There is a large and growing literature on disease and its causes in low- and middle-income countries (LMICs) – not only infectious disease, but also non-communicable diseases. Endless studies are published on disease incidence and prevalence, for example. There is also a substantial literature on policy / health systems, much captured in the Health Systems Evidence database. This deals with topics such as general taxation vs. contributory insurance, financial incentives for providers, and use of private providers to extend coverage.
However, how to provide health services given general policy and a certain profile of disease is less well studied. Issues such as skill mix (e.g. who should do what), distribution of services (e.g. hospital vs. clinic vs. home) and coverage (e.g. how many nurses or clinics are needed per head of population) are less well studied. For example, there have been calls for Africa to increase the capacity of Community Health Workers (CHW) to one million, but no-one knows the optimal mix of CHWs to nurses to medical officers to doctors, for example. Likewise, the mix of outreach services (e.g. CHWs), clinics, pharmacies, private facilities, and traditional healers that can best serve populations is very unclear according to a recent Lancet commission. The situation in slums is positively chaotic. One could sit in an arm chair and propose a service configuration for slum environments of 10,000 people that looks like this:
The role of CHWs could be narrow (vaccination, child malnutrition), intermediate (vaccination, child malnutrition, sexual and reproductive health), or broad (all of the above, plus hypertension, obesity prevention, adherence to treatment, detection of depression, etc.). HIV and TB screening and treatment maintenance could be separate or included in the above, and so on.
Note that decisions about workforce and how and where the workforce is deployed have to be made irrespective of how care is financed, or whether financial or other incentives are used – decisions are still needed about who is to be incentivised to do what. And people do not appear overnight, so training (and the associated costs) must be included in cost and economic models. Of course, the range of possibilities according to per capita wealth in a country is large, but we do not know what good looks like in countries of approximately equal wealth. Here is the rub – it is much easier to study a diseases and its determinants than to study health services. Yet another study to link pollution to illness is easy to write as an applicant and understand as a reviewer. But talk about skill mix and eyes glaze over. Yet there is little point in measuring disease ever more precisely if there is no service to do anything about it.
— Richard Lilford, CLAHRC WM Director
- Mills A. Health Care Systems in Low- and Middle-Income Countries. New Engl J Med. 2014; 370: 552-7.
- McMaster University. Health systems evidence. Hamilton, Canada: McMaster University. 2017.
- McPake B, & Hanson K. Managing the public–private mix to achieve universal health coverage. Lancet. 2016; 388: 622-30.