A transparent Universal Health Coverage index with decomposition by socioeconomic groups: application in Asian and African settings

Khan, J. A.M., Ahmed, S. , Chen, T., Tomeny, E. M. and Niessen, L. W. (2019) A transparent Universal Health Coverage index with decomposition by socioeconomic groups: application in Asian and African settings. Applied Health Economics and Health Policy, 17(3), pp. 399-410. (doi: 10.1007/s40258-019-00464-9) (PMID:30880358)

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Background: Health and wellbeing as one of the Sustainable Development Goals requires 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, applied to some Asian and African countries. We also decompose the contribution of socioeconomic groups to 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 broke down 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 (OOP) payments was estimated. Results: World Bank data from six 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 the 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% in response to a 1% 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 subpopulations and health services with need for further interventions towards UHC achievement.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Ahmed, Dr Sayem
Authors: Khan, J. A.M., Ahmed, S., Chen, T., Tomeny, E. M., and Niessen, L. W.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Health Economics and Health Technology Assessment
Journal Name:Applied Health Economics and Health Policy
ISSN (Online):1179-1896
ISBN:11791896 11755652
Published Online:16 February 2019

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