S : H E A LT H FA C I L I T Y P R O F I L E S

Table 18 District-wise efficiency scores (%), by platform DISTRICT/ PLATFORM

DISTRICT HOSPITAL 1

COMMUNITY HEALTH CENTRE

SUB DISTRICT HOSPITAL 1

District 1

87.4

74.9

74.3

District 2

87.9

79.8

56.2

District 3*

Figure 25 Observed and estimated additional visits that could be produced given observed facility resources

67.0

65.8

56.3

49.4

46.2

64.0

37.9

77.9

37.6

26.5

17.2

31.0

46.8

72.8

53.0

43.9

39.4

47.2

District 4*

84.4

73.0

56.2

64.9

67.1

60.7

31.5

District 5*

78.7

33.6

80.5

50.2

61.3

44.0

41.0

District 6*

58.9

52.4

60.2

63.2

18.5

34.2

30.1

District 7

75.6

56.2

37.9

52.6

46.2

71.3

75.6

58.0

District 8

75.8

48.6

54.8

67.4

43.4

44.3

51.8

57.0

District 9

72.7

58.8

58.6

41.4

26.0

57.1

30.7

47.1

62.5

58.6

PRIMARY HEALTH CENTRE

58.9

62.0

OUTPATIENT VISITS

INPATIENT VISITS

Outpatient visits

Inpatient visits

District Hospital

Sub District Hospital

Community Health Centre

Primary Health Centre

*There were no SDH facilities in Districts 3, 4, 5, and 6.

50,000

150000 100000 Outpatient visits

Observed

200000

250000

Estimate additional visits

20,000 Inpatient visits

10,000 Observed

30,000

40,000

Estimate additional visits

White cells were either dropped from analysis due to data availability, or there were no more facilities to sample of that platform.

DELIVERIES

IMMUNIZATION DOSES

Immunization Doses

Deliveries

tial efficiency performance across platforms, depicting

health system, such that “significant [human resources for

District Hospital

achieved if every facility in the ABCE sample operated at

services.13 Our results suggest otherwise, as most facilities

Sub District Hospital

Community Health Centre

Primary Health Centre

the possible gains in total service provision that could be

health] will be required to meet the demand” for health

optimal efficiency.

in the ABCE sample had the potential to bolster service

We found that all types of facilities could expand their

production given their reported staffing of skilled person-

outputs substantially given their observed resources.

nel and physical capital.

Based on our analyses, the highest level of care, district

These findings provide a data-driven understanding of

hospitals, had the greatest potential for increasing service

facility capacity and how health facilities have used their

provision without expanding current resources. Overall,

resources in OD at the same time, they are not without

based on our estimation of efficiency, a large portion of

limitations. Efficiency scores quantify the relationship be-

OD health facilities could increase the volume of patients

2,000 Observed

Deliveries

4,000

6,000

measures do not fully explain where inefficiencies orig-

to them.

inate, why a given facility scores higher than another, or

If all facilities were perfectly efficient, many more pa-

what levels of efficiency are truly ideal. It is conceivable

(Figure 25). On average, district hospitals could provide

negative effects on service provision, such as longer wait

tient services could be provided with the same inputs

that always operating at full capacity could actually have

58,812 additional outpatient visits with the same inputs,

times, high rates of staff burnout and turnover, and com-

10,335 additional outpatient visits. Community health

tangible characteristics such as facility management, are

immunization doses with the same inputs if all facilities

ture work should also assess these factors alongside

while primary health centres could see an average of

promised quality of care. These factors, as well as less

centres could administer an average of 1,215 additional

all important drivers of health service provision, and fu-

were efficient.

measures of efficiency.

At the same time, many reports and policy documents

emphasize that pronounced deficiencies in human re-

sources for health exist across India in the public sector

13 Rao M, Rao KD, Kumar AK, Chatterjee M, Sundararaman T. Human resources for health in India. The Lancet. 2011; 377(9765): 587-98.

60,000 40,000 Immunization doses

Observed

Estimate additional deliveries

tween what a facility has and what it produces, but these

seen and services provided with the resources available

20,000

80,000

Estimate additional doses

C O N C L U S I O N S A N D P O L I C Y I M P L I C AT I O N S

Conclusions and policy implications

of essential equipment for NCD services at lower facility

health centres and sub health centres. Similarly, most

levels, including basic items such as glucometer/test

hospitals and community health centres reported having

strips. These findings support the need for immediate ac-

flush toilets, with a scarcity at lower levels. That so many

tion to scale up interventions for chronic diseases through

facilities reported access to essential resources like water,

improved public health and primary health care

sanitation, and electricity likely reflects India’s commit-

systems that are essential for the implementation of

ment10,11 to upgrade all facilities so they meet Indian Public

cost-effective interventions.

o achieve its mission to “expand the reach of

cated that they provided routine delivery care, only 11%

health care and establishing universal health

of district hospitals and no lower level facilities had the

coverage,” India has strived over the past 10 1

years to expand and strengthen the public

sector of health care, with a focus on reaching rural areas.

The country recognizes disparities and has sought to enact policies and implement programs to expand access

for ANC and general surgical services, and in all facil-

health personnel at all levels of the health system, but

levels. In general, district hospitals were well equipped

patterns between facilities. Hospitals employ a large num-

provide these services. These gaps were also evident

in urban areas. In the context of a shortage of qualified

ity types, though they were more pronounced at lower

especially rural areas,

tainable, if the country focuses on rigorously measuring

equipment declined through the levels of the system,

Our findings show that these goals are ambitious but athealth facility performance and costs of services across

and within levels of care, and if it can align the different health system performance.

Facility capacity for service provision

particularly with regard to laboratory equipment and im-

that all facilities are fully equipped to optimally provide

within the health system, and the resources to train them

Chronic diseases (e.g., cardiovascular diseases, men-

ment to urgently address the issues of human resources

which are leading causes of death and disability in India,

ing blocks of the health system, is linked to facility 2

are projected to increase in their contribution to the bur-

capacity to provide individuals with the services they

den of disease during the next 25 years.

need and want. With the appropriate balance of skilled

3,4,5

Much of the

care for chronic diseases and injuries is provided in the

staff and supplies needed to offer both essential and spe-

private sector and can be very expensive. Many NCD-re-

cial health services, a health system has the necessary

lated services, including cardiology, psychiatry, and

foundation to deliver quality, equitable health services.

chemotherapy, are notably lacking at all levels of care.

The availability of a subset of services including immu-

Only 11% of district hospitals provide cardiology services

nization, routine deliveries, obstetrics and gynecology services, and laboratory services was generally high

across facility types in Odisha, reflecting the expansion

of these services throughout the state. However, differences remain between high and lower-level platforms.

Notably, while STI/HIV services were available in most

district hospitals, they were available in only 28% of com-

munity health centres. Moreover, substantial gaps were

service delivery. Few facilities at lower levels reported access to a landline phone, which are often a first port of call

for referrals for further treatment. Compounding this, access to emergency vehicles was also generally low: 97% of the primary health centres had no vehicle available at

all. There is scope, then, to address these gaps in order

to ensure that all patients receive timely emergency and curative care.

are still inadequate. A call has been made to the govern-

Facility production of health services

Overall, the number of outpatient visits by year and

through a comprehensive national policy for human re-

platform saw slight increases over the five years of ob-

sources to achieve universal health care in India. However,

servation. Volume of outpatient visits were considerably

it should be noted that despite the shortfall in human

lower at the lower health facilities. The volume of inpa-

resources, the study findings suggest that sub-optimal ef-

tient visits and deliveries increased over the five years of

ficiency in production of services with the given level of

observation for most platforms. The highest volumes of

human resources.

visits were held by district hospitals, followed by sub-dis-

Infrastructure

trict hospitals. Facility expenditure is dominated by

Adequate operational infrastructure is essential for the

Such gaps in the health system will exacerbate disparities

nity health centres, and almost all primary health centres,

ing to endeavor to eliminate major infectious diseases

ties reported being solely dependent on a generator. This

tal and infant mortality. Furthermore, there is a paucity

for reliable storage of medications, vaccines, and labo-

like tuberculosis, HIV, and malaria or to reduce neona-

Communication is also an important facet of health

care. However, nurses do not have much authority or say

functioning of a facility, which in turn affects the efficiency

by not dealing appropriately with NCDs while continu-

levels of the health system.

care to patients (based on reported staffing). These staff-

11% provide chemotherapy, and 33% provide psychiatry. These services are not available at other facility levels.

cus on making sure that these resources reach the lowest

ber of staff. At the lower, community levels, paramedical

ing patterns are not unexpected, due to the hierarchy of

tal health disorders, diabetes, and cancer) and injuries,

water. This suggests that there should be a sustained fo-

results reveal disparate staffing

limited capacity for imaging services. The availability of

essential services warrants fur ther policy consideration.

Optimal health service delivery, one of the key build-

7,8,9

staff including nurses and ANMs provide the majority of

aging equipment. Closing these gaps and by making sure

dimensions of health service provision to support optimal

of human resources for health. It has a shortage of qual-

full stock of medical supplies and equipment to optimally

with medical and laboratory equipment, though with

centres had functional electricity and only 14% had piped

ified health workers and the workforce is concentrated

to essential and special services for marginalized groups.

Health Standards. However, three-quarters of sub health

Recent studies show that India has a severe shortage

personnel costs – accounting for, on average, at least 60% of total costs.

of service provision. In Odisha, all hospitals and commu-

Efficiency scores reflect the relationship between facil-

ity-based resources and the facility’s total patient volume

had access to functioning electricity and only two facili-

each year. Average efficiency scores by platform ranged

from 46.7% to 74.3%, indicating patient volume could

means a higher quality of service provision, as it allows

substantially increase with the observed levels of resources and expenditure. Within each platform, there is

ratory samples. Access to piped water was more variable

great variation in the efficiency of health facilities between

in these types of facilities, particularly lacking in primary

identified between facilities reporting availability of these

services and having the full capacity to actually deliver

3 GBD 2015 Mortality and Causes of Death Collaborators. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. The Lancet. 2016; 388:1459–1544. 4 Patel V, Chatterji S, Chisholm D, Ebrahim S, Gopalakrishna, G, Mathers C et al. Chronic diseases and injuries in India. The Lancet. 2011; 377: 413-28. 5 GBD 2015 DALYs and HALE Collaborators. Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. The Lancet. 2016 Oct 7; 388:1603–1658.

them. While almost all facilities, across platforms, indi-

1 Planning Commission Government of India. Twelfth Five Year Plan (2012-17). New Delhi, India: Government of India, 2012. 2 World Health Organization (WHO). Everybody’s Business: Strengthening health systems to improve health outcomes: WHO’s Framework for Action. Geneva, Switzerland: WHO, 2007.

and within districts. With this information, we estimated

that facilities could substantially increase the number of

patients seen and services provided each based on their

6 Rao M, Rao KD, Kumar AK, Chatterjee M, Sundararaman T. Human resources for health in India. The Lancet. 2011; 377(9765): 587-98. 7 Planning Commission Government of India. Twelfth Five Year Plan (2012-17). New Delhi, India: Government of India, 2012. 8 Hazarika I. Health Workforce in India: Assessment of Availability, Production and Distribution. WHO South East Asia Journal of Public Health. 2013; 2(2): 106-112. 9 Rao M, Rao KD, Kumar AK, Chatterjee M, Sundararaman T. Human resources for health in India. The Lancet. 2011; 377(9765): 587-98.

observed levels of medical personnel and resources in

10 Planning Commission Government of India. Eleventh Five Year Plan (2007-12). New Delhi, India: Government of India, 2007. 11 Planning Commission Government of India. Twelfth Five Year Plan (2012-17). New Delhi, India: Government of India, 2012.

ABCE IN ODISHA

2013. As India seeks to strengthen public sector care to re-

specific services provided for each visit, they can enable

duce the heavy burden of out-of-pocket expenditures,12,13

a compelling comparison of overall health care expenses

stakeholders may seek to increase efficiency by provid-

across states within India. Future studies should aim to

ing more services while maintaining personnel, capacity

capture information on the quality of services provided,

(beds), and expenditure.

as it is a critical indicator of the likely impact of care on

Further use of these results require considering effi-

patient outcomes.

ciency in the context of several other factors, including

Patient perspectives

quality of care provided, demand for care, and expedi-

Patient satisfaction is an important indicator of pa-

ency with which patients are seen.

The policy implications of these efficiency results are

tient perception of the quality of services provided by

with a few caveats. A given facility’s efficiency score cap-

tients is important for purposes of monitoring, increasing

and facility-based resources, but it does not reflect the

adapting patient-centric services, and for utilization of

provision of services, and demand for the care received

amined patient perspectives at public facilities; a major

are disadvantaged.14 These are all critical components of

both numerous and diverse, and they should be viewed

the healthcare sector.15,16 Evaluation of services by pa-

tures the relationship between observed patient volume

accountability, recognizing good performance and

expediency with which patients are seen, the optimal

services, and compliance to treatment. This report ex-

C O N C L U S I O N S A N D P O L I C Y I M P L I C AT I O N S

captured or collated by disease groups at the facilities. At

patients who received care from nurses and ANMs at

the higher-level facilities, collation of patients seen at the

sub-district hospitals. Holding other factors constant, pa-

facilities was not readily available, and it was not possible

tients who reported to be part of a backwards caste were

to assess the level of duplication of patients across the

less satisfied with their care from doctors.

departments. Furthermore, documentation of patients as

Most patients experienced short travel and wait times.

a new patient or a follow-up patient was neither standard-

Most patients travelled fewer than 30 minutes to receive

care, with patients at lower-level facilities reporting the

ized nor practiced across most health facilities. Therefore,

proportion of patients who had to wait more than 30

visits and not in terms of number of patients.

data interpretation is possible only in terms of number of

shortest travel times. District hospitals had the highest

Data were either incomplete or inaccurate at some fa-

minutes to receive care; the lowest proportion patients

cilities for expenditure, patient-related outputs, and staff

waiting more than 30 minutes were at primary health centres. However only 2% of patients waited more than one

numbers. In general, the expenditure documentation

Finally, nearly 40% of patients at all levels reported be-

various sources for a given facility. For example, it is not

patients may obtain prescribed medications at the time

without procuring relevant data from the facility, a higher

sessed across the various levels of public sector health

and continuity of care.

times from the state. The most limited capacity was to

considered alongside measures of efficiency. On the

significant variance in the multilevel model in both states.

ment of India clearly highlighting the need to increase

and supplies.

provides a data-driven, rather than strictly anecdotal,

ferral hierarchical system to provide continuum of health

ter accountability,20 understanding how patients perceive

potentially expand service provision without necessarily

impact the chain of care at another level.17 Although var-

ing various dimensions of care such as time to receive

and equity in provision of services to serve those who

strength of this study is that patient satisfaction was as-

health service delivery, and they should be thoroughly

care in both the states. The type of platform accounted for The public health system in India was designed as a re-

other hand, quantifying facility-based levels of efficiency

care, and as a consequence of this failure at one level can

understanding of how much OD health facilities could

ious government initiatives have led to improved basic

increasing personnel or bed capacity in parallel.

service delivery at primary care health facilities over the

Costs of care

last few years, still a large number of patients directly visit

Average facility expenditure per year differed sub-

higher-level facilities leading to overcrowding of those

had the most bottlenecks with these data available across

hour to receive care.

possible to document the expenditures at a given facility

ing unable to acquire prescribed drugs. Ensuring that all

level of facility (block level), district health society, and at

of their visit should be a priority, as it facilitates adherence

capture the expenditure on drugs, medical consumables

With the developmental priorities for the govern-

user participation in health care service delivery for bet-

Summary

The ABCE project was designed to provide policymak-

quality of the existing public health services encompass-

ers and funders with new insights into health systems and

medical attention, staff behavior, etc., could contribute to

to drive improvements. We hope these findings will not

zation of the public health system.

also inform broader efforts to mitigate factors that im-

only prove useful to policymaking in the state, but will

developing strategies to improve performance and utili21

pede the equitable access or delivery of health services in

Health information system

stantially across platforms. We were unable to estimate

facilities,18 which impacts quality of care as it stretches fa-

in-patients, deliveries, immunisation, etc.) or by type of

In addition, the persistent shortage of medical staff in

the facilities for the various inputs and outputs. Because

are not readily available at the facilities. Estimating such

these facilities.19

nancial years across the facilities, there are several lessons

across the type of platforms is critical for isolating areas

with the care they received, and ratings and satisfaction

information system, both at the facility-level and at the

take into account a broader set of the state’s facilities,

were not satisfied with the cleanliness at the facility they

capture, data management and use (interpretation or

ture of levels and trends in capacity, efficiency, and cost.

the costs of care by type of services (such as out-patients,

cility resources in terms of both infrastructure and staff.

disease/condition (such as TB, diabetes, etc.) as such data

public facilities only aggravates the crowded condition at

costs of care and identifying differences in patient costs

Findings indicate that patients were generally satisfied

to improve cost-effectiveness and expand less costly ser-

were highest at the highest levels of care. However, many

vices, especially for hard-to-reach populations.

Nevertheless, these results on expenditures offer in-

visited. Additionally, there was low satisfaction among

sights into each state’s health financing landscape, a

key component to health system performance, in terms

15 Mpinga EK, Chastonay P. Satisfaction of patients: a right to health indicator? Health Policy. 2011; 100(2-3):144-150. 16 Baltussen RM, Yé Y, Haddad S, Sauerborn RS. Perceived quality of care of primary health care services in Burkina Faso. Health Policy Plan. 2002; 17: 42-48. 17 National Health Mission, Ministry of Health and Family Welfare, Government of India. Framework for Implementation National Health Mission (2012-2017). New Delhi, India: Government of India, 2012. 18 Bajpai V. The Challenges Confronting Public Hospitals in India, Their Origins, and Possible Solutions. Advances in Public Health 2014; 2014: 27. 19 Rao M, Rao KD, Kumar AK, Chatterjee M, Sundararaman T. Human resources for health in India. The Lancet. 2011; 377(9765): 587-98.

of cost to facilities and service production. While these

costs do not reflect the quality of care received or the

12 Ibid. 13 Kumar AKS, Chen LC, Choudhury M, Ganju S, Mahajan V, Sinha A et al. Financing health care for all: challenges and opportunities. The Lancet. 2011; 377: 668-79. 14 UNICEF. Narrowing the gaps: The power of investing in the poorest children. New York, NY: UNICEF, 2017.

India. It is with this type of information that the individual

building blocks of health system performance, and their

This study was dependent on the data availability at

critical interaction with each other, can be strengthened.

More efforts like the ABCE project in India are needed to

of the vast extent of data that were collected for five fi-

continue many of the position trends highlighted in this

report and overcome the identified gaps. Analyses that

regarding the common bottlenecks within the health

including private facilities, may offer an even clearer pic-

state-level. In general, there is weak staff capacity for data planning) at all levels. No system of regular review of data

Continued monitoring of the strength and efficiency of

ment of service provision was observed.

formance and the equitable provision of cost-effective

service provision is critical for optimal health system per-

at the facility level that could guide planning or improve-

interventions throughout the states and in India.

It is not possible to assess the outputs by disease/

condition other than that for deliveries as data are not

20 Planning Commission, Government of India. Faster, sustainable and more inclusive growth: An approach to the Twelfth Five Year Plan. New Delhi, India: Government of India, 2012. 21 World Health Organization (WHO). Global Health Observatory Data Repository. Geneva, Switzerland: WHO, 2016.

Annex: Facility-specific data utilized for the efficiency analysis. Please note that data may be missing for some years across the facilities based on availability of data. DH: District hospital; SDH: Sub-district hospital; CHC: Community health centre; PHC: Primary health centre

FACILITY INFORMATION

INPUTS (BEDS & STAFF)

OUTPUTS

EXPENDITURE

Beds

Doctors

Nurses

ANMs

Paramed

Nonmed

Outpatient

Inpatient

Births

Vaccinations

Personnel

Medical supplies + pharmaceuticals

232,460

25,381

2,493

20,402

20,381,216

3,355,580

10,580,845

2010

237,407

25,695

2,810

19,481

29,007,412

1,955,791

13,652,204

District hospital (DH)

2011

244,911

26,334

3,121

28,945

33,099,032

2,419,081

15,610,032

District hospital (DH)

2012

247,159

30,995

3,453

36,801

29,288,280

5,279,929

21,151,946

District hospital (DH)

2013

266,506

30,761

3,701

34,538

39,952,540

8,982,308

25,242,155

Sub-district hospital (SDH)

2009

49,939

6,459

359

1,707

8,097,413

982,611

1,421,056

Sub-district hospital (SDH)

2010

47,520

7,960

449

1,890

12,650,227

574,690

1,888,332

Sub-district hospital (SDH)

2011

54,854

8,263

497

2,385

13,723,227

705,609

2,319,907

Sub-district hospital (SDH)

2012

41,525

11,659

523

2,527

13,606,171

1,445,092

2,555,401

Sub-district hospital (SDH)

2013

37,874

12,276

579

2,871

10,957,114

2,177,277

2,586,938

Community health centre (CHC)

2009

53,529

9,145

343

1,296

11,137,281

879,615

2,592,370

Community health centre (CHC)

2010

60,453

9,558

365

1,495

11,017,110

609,354

3,391,296

Community health centre (CHC)

2011

63,799

10,242

400

1,109

11,502,209

746,200

3,315,702

Community health centre (CHC)

2012

59,291

10,761

413

1,862

12,864,023

1,148,748

3,324,856

Community health centre (CHC)

2013

53,919

11,101

427

3,140

14,662,592

1,801,781

4,900,874

Primary health centre (PHC)

2009

4,474

365,680

72,680

27,590

Primary health centre (PHC)

2010

6,132

378,580

50,312

33,108

Primary health centre (PHC)

2011

6,813

417,098

61,651

35,475

District

Platform

Facility

Year

District hospital (DH)

2009

District hospital (DH)

1 1

Other expenditure

Primary health centre (PHC)

2012

9,312

1,136

448,615

146,974

39,328

Primary health centre (PHC)

2013

7,745

1,107

464,174

239,187

42,129

Primary health centre (PHC)

2009

8,900

448,172

72,680

23,410

Primary health centre (PHC)

2010

8,168

620,556

50,312

27,640

Primary health centre (PHC)

2011

7,498

663,308

61,651

29,900

Primary health centre (PHC)

2012

7,533

722,634

146,974

29,650

Primary health centre (PHC)

2013

7,962

772,514

239,187

31,200

Community health centre (CHC)

2009

28,566

377

554

1,996,990

776,745

1,012,385

Community health centre (CHC)

2010

22,064

413

619

2,317,119

500,928

1,307,941

Community health centre (CHC)

2011

19,570

468

104

660

3,420,868

535,995

1,291,117

FACILITY INFORMATION

INPUTS (BEDS & STAFF)

OUTPUTS

EXPENDITURE

District

Platform

Facility

Year

Beds

Doctors

Nurses

ANMs

Paramed

Nonmed

Outpatient

Inpatient

Births

Vaccinations

Personnel

Medical supplies + pharmaceuticals

Community health centre (CHC)

2012

27,768

523

112

698

3,636,305

890,493

1,518,926

Community health centre (CHC)

2013

31,380

668

132

742

3,734,754

1,682,368

1,334,036

Primary health centre (PHC)

2009

6,798

231,900

72,680

75,554

Primary health centre (PHC)

2010

7,854

319,992

50,312

26,561

Primary health centre (PHC)

2011

8,180

431,376

61,651

20,305

Primary health centre (PHC)

2012

8,270

484,248

146,974

110,721

Primary health centre (PHC)

2013

9,545

522,144

239,187

57,734

Primary health centre (PHC)

2009

5,983

137

233

348

747,396

112,323

548,326

Primary health centre (PHC)

2010

6,230

168

257

344

907,904

86,283

625,373

Primary health centre (PHC)

2011

6,482

177

288

752

1,075,500

103,718

598,958

Primary health centre (PHC)

2012

6,623

198

305

724

1,194,384

208,096

335,900

Primary health centre (PHC)

2013

6,744

213

348

786

1,128,780

286,216

531,920

Sub-district hospital (SDH)

2009

56,630

35,372

3,467

7,570

9,816,391

980,295

3,098,908

Sub-district hospital (SDH)

2010

58,793

36,741

3,899

8,942

11,049,308

566,910

3,389,547

Sub-district hospital (SDH)

2011

61,325

38,405

4,345

17,363

12,103,970

647,313

3,838,367

Sub-district hospital (SDH)

2012

64,708

39,995

4,661

16,451

15,785,403

1,439,421

3,923,503

Sub-district hospital (SDH)

2013

66,999

41,678

4,905

18,277

17,072,656

2,169,099

4,450,343

Sub-district hospital (SDH)

2009

37,231

6,151

1,462

9,822

15,548,382

1,044,329

4,273,148

Sub-district hospital (SDH)

2010

38,482

5,314

1,650

11,153

17,278,964

619,170

6,315,663

Sub-district hospital (SDH)

2011

39,543

7,816

2,067

12,713

15,206,549

734,877

6,404,861

Sub-district hospital (SDH)

2012

41,113

5,563

1,728

14,618

17,748,144

1,562,606

8,278,390

Sub-district hospital (SDH)

2013

42,346

5,382

1,470

13,291

20,612,608

2,190,364

8,351,812

District hospital (DH)

2009

217

191,369

34,983

4,993

19,221

45,585,440

5,476,497

12,526,937

District hospital (DH)

2010

217

227,085

37,467

5,307

21,265

64,364,644

3,179,423

13,325,569

District hospital (DH)

2011

217

249,937

39,793

5,765

26,548

71,769,864

5,228,534

14,322,687

District hospital (DH)

2012

217

251,067

40,647

6,123

34,190

78,843,472

11,478,707

20,972,020

District hospital (DH)

2013

217

258,567

40,114

6,579

34,855

86,050,312

15,160,016

26,507,567

Sub-district hospital (SDH)

2009

98,203

53,126

8,084

12,990

9,598,683

2,816,277

6,758,993

Sub-district hospital (SDH)

2010

98,923

53,712

7,851

12,842

14,109,202

1,389,753

7,990,423

Sub-district hospital (SDH)

2011

56,631

35,372

4,382

11,666

14,318,234

1,618,565

8,626,350

Sub-district hospital (SDH)

2012

59,205

36,660

3,055

12,956

16,979,778

3,277,054

9,859,285

Sub-district hospital (SDH)

2013

59,824

37,516

2,950

11,628

17,513,862

4,549,722

10,915,259

Community health centre (CHC)

2009

21,533

1,175

196

3,727,792

602,473

1,472,108

Community health centre (CHC)

2010

21,116

944

201

5,612,762

342,759

1,557,506

Community health centre (CHC)

2011

13,289

529

4,835,867

476,882

1,540,126

Community health centre (CHC)

2012

11,945

523

279

5,011,385

866,836

1,751,842

Community health centre (CHC)

2013

13,740

730

282

6,710,227

1,165,077

1,748,126

Primary health centre (PHC)

2009

9,410

1,328,020

119,549

33,150

Primary health centre (PHC)

2010

7,724

997,244

60,873

37,639

Other expenditure

FACILITY INFORMATION

INPUTS (BEDS & STAFF)

OUTPUTS

EXPENDITURE

District

Platform

Facility

Year

Beds

Doctors

Nurses

ANMs

Paramed

Nonmed

Outpatient

Inpatient

Births

Vaccinations

Personnel

Medical supplies + pharmaceuticals

Primary health centre (PHC)

2011

7,165

1,057,320

75,825

45,885

Primary health centre (PHC)

2012

6,375

1,266,675

178,996

49,026

Primary health centre (PHC)

2013

6,250

1,623,706

201,308

53,980

Primary health centre (PHC)

2009

4,565

1,265,954

119,549

26,120

Primary health centre (PHC)

2010

4,675

1,409,280

60,873

43,333

Primary health centre (PHC)

2011

6,183

1,691,616

75,825

117,951

Primary health centre (PHC)

2012

6,515

1,676,112

178,996

27,406

Primary health centre (PHC)

2013

5,211

1,152,036

201,308

73,610

Community health centre (CHC)

2009

17,901

590

455

888

2,969,621

621,550

1,289,623

Community health centre (CHC)

2010

18,567

614

461

906

3,285,366

391,283

1,435,265

Community health centre (CHC)

2011

19,567

689

529

1,554

4,336,090

496,036

1,778,832

Community health centre (CHC)

2012

20,594

798

614

1,794

4,645,890

878,703

2,373,058

Community health centre (CHC)

2013

22,832

819

630

1,860

4,187,589

1,201,622

2,221,366

Primary health centre (PHC)

2009

3,165

670,959

119,549

47,720

Primary health centre (PHC)

2010

2,485

752,112

60,873

47,371

Primary health centre (PHC)

2011

1,978

321,275

75,825

47,692

Primary health centre (PHC)

2012

1,580

979,944

178,996

64,292

Primary health centre (PHC)

2013

1,230

1,008,989

201,308

66,202

Primary health centre (PHC)

2009

5,121

279,200

119,549

25,790

Primary health centre (PHC)

2010

5,882

299,950

60,873

27,253

Primary health centre (PHC)

2011

4,020

356,400

75,825

24,800

Primary health centre (PHC)

2012

4,033

397,330

178,996

28,720

Primary health centre (PHC)

2013

3,316

426,080

201,308

30,160

Other expenditure

Sub-district hospital (SDH)

2009

67,171

12,033

1,593

6,092

15,996,637

2,801,346

4,232,419

Sub-district hospital (SDH)

2010

61,261

12,066

1,840

5,417

21,001,344

1,370,811

4,995,260

Sub-district hospital (SDH)

2011

71,773

12,856

2,033

6,539

23,774,566

1,620,803

5,870,703

Sub-district hospital (SDH)

2012

55,077

13,986

2,078

8,620

26,322,984

3,291,550

7,607,832

Sub-district hospital (SDH)

2013

67,854

12,958

2,943

8,562

28,405,222

4,591,719

6,624,255

District hospital (DH)

2009

120

71,996

10,069

1,776

4,395

31,740,464

2,499,071

16,475,238

District hospital (DH)

2010

120

70,218

11,491

1,868

5,783

37,394,124

1,058,580

18,744,244

District hospital (DH)

2011

120

72,051

13,156

2,157

8,751

40,051,008

1,958,464

21,040,474

District hospital (DH)

2012

120

86,942

10,053

2,016

7,328

46,366,008

2,827,449

23,741,247

District hospital (DH)

2013

120

77,483

14,679

1,584

8,626

50,650,124

6,057,843

27,048,676

Community health centre (CHC)

2009

21,156

1,559

635

2,181,555

480,916

1,491,330

Community health centre (CHC)

2010

22,588

1,550

783

2,388,811

188,576

1,589,033

Community health centre (CHC)

2011

23,918

1,530

902

2,753,951

398,072

1,800,623

Community health centre (CHC)

2012

21,283

2,011

880

2,130

3,029,110

609,628

1,994,125

Community health centre (CHC)

2013

19,738

1,303

581

2,448

3,017,667

1,214,709

2,156,740

Primary health centre (PHC)

2009

10,120

465,248

171,832

172,008

FACILITY INFORMATION

INPUTS (BEDS & STAFF)

OUTPUTS

EXPENDITURE

District

Platform

Facility

Year

Beds

Doctors

Nurses

ANMs

Paramed

Nonmed

Outpatient

Inpatient

Births

Vaccinations

Personnel

Medical supplies + pharmaceuticals

Primary health centre (PHC)

2010

8,756

691,304

54,593

29,486

Primary health centre (PHC)

2011

8,254

1,287,532

116,912

44,345

Primary health centre (PHC)

2012

7,560

1,045,877

188,439

17,910

Primary health centre (PHC)

2013

8,378

1,907,726

424,476

18,274

Community health centre (CHC)

2009

13,747

356

287

1,307

3,867,479

551,091

4,078,374

Community health centre (CHC)

2010

14,399

477

339

1,462

4,496,634

265,566

3,870,220

Community health centre (CHC)

2011

15,011

598

353

1,901

3,805,079

479,569

2,724,780

Other expenditure

Community health centre (CHC)

2012

15,769

647

361

2,380

5,193,027

716,787

3,370,194

Community health centre (CHC)

2013

17,111

689

369

2,605

5,855,815

1,324,948

3,595,763

Primary health centre (PHC)

2009

5,603

1,146,242

171,832

116,371

Primary health centre (PHC)

2010

5,990

1,570,796

54,593

197,624

Primary health centre (PHC)

2011

6,235

1,125,196

116,912

154,438

Primary health centre (PHC)

2012

6,501

1,095,888

188,439

109,077

Primary health centre (PHC)

2013

6,703

1,349,312

424,476

99,813

Primary health centre (PHC)

2009

4,993

153

887,785

171,832

209,045

Primary health centre (PHC)

2010

5,209

185

968,097

54,593

138,056

Primary health centre (PHC)

2011

5,463

221

1,102,554

116,912

92,992

Primary health centre (PHC)

2012

5,810

235

1,207,782

188,439

81,200

Primary health centre (PHC)

2013

6,014

260

101

1,347,992

424,476

149,900

District hospital (DH)

2009

195

235,557

33,471

4,817

17,965

21,616,296

4,799,810

18,458,532

District hospital (DH)

2010

195

239,105

34,102

3,391

16,402

24,064,234

2,249,916

17,912,278

District hospital (DH)

2011

195

242,953

35,459

7,170

22,069

27,395,404

3,791,772

20,148,177

District hospital (DH)

2012

195

244,685

38,318

6,796

25,874

29,572,288

5,048,000

26,109,228

District hospital (DH)

2013

195

245,980

40,777

6,719

27,836

40,657,256

8,146,164

29,374,860

Community health centre (CHC)

2009

56,392

10,391

1,391

2,353

15,296,180

1,043,350

8,807,269

Community health centre (CHC)

2010

49,570

7,725

727

1,992

17,232,748

477,772

9,142,746

Community health centre (CHC)

2011

55,023

10,692

2,362

2,341

16,816,184

687,063

10,402,219

Community health centre (CHC)

2012

51,448

12,522

2,135

5,348

19,718,674

1,019,526

17,549,452

Community health centre (CHC)

2013

55,590

14,460

2,156

6,356

23,716,390

1,547,615

8,938,002

Primary health centre (PHC)

2009

18,415

806,748

194,791

70,017

Primary health centre (PHC)

2010

21,468

941,976

107,461

151,366

Primary health centre (PHC)

2011

19,921

1,177,511

178,547

28,078

Primary health centre (PHC)

2012

20,051

1,359,013

217,935

54,497

Primary health centre (PHC)

2013

20,409

1,438,336

324,576

38,140

Primary health centre (PHC)

2009

11,961

401,772

194,791

72,006

Primary health centre (PHC)

2010

13,994

554,477

107,461

127,262

Primary health centre (PHC)

2011

13,931

565,738

178,547

154,999

Primary health centre (PHC)

2012

13,876

668,634

217,935

100,516

Primary health centre (PHC)

2013

14,361

747,267

324,576

74,600

FACILITY INFORMATION

INPUTS (BEDS & STAFF)

OUTPUTS

EXPENDITURE

District

Platform

Facility

Year

Beds

Doctors

Nurses

ANMs

Paramed

Nonmed

Outpatient

Inpatient

Births

Vaccinations

Personnel

Medical supplies + pharmaceuticals

Community health centre (CHC)

2009

25,319

2,245

979

4,089,064

982,476

6,734,113

Community health centre (CHC)

2010

22,176

2,791

881

9,875

4,493,081

376,850

7,975,989

Community health centre (CHC)

2011

19,668

2,758

1,811

8,852

4,951,521

727,486

8,925,167

Community health centre (CHC)

2012

21,731

3,260

1,833

10,092

5,646,512

977,726

9,785,209

Community health centre (CHC)

2013

13,941

5,419

1,964

11,147

7,196,972

1,497,133

11,976,731

Primary health centre (PHC)

2009

8,316

179,100

194,791

55,091

Primary health centre (PHC)

2010

13,463

107

187,524

107,461

60,539

Primary health centre (PHC)

2011

14,302

199

212,176

178,547

13,800

Primary health centre (PHC)

2012

9,916

195

227,044

217,935

Primary health centre (PHC)

2013

8,079

137

258,364

324,576

49,367

Primary health centre (PHC)

2009

5,674

369,558

194,791

114,739

Primary health centre (PHC)

2010

5,576

489,708

107,461

25,128

Primary health centre (PHC)

2011

5,373

833,772

178,547

49,638

Primary health centre (PHC)

2012

6,161

793,963

217,935

112,901

Primary health centre (PHC)

2013

3,442

608,643

324,576

47,150

District hospital (DH)

2009

132

230,083

5,233

4,543

7,491

18,330,256

4,064,117

9,595,830

District hospital (DH)

2010

132

243,198

5,298

4,820

13,335

31,249,182

1,567,926

12,645,018

District hospital (DH)

2011

132

253,958

6,591

6,079

17,772

36,911,532

3,393,604

15,107,962

District hospital (DH)

2012

132

274,023

6,270

5,908

24,749

36,153,192

6,056,115

15,363,937

District hospital (DH)

2013

132

281,680

6,567

5,705

31,200

44,745,884

11,467,424

16,498,736

Community health centre (CHC)

2009

13,484

562

305

4,081,347

1,036,892

1,660,908

Community health centre (CHC)

2010

13,424

748

610

4,332,300

515,744

2,754,236

Community health centre (CHC)

2011

10,399

777

528

4,990,428

872,376

2,485,929

Community health centre (CHC)

2012

9,696

1,127

406

5,466,704

1,262,073

1,756,576

Community health centre (CHC)

2013

9,384

1,476

376

351

5,407,355

2,633,315

1,831,135

Primary health centre (PHC)

2009

7,622

834,396

152,441

144,093

Primary health centre (PHC)

2010

12,717

1,006,836

70,501

80,875

Primary health centre (PHC)

2011

13,332

1,151,772

150,821

44,800

Primary health centre (PHC)

2012

13,353

1,297,452

236,611

51,404

Primary health centre (PHC)

2013

17,114

1,625,160

498,644

73,821

Primary health centre (PHC)

2009

12,253

811,609

152,441

52,543

Other expenditure

Primary health centre (PHC)

2010

15,001

852,841

70,501

37,941

Primary health centre (PHC)

2011

12,950

1,058,556

150,821

46,727

Primary health centre (PHC)

2012

13,358

1,286,592

236,611

15,980

Primary health centre (PHC)

2013

12,513

1,397,556

498,644

34,577

Community health centre (CHC)

2009

79,402

7,767

1,591

3,927,298

866,063

2,991,649

Community health centre (CHC)

2010

98,690

9,036

1,500

5,015,579

372,333

3,530,620

Community health centre (CHC)

2011

94,431

8,629

1,560

6,268,702

727,663

5,095,193

Community health centre (CHC)

2012

83,562

7,409

1,440

6,419,453

1,077,681

6,844,761

FACILITY INFORMATION

INPUTS (BEDS & STAFF)

OUTPUTS

EXPENDITURE

District

Platform

Facility

Year

Beds

Doctors

Nurses

ANMs

Paramed

Nonmed

Outpatient

Inpatient

Births

Vaccinations

Personnel

Medical supplies + pharmaceuticals

Community health centre (CHC)

2013

102,904

7,044

1,109

8,117,551

2,368,306

5,188,348

Primary health centre (PHC)

2009

6,496

493,631

152,441

23,120

Primary health centre (PHC)

2010

7,278

626,134

70,501

178,416

Primary health centre (PHC)

2011

8,206

554,077

150,821

31,403

Primary health centre (PHC)

2012

7,452

604,081

236,611

32,125

Primary health centre (PHC)

2013

10,303

705,519

498,644

264,033

Primary health centre (PHC)

2009

9,260

1,001,172

152,441

49,300

Primary health centre (PHC)

2010

11,167

1,134,882

70,501

182,435

Primary health centre (PHC)

2011

12,867

1,319,032

150,821

98,910

Primary health centre (PHC)

2012

10,536

1,367,892

236,611

46,300

Primary health centre (PHC)

2013

10,942

1,479,828

498,644

73,239

District hospital (DH)

2009

188

44,000

9,185

1,640

6,889

19,964,460

2,577,620

5,456,885

District hospital (DH)

2010

188

43,615

16,590

1,527

7,161

31,219,158

1,025,286

5,855,441

District hospital (DH)

2011

188

44,560

22,282

2,535

9,445

32,337,418

1,710,132

8,216,169

District hospital (DH)

2012

188

45,349

21,212

2,784

14,290

39,309,148

3,675,304

12,755,473

District hospital (DH)

2013

188

53,623

22,127

3,031

14,240

42,263,744

6,245,787

12,057,347

Community health centre (CHC)

2009

22,525

568

477

1,865

3,914,966

1,690,487

2,868,115

Community health centre (CHC)

2010

22,929

628

581

1,592

5,437,877

677,710

2,587,749

Community health centre (CHC)

2011

20,113

718

646

1,978

5,450,016

945,827

7,926,897

Community health centre (CHC)

2012

16,965

757

560

1,985

6,267,644

1,841,958

8,635,953

Community health centre (CHC)

2013

17,551

959

475

1,933

14,279,720

2,386,407

5,791,318

Primary health centre (PHC)

2009

7,819

357

1,054,884

250,060

158,795

Primary health centre (PHC)

2010

6,883

377

1,196,820

135,169

51,470

Primary health centre (PHC)

2011

5,922

504

159

389

1,362,130

188,166

124,500

Primary health centre (PHC)

2012

6,312

703

138

253

1,362,958

415,830

56,400

Primary health centre (PHC)

2013

7,388

623

185

1,567,152

651,160

40,107

Primary health centre (PHC)

2012

257

96,909

358,104

5,000

Primary health centre (PHC)

2013

2,996

563,904

588,695

79,356

Community health centre (CHC)

2009

40,371

3,976

813

1,081

6,261,892

1,697,344

4,681,661

Community health centre (CHC)

2010

44,917

4,566

889

1,189

6,075,145

589,796

6,339,096

Community health centre (CHC)

2011

44,696

5,362

1,046

1,972

7,247,859

873,305

6,086,785

Community health centre (CHC)

2012

41,581

5,509

1,069

2,155

8,228,328

1,742,267

6,807,033

Community health centre (CHC)

2013

33,590

4,364

735

2,049

8,658,266

2,297,609

7,095,686

Primary health centre (PHC)

2009

10,205

406,560

218,636

42,264

Primary health centre (PHC)

2010

11,504

494,100

92,009

15,826

Primary health centre (PHC)

2011

10,204

531,696

138,164

141,496

Primary health centre (PHC)

2012

11,804

573,264

358,104

Primary health centre (PHC)

2013

11,215

626,568

588,695

87,726

Primary health centre (PHC)

2009

3,346

584,868

218,636

Other expenditure

FACILITY INFORMATION

INPUTS (BEDS & STAFF)

OUTPUTS

EXPENDITURE

District

Platform

Facility

Year

Beds

Doctors

Nurses

ANMs

Paramed

Nonmed

Outpatient

Inpatient

Births

Vaccinations

Personnel

Medical supplies + pharmaceuticals

Primary health centre (PHC)

2010

4,062

1,169,652

92,009

Primary health centre (PHC)

2011

5,818

1,374,108

138,164

51,933

Primary health centre (PHC)

2012

7,585

1,077,840

358,104

14,674

Primary health centre (PHC)

2013

6,726

1,250,040

588,695

31,615

District hospital (DH)

2009

264

135,557

73,893

5,645

21,273

76,382,984

5,722,171

25,791,347

District hospital (DH)

2010

264

139,105

75,771

5,937

25,509

87,373,216

1,480,650

27,985,115

District hospital (DH)

2011

264

142,953

77,889

6,312

33,949

87,324,864

3,434,612

30,151,885

District hospital (DH)

2012

264

145,980

80,213

6,577

35,796

97,050,960

6,567,482

38,861,496

District hospital (DH)

2013

264

149,673

83,418

6,781

36,341

107,593,472

11,338,076

43,136,000

Sub-district hospital (SDH)

2009

40,890

15,739

2,850

7,792

12,364,230

2,121,115

6,089,657

Sub-district hospital (SDH)

2010

47,630

16,614

3,232

8,477

13,153,408

524,772

6,808,164

Sub-district hospital (SDH)

2011

54,030

15,638

2,800

12,180

13,702,916

1,309,753

7,644,418

Sub-district hospital (SDH)

2012

56,650

14,618

2,163

14,944

15,699,056

2,595,068

8,552,068

Sub-district hospital (SDH)

2013

60,152

17,637

2,355

17,487

20,947,782

4,751,984

10,053,734

Community health centre (CHC)

2009

9,725

1,656

364

2,493

5,588,784

465,991

2,267,701

Community health centre (CHC)

2010

10,438

1,994

454

2,747

6,477,060

190,525

2,416,793

Community health centre (CHC)

2011

9,785

1,920

642

3,649

6,299,968

330,293

2,707,771

Community health centre (CHC)

2012

11,851

1,817

305

4,661

6,956,993

589,319

2,628,177

Community health centre (CHC)

2013

11,927

1,715

645

5,097

8,397,528

1,046,362

2,764,383

Primary health centre (PHC)

2009

10,502

770,342

429,357

38,700

Primary health centre (PHC)

2010

11,569

1,011,984

108,961

41,280

Primary health centre (PHC)

2011

11,346

951,720

257,377

45,759

Primary health centre (PHC)

2012

12,015

1,151,580

505,648

51,059

Other expenditure

Primary health centre (PHC)

2013

10,275

1,378,756

835,450

56,074

Primary health centre (PHC)

2009

10,358

1,202

680,300

434,103

41,720

Primary health centre (PHC)

2010

15,699

1,447

944,950

114,245

44,500

Primary health centre (PHC)

2011

17,615

1,889

1,167,650

264,280

87,600

Primary health centre (PHC)

2012

16,560

2,652

1,179,700

516,365

97,224

Primary health centre (PHC)

2013

13,587

3,047

1,209,850

847,457

95,492

Community health centre (CHC)

2009

14,830

123

2,865,693

506,910

226,530

Community health centre (CHC)

2010

16,593

190

4,333,676

240,990

488,610

Community health centre (CHC)

2011

17,384

653

308

4,798,862

439,139

1,637,673

Community health centre (CHC)

2012

22,939

553

187

552

4,812,879

841,875

1,893,081

Community health centre (CHC)

2013

24,532

666

244

582

4,860,666

1,180,763

1,944,568

Primary health centre (PHC)

2009

24,274

775,041

429,357

47,594

Primary health centre (PHC)

2010

27,288

936,341

108,961

49,322

Primary health centre (PHC)

2011

23,607

1,238,616

257,377

52,616

Primary health centre (PHC)

2012

25,087

1,379,377

505,648

57,054

Primary health centre (PHC)

2013

29,084

1,531,975

835,450

61,382

FACILITY INFORMATION

INPUTS (BEDS & STAFF)

OUTPUTS

EXPENDITURE

District

Platform

Facility

Year

Beds

Doctors

Nurses

ANMs

Paramed

Nonmed

Outpatient

Inpatient

Births

Vaccinations

Personnel

Medical supplies + pharmaceuticals

Primary health centre (PHC)

2009

19,748

1,035,132

429,357

39,760

Primary health centre (PHC)

2010

18,031

1,165,407

108,961

43,240

Primary health centre (PHC)

2011

17,863

1,315,876

257,377

44,830

Primary health centre (PHC)

2012

19,439

1,590,724

505,648

48,375

Primary health centre (PHC)

2013

17,669

1,827,894

835,450

51,486

Sub-district hospital (SDH)

2009

79,644

13,680

2,580

9,538

17,861,420

2,155,179

8,156,726

Sub-district hospital (SDH)

2010

73,339

15,140

2,767

10,206

19,728,322

561,556

8,612,424

Sub-district hospital (SDH)

2011

70,356

17,230

2,953

13,045

19,920,926

1,349,916

9,930,976

Sub-district hospital (SDH)

2012

73,714

18,950

3,108

15,567

25,486,674

2,644,849

11,601,200

Sub-district hospital (SDH)

2013

71,692

20,560

3,301

18,713

28,453,284

4,804,099

13,724,573

Sub-district hospital (SDH)

2009

72,253

15,867

2,776

7,248

19,774,308

2,175,355

6,889,365

Sub-district hospital (SDH)

2010

79,634

18,578

3,030

7,908

23,581,044

579,245

7,907,232

Sub-district hospital (SDH)

2011

83,542

21,478

3,340

10,976

25,755,886

1,347,664

9,590,915

Sub-district hospital (SDH)

2012

87,672

25,550

3,780

12,764

27,156,980

2,641,485

10,896,540

Sub-district hospital (SDH)

2013

99,345

29,113

4,100

14,676

30,161,732

4,818,518

11,601,814

District hospital (DH)

2009

147

104,988

31,545

1,856

15,912

21,206,114

4,678,796

12,695,456

District hospital (DH)

2010

147

108,471

32,961

2,057

15,936

27,052,522

2,740,910

14,271,770

District hospital (DH)

2011

147

101,297

27,104

2,553

21,809

34,112,288

3,674,002

15,618,254

District hospital (DH)

2012

147

110,987

20,173

2,842

23,088

38,431,208

4,022,380

16,683,897

District hospital (DH)

2013

147

122,333

19,314

3,451

25,550

41,779,004

10,544,800

15,950,307

Sub-district hospital (SDH)

2009

30,134

5,748

639

1,989

4,486,110

1,255,375

3,396,365

Sub-district hospital (SDH)

2010

30,875

6,228

750

2,100

5,226,050

744,640

3,556,889

Sub-district hospital (SDH)

2011

31,630

6,729

796

4,502

5,730,351

1,121,889

5,459,937

Sub-district hospital (SDH)

2012

36,636

7,463

1,161

5,265

6,388,049

1,382,783

6,125,109

Sub-district hospital (SDH)

2013

41,932

8,308

1,441

7,273

7,035,460

3,732,502

7,304,759

Community health centre (CHC)

2009

16,586

489

3,466,068

855,888

146,435

Community health centre (CHC)

2010

13,759

452

136

3,671,766

553,948

447,343

Community health centre (CHC)

2011

22,386

651

221

5,050,730

879,099

1,356,460

Community health centre (CHC)

2012

16,539

784

140

396

5,222,720

951,733

1,343,787

Community health centre (CHC)

2013

17,765

884

141

405

6,193,594

1,973,375

1,648,340

Primary health centre (PHC)

2009

8,208

980,358

241,538

57,237

Other expenditure

Primary health centre (PHC)

2010

10,457

988,842

161,137

73,940

Primary health centre (PHC)

2011

10,522

1,227,630

238,235

83,120

Primary health centre (PHC)

2012

10,759

921,740

294,160

94,480

Primary health centre (PHC)

2013

11,893

1,024,592

751,152

101,600

Primary health centre (PHC)

2009

6,685

565,332

241,538

2,518

Primary health centre (PHC)

2010

7,538

770,062

161,137

2,639

Primary health centre (PHC)

2011

8,272

940,638

238,235

2,580

Primary health centre (PHC)

2012

9,608

1,003,278

294,160

3,215

FACILITY INFORMATION

INPUTS (BEDS & STAFF)

OUTPUTS

EXPENDITURE

District

Platform

Facility

Year

Beds

Doctors

Nurses

ANMs

Paramed

Nonmed

Outpatient

Inpatient

Births

Vaccinations

Personnel

Medical supplies + pharmaceuticals

Primary health centre (PHC)

2013

9,491

1,126,290

751,152

3,450

Community health centre (CHC)

2009

20,876

1,246

244

474

6,427,634

796,844

961,010

Community health centre (CHC)

2010

21,779

1,277

291

556

6,681,422

637,155

1,065,262

Community health centre (CHC)

2011

23,257

1,304

335

795

5,853,632

921,211

1,215,938

Community health centre (CHC)

2012

25,905

1,315

339

987

6,164,933

1,070,939

1,320,742

Community health centre (CHC)

2013

26,623

1,331

354

1,017

6,553,931

2,129,288

1,454,836

Primary health centre (PHC)

2009

6,289

104

724,226

271,534

138,192

Primary health centre (PHC)

2010

6,935

420

812,572

199,701

120,283

Primary health centre (PHC)

2011

7,115

511

912,572

283,212

132,115

Primary health centre (PHC)

2012

9,493

526

1,014,036

355,082

110,800

Primary health centre (PHC)

2013

10,529

631

1,135,368

817,048

120,664

Primary health centre (PHC)

2009

8,031

273,192

241,538

3,370

Primary health centre (PHC)

2010

9,206

308,683

161,137

4,008

Primary health centre (PHC)

2011

8,272

528,630

238,235

4,380

Primary health centre (PHC)

2012

9,852

550,950

294,160

5,028

Other expenditure

Primary health centre (PHC)

2013

9,075

578,660

751,152

5,595

District hospital (DH)

2009

254

334,585

26,462

3,668

19,073

44,532,432

7,513,616

11,530,152

District hospital (DH)

2010

254

376,397

27,552

3,818

20,492

40,407,088

2,951,438

15,482,548

District hospital (DH)

2011

254

378,228

26,930

4,343

23,257

63,292,548

3,689,842

16,911,125

District hospital (DH)

2012

254

381,645

31,371

3,866

31,795

74,830,488

8,260,688

21,296,764

District hospital (DH)

2013

254

374,238

32,525

4,351

32,839

79,516,768

11,988,175

24,046,362

Sub-district hospital (SDH)

2009

44,985

7,856

1,773

9,568

13,676,824

1,264,220

5,886,435

Sub-district hospital (SDH)

2010

56,389

7,247

1,940

8,222

15,763,460

534,313

5,736,523

Sub-district hospital (SDH)

2011

52,824

7,407

1,979

9,950

17,746,258

653,944

10,211,064

Sub-district hospital (SDH)

2012

54,519

7,038

2,148

10,829

17,617,330

1,521,839

9,341,558

Sub-district hospital (SDH)

2013

61,441

7,349

2,152

10,494

16,946,628

2,354,966

11,608,678

Community health centre (CHC)

2009

21,659

102

188

7,152,469

512,323

2,783,968

Community health centre (CHC)

2010

25,885

130

7,416,899

266,204

2,909,408

Community health centre (CHC)

2011

23,630

157

243

8,044,800

310,461

3,499,314

Community health centre (CHC)

2012

25,761

124

228

11,724,223

576,962

3,513,083

Community health centre (CHC)

2013

32,922

152

255

11,446,636

919,142

3,861,469

Primary health centre (PHC)

2009

4,424

808,404

95,037

29,488

Primary health centre (PHC)

2010

5,610

787,124

37,103

11,096

Primary health centre (PHC)

2011

4,183

718,259

82,755

218,468

Primary health centre (PHC)

2012

4,012

854,808

217,998

64,444

Primary health centre (PHC)

2013

5,101

1,015,983

335,734

78,143

Primary health centre (PHC)

2010

550

65,014

37,103

Primary health centre (PHC)

2011

16,927

780,168

82,755

Primary health centre (PHC)

2012

23,475

858,348

217,998

48,469

FACILITY INFORMATION

INPUTS (BEDS & STAFF)

OUTPUTS

EXPENDITURE

District

Platform

Facility

Year

Beds

Doctors

Nurses

ANMs

Paramed

Nonmed

Outpatient

Inpatient

Births

Vaccinations

Personnel

Medical supplies + pharmaceuticals

Primary health centre (PHC)

2013

23,611

984,312

335,734

49,810

Community health centre (CHC)

2009

16,432

505

372

744

7,728,433

483,984

2,066,157

Community health centre (CHC)

2010

16,989

707

227

9,011,742

235,255

2,423,115

Community health centre (CHC)

2011

17,048

659

540

114

11,628,898

337,082

3,437,836

Community health centre (CHC)

2012

17,843

859

537

1,195

12,662,487

595,329

3,927,005

Community health centre (CHC)

2013

18,389

909

721

1,830

14,459,652

902,600

4,327,708

Primary health centre (PHC)

2009

7,519

923,659

95,037

86,357

Primary health centre (PHC)

2010

8,285

1,041,480

37,103

78,533

Primary health centre (PHC)

2011

7,841

1,004,904

82,755

42,574

Primary health centre (PHC)

2012

8,399

1,130,001

217,998

50,240

Primary health centre (PHC)

2013

8,748

1,338,762

335,734

52,214

Primary health centre (PHC)

2009

6,487

552,270

95,037

117,870

Primary health centre (PHC)

2010

6,651

905,320

37,103

112,820

Primary health centre (PHC)

2011

8,816

1,155,048

82,755

162,070

Primary health centre (PHC)

2012

8,463

1,264,311

217,998

115,800

Primary health centre (PHC)

2013

8,692

1,532,393

335,734

104,300

Sub-district hospital (SDH)

2009

59,768

4,295

607

3,130

11,337,212

1,211,605

1,414,770

Sub-district hospital (SDH)

2010

68,356

4,762

738

3,665

15,314,672

528,625

2,430,895

Sub-district hospital (SDH)

2011

69,122

5,152

979

5,043

14,396,854

628,810

2,481,882

Sub-district hospital (SDH)

2012

78,699

6,326

1,011

6,006

18,399,512

1,494,601

3,364,763

Sub-district hospital (SDH)

2013

80,422

6,962

1,041

6,511

22,441,786

2,315,078

4,581,017

Other expenditure

A B C E

CCESS, OTTLENECKS, OSTS, AND QUITY

I N ST I T UT E F OR HEA LT H M ET R ICS AND EVA LUATION

PUBLIC HEALTH FOUNDATION OF INDIA

Seattle, WA 98121

Gurugram, National Capital Region 122002

2301 Fifth Ave., Suite 600 USA

Plot 47, Sector 44 India

TE L E PH O N E : +1-206-897-2800

TELEPHONE: +91 124 478 1400

EM A I L : engage@healthdata.org

EMAIL: contact@phfi.org

FA X : +1-206-897-2899 www.healthdata.org

FAX: +91 124 478 1601 www.phfi.org