A Transparent Universal Health Coverage Index with Decomposition by Socioeconomic Groups: Application in Asian and African Settings

Khan, Jahangir ORCID: https://orcid.org/0000-0002-6151-764X, Ahmed, Sayem ORCID: https://orcid.org/0000-0001-9499-1500, Chen, Tao ORCID: https://orcid.org/0000-0002-5489-6450, Tomeny, Ewan ORCID: https://orcid.org/0000-0003-4547-2389 and Niessen, Louis ORCID: https://orcid.org/0000-0002-8639-5191 (2019) 'A Transparent Universal Health Coverage Index with Decomposition by Socioeconomic Groups: Application in Asian and African Settings'. Applied Health Economics and Health Policy, Vol 17, Issue 3, pp. 399-410.

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Abstract

Background: Health and Wellbeing as one of the Sustainable Development Goals require all countries to achieve Universal Health Coverage (UHC). That is, all people must have access to healthcare when needed at an affordable price. While several indices were developed recently to assess UHC status, these indices appeared to be difficult for practitioners to apply without statistical knowledge.

Objective: This paper presents a transparent and step-by-step practical calculation method of such an index using Excel spreadsheets, applying in some Asian and African countries. We further intend to decompose the contribution of socioeconomic groups to the UHC index values.

Methods: We utilized the well-known UHC illustration (three-dimensional box, showing population coverage, service coverage and financial protection) to calculate the UHC index. We also decomposed the index into socioeconomic groups. For validation, correlation coefficients between our index and other UHC indices were calculated and the relationship of our index with out-of-pocket payments was estimated.

Results: World Bank data from 6 Asian and 15 African countries on health service coverage of people in five socioeconomic quintiles with financial protection were used to calculate our UHC index. Among Asian countries, indices ranged between 26.0% (Nepal) and 58.7% (Kazakhstan), while in African countries indices ranged between 8.9% (Chad) and 55.3% (Namibia). Decomposition of the UHC index showed a higher contribution to the index by richer socioeconomic groups. The correlation coefficients between our estimated UHC index values and those of others ranged between 0.774 and 0.900. Our index reduced by 1.4 percent in response to a one percent increase in OOP payments.

Conclusions: This spreadsheet approach for calculating the UHC index appeared to be useful, where the interrelation of UHC dimensions was easily observed. Decomposition of the index could be useful for policy-makers to identify the sub-populations and health services with need for further interventions towards UHC achievement.

Keywords: Africa, Asia, decomposition of UHC index, Econometric models, Out-of-pocket payments, Universal health coverage, UHC index

Item Type:	Article
Subjects:	W General Medicine. Health Professions > Health Services. Patients and Patient Advocacy > W 84 Health services. Delivery of health care WA Public Health > WA 30 Socioeconomic factors in public health (General) WA Public Health > Health Problems of Special Population Groups > WA 395 Health in developing countries WA Public Health > Health Administration and Organization > WA 525 General works
Faculty: Department:	Clinical Sciences & International Health > Clinical Sciences Department
Digital Object Identifer (DOI):	https://doi.org/10.1007/s40258-019-00464-9
Depositing User:	Stacy Murtagh
Date Deposited:	19 Mar 2019 10:53
Last Modified:	16 Feb 2020 02:02
URI:	https://archive.lstmed.ac.uk/id/eprint/10110

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