Table 6: Hypotheses and assumptions for the initial Kuunika theory of change

Table 6: Hypotheses and assumptions for the initial Kuunika theory of change

Hypotheses and Assumptions

1. HMIS systems management procedures, including availability of material resources for

HMIS and supervision for HMIS within the past six months, are associated with better data quality.

2. There are important planning and service delivery advantages to using routine/ administrative data (instead of survey data) – e.g. the power to describe all administrative levels in the country, near-real time accessibility, and reduced cost.

3. A lack of trust in the quality of admin data discourages its use

4. Data Users will have the cognitive skills to transform ‘data’ into ‘knowledge’ 5. The degree of organisational and political decentralisation can affect use of evidence in decision making.

6. Individual beliefs, attitudes and motivations to use data and evidence are connected to pre-existing norms and values that prevail across organisations or wider society

7. There are formal and informal ‘policy/practice making cycles’: the formal policy making cycle uses peer reviewed research evidence and debate to inform collective understanding and promote step changes in policy; the informal policy cycle is more messy and opportunistic

8. Beliefs about what counts as ‘good’ evidence may result in data being discounted; certain evidence may be viewed as ‘unacceptable’ in particular contexts and so ignored.

9. Policy making [and the development of practice] is often messy and opportunistic, using pragmatic decisions [based on evidence emerging at the local level] by a range of actors.

10. HMIS data can directly inform practice and policy change or shift understanding and awareness of an issue.

11. Lack of trust in admin data leads to [costly, possibly contradictory] parallel M&E systems (e.g. for specific service areas or health conditions) to be established and used.

12. Organisational tools and systems designed to promote use of data in policy and practice (such as guidelines, templates and procedures for incorporating evidence into programme design) can motivate individuals to use evidence more in their day-to-day work.

13. Claims of ‘lack of time’ may be linked to organisational values and norms around data use – whether individuals are given the permission and space in their working days to spend time finding and using data

14. Data (& evidence) use is influenced by the type and nature of relationships between [individuals or institutions]

15. Hierarchical management of information or organisational silos can limit access to data and its use.. divisions of responsibilities and ‘institutional silos’ can also limit consideration of evidence.

16. Civil society may play a number of different roles in relation to data/evidence use, including putting pressure on government to use evidence, building momentum behind ideas, and bringing together different forms of knowledge.

17. Policy/practice development processes involve ‘a disorderly set of interconnections and back-and-forth’ between different groups 18. Individuals are empowered through access to data

19. Interoperability is technically and organisationally feasible 20. Clinicians do not follow patient management guidelines due to lack of time, heavy workload

21. Running two parallel systems (EMR + paper) makes health workers consider EMRs redundant and cumbersome

Source

Ahanhanzo YG, et al. 2014

Hung, Y.W. et. al. 2020 (updated)

Mutale W, 2013; Mate K, et al. 2009

Reynolds, M. 2016

Liverani et al. 2013; Beck et al. 2005

BCURE Evaluation Evidence Review p37

Jones, H., 2009; Nutley et al. 2007

BCURE Evaluation Evidence p43

Jones, H., 2009.

Nutley et al. 2007

Sucich, K. 2019 (updated)

Yost et al. 2014; Nutley et al. 2013; Peirson et al. 2012; Dobbins, et al. 2009

Orton et al. 2011; Armstrong et al. 2013

Walter et al. 2005

Trostle et al. 1999

BCURE Evaluation Evidence Review p 51

Weiss, C. H. 1979

BCURE Evaluation Evidence Review

Evaluation Team

Barth, J. H. et al. 2016

Gadabu O. 2010

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