Jahangir A M Khan1,2,3, Sayem Ahmed4,5,6, Tao Chen4, Ewan M Tomeny4, Louis W Niessen4,7. 1. Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK. Jahangir.khan@lstmed.ac.uk. 2. Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Solna Campus, 171 77, Stockholm, Sweden. Jahangir.khan@lstmed.ac.uk. 3. James P Grant School of Public Health, Brac University, 68, Shahid Tajuddin Ahmed Sharani, Mohakhali, Dhaka, 1212, Bangladesh. Jahangir.khan@lstmed.ac.uk. 4. Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK. 5. Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Solna Campus, 171 77, Stockholm, Sweden. 6. Health Systems and Population Studies Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), 68, Shahid Tajuddin Ahmed Sharani, Mohakhali, Dhaka, 1212, Bangladesh. 7. Department of International Health, Johns Hopkins SPH, Baltimore, MD, USA.
Abstract
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.
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.
Authors: Maya Jane Bates; Miriam R P Gordon; Stephen B Gordon; Ewan M Tomeny; Adamson S Muula; Helena Davies; Claire Morris; Gerald Manthalu; Eve Namisango; Leo Masamba; Marc Y R Henrion; Peter MacPherson; S Bertel Squire; Louis W Niessen Journal: Lancet Glob Health Date: 2021-10-29 Impact factor: 38.927