How often do BoP health care providers follow established treatment protocols? How much training do these providers have? Do trained providers reliably provide better care than untrained ones?
Jishnu Das, Senior Economist in the Development Research Group at The World Bank, recently explored these questions in an illuminating study on primary care provider quality in India, published in Health Affairs.
In Part 2 of his interview with CHMI's Rose Reis, Das talks about the limitations of existing data on BoP health care quality, the lessons of the study, how they apply to India and beyond. (You can read Part 1 of their interview here.)
RR: You wrote that in India, little information is available on the practices of private providers, the largest sector providing primary care in resource poor settings. Do other countries have better information about the quality of health care delivered by private providers?
JD: I don't think that this is a problem only in India. There have been some excellent studies in a number of countries that have focused on specific dimensions of private sector practice in smaller samples, and our current study builds on some of the insights from this wider literature.
Moving forward, I think that our understanding of the sector could be improved through better data on the overall number and distribution of private sector providers and by a general method of measuring quality.
For instance, wide variation in quality in the private sector implies that there are both very good and very bad private sector providers. How the sample is drawn can completely change the results, and without a wider informational base, it becomes difficult to say how the specific sampling affected the conclusion of the study.
Similarly, studies of prescriptions in the private sector will typically show that patients are frequently given unnecessary or even harmful medications, but without a comparative group from, say, the public sector, it is difficult to draw firm conclusions on the origins of poor prescription practices. Are results very different in the public sector? Is there a difference by the training of the provider? These are key questions that will allow us to eventually parse out the "deep determinants" of provider behavior in low-income countries.
Partly because of the difficulty of collecting these data, systematic gaps remain in our understanding of the private sector, and particularly among providers without formal training. In many low-income countries we do not have credible estimates of the number of health care providers in an average village--once you count the untrained providers in the private sector.
An excellent systematic review by Berendes and others in PLoS Medicine on quality of care found only two studies on informal sector providers--which could not be included because they did not meet the minimal criteria for inclusion. More comparative research on the private sector that allows us to assess the care that patients receive from different kinds of providers is key to diagnosing the underlying problems.
RR: What should be done about the issues raised in your study?
JD: One major conclusion from this study is that widespread assumptions regarding the quality of care among untrained providers and among providers in the private and public sector may not be accurate.
Although our study is limited to two locations, in both urban Delhi (one of India's richest states) and in rural Madhya Pradesh (one of India's poorest states) we find no correlation between case-loads and quality or equipment and quality, and only small impacts of training. This has important implications for policy.
For instance, one natural question for policy makers is why people use informal sector providers. Answers typically range from familiarity with such providers in the target population to their links to the community. Our study suggests a simple alternative: people use informal sector providers because they may provide better care than alternative sources.
My hope is that the study results are sufficiently important that they lead us to rethink our assumptions on the links between qualifications and quality, and the ability of poor people to make accurate judgments regarding the quality of medical services they access.
Look, I don't think that there is a magic wand that can improve quality of care for the poor. But equally, I do believe that as governments, as members of civil society and as donors, researchers and practitioners, we should be trying our hardest to do so. And I know that there are many fantastic initiatives that are currently underway.
This study helps by providing a method to assess the impact of these initiatives on quality, and therefore creating a feedback loop, leading to evidence-based policy. Particularly for donors and researchers, one major step forward could be the development of a consensus on the measurement of quality, and an acknowledgment that the absence of evidence should not become fertile ground for speculation.
At the end of the day, if this study can do a couple of things, I would wish for nothing more. The first is that faced by blanket statements regarding the quality of care among one set of providers or another, we should step back and ask: Is there clear evidence based on a representative sampling scheme and (something like) a standardized-patient methodology that allows us to make these statements? The second is to start a broader conversation on whether the method proposed here could be brought into mainstream quality measurement and institutionalized in a number of countries.
I am confident that doing so would radically alter our understanding of how health markets function, and open up important policy alternatives in the future.
Below: A short video showing three doctor-patient interactions in New Delhi, India:
This post was also published on NextBillion Health Care. Part 1 was published last week on both CHMI and NextBillion