On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Meghan Kumar who has a PhD from the University of Liverpool. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.
Economic evaluation and decision making for quality improvement in complex community health systems
Miriam Taegtmeyer, Jason Madan, Edwine Barasa
What does ‘quality improvement’ mean in the context of community health?
Quality improvement or QI is a structured management process that involves identifying quality problems, using root cause analysis to identify why a problem is occurring, coming up with change plans to address those problems, and using local data to track whether the change plans are really making change happen! It’s no different at the community level than any other level of the health system or even beyond health. A nuance, though, is that at the community level many core work activities are related to preventing disease or health promotion, so they are more indirectly linked to health outcomes than curative clinical care. We are also helping expand the data available for QI beyond clinical processes and technical quality to include patient experience data on quality through a community follow up tool.
You describe your work as ‘mixed methods’; what did this mean for your study?
My interests lie firmly across boundaries, whether methods, disciplines, or even implementation and research! This has always been the space I am most comfortable in – the title of my thesis refers to complex systems, and the idea that a linear theory of change would well reflect implementation in a system seems an over-simplification. The three studies published from my work include a costing and budget impact analysis, a cost-effectiveness decision model, and a multi-country qualitative study with decision-makers at different levels. I’ll be part of a session at iHEA that we just found out was accepted on Advancing Mixed-Methods Approaches for Considering Multiple Decision Criteria and Health System Constraints in Health Care Evaluation, which might be interesting to readers with whom this resonates.
How did you determine cost-effectiveness in your case study?
Although the rest of the thesis was a multi-country piece, for the cost-effectiveness study I focused on a case study in one country, Kenya. This was in recognition of the differences between decision space in each country and policy priorities, as well as the varying responsibilities of community health workers. It helps that I have lived in Kenya for most of the last 10 years, so know the system and the stakeholders well. There was also some ongoing work happening in Kenya by my wider research team to quantify the impact of the QI intervention using lot quality assurance sampling methodology (publication in development). This meant that we had impact data including controls. Using data from the costing study, we developed a decision tree that looked at the behaviour of pregnant women in the intervention and control sub-counties. We used sub-county level in recognition of the role of leadership and a culture of quality in the successful implementation of community QI. The cost-effectiveness analysis included effectiveness data from both infant and maternal outcomes. One key observation was that although we only quantified impact in one patient pathway, community health QI is likely to act across multiple health areas and therefore impact will likely be greater than what is directly quantified here.
To what extent are your findings relevant for other settings?
That is always the million-dollar question! And perhaps one that often gets ignored when we say “data from low- and middle-income countries (LMICs)” or “data from sub-Saharan Africa” as though these are homogenous. Individual countries themselves are so heterogeneous (see excellent work on this from KEMRI-Wellcome Trust colleagues, such as Peter Macharia). Are these data generalisable and/or transferable? What’s the difference and what does that mean for how we design future studies? In the thesis, I wrote:
“The health economics of high-income countries is insufficient for direct transferability to LMIC settings. Particularly, the focus on ever-more sophisticated modelling approaches relies on high-quality, complete data sets that are rarely available for LMIC settings. Some approaches that might improve the use of economic evidence are:
- Inclusion of mechanism in the publication of economic evaluation results; recognition of (at least) the direction of change that might occur if the prerequisites for that/those mechanism(s) are not met
- Acknowledgement of the multiplicity of decision makers in presentation of cost-effectiveness results and the potential impact, perhaps as a type of sensitivity analysis
- More research into disinvestment and ways to communicate trade-offs to constituent to facilitate evidence use by elected officials
- Default use of the societal perspective to more accurately reflect the costs that are often shifted to individuals through out-of-pocket payment and use of low/unpaid CTC providers”
I am working with some of my new colleagues at the London School of Hygiene and Tropical Medicine to further our definition and improve understanding and methods of transferability for economic evaluation research in LMICs. Watch this space!
What does your research tell us about how decision-makers use economic evidence?
What we verified in the multi-country qualitative component of my research was that there were two major barriers to the use of economic evidence in domestic decision-making. The first refers to the above question (i.e. perception by decision-makers that findings from other settings did not apply to theirs) and the other was the capacity to interpret and use this evidence. Economic evidence was more often considered by the global decision-makers we interviewed in their priority setting. The rhetoric around community health continues to rightly focus on access, but there is an under-valuing of quality as a component of meaningful coverage, and this is rarely mentioned as a funding priority in community health. One thing that I’d like to spend more time understanding is when and how disinvestment happens if an intervention or approach is found to be less cost-effective than an alternative. This remains politically challenging and underlines the importance of political economy in these decisions.
How would you like to see your research used?
I see several applications of my research – most directly, in national planning around UHC and scaling up meaningful coverage. Note that ‘meaningful’ reappears here – quality is what all health systems researchers need to be thinking about, both in terms of evaluating equity in access to services as well as whether interventions that yield benefits in a trial setting are actually getting those in the real world implementation. Community health systems will absolutely be a part of UHC when attained and have a major role to play at the interface of community and health systems to include social determinants of health in assessing risk. My work has provided further evidence that efficient, equitable health systems need to more completely integrate community health workers into primary health care delivery in a meaningful way.
Thanks for the chance to ‘chat’ about this. I would be happy to speak further with interested readers!