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Probability and amount of medicines expenditure according to health insurance status in Kenya: A household survey in eight counties

BACKGROUND: National and county governments in Kenya have introduced various health insurance schemes to protect households against financial hardship as a result of large health expenditure. This study examines the relationship between health insurance and medicine expenditure in eight counties in...

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Autores principales: Wirtz, Veronika J., Servan‐Mori, Edson, Mungai, John, Mboya, John, Rockers, Peter C., Onyango, Monica A., Kiragu, Zana Wangari, Laing, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9298347/
https://www.ncbi.nlm.nih.gov/pubmed/34674309
http://dx.doi.org/10.1002/hpm.3368
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author Wirtz, Veronika J.
Servan‐Mori, Edson
Mungai, John
Mboya, John
Rockers, Peter C.
Onyango, Monica A.
Kiragu, Zana Wangari
Laing, Richard
author_facet Wirtz, Veronika J.
Servan‐Mori, Edson
Mungai, John
Mboya, John
Rockers, Peter C.
Onyango, Monica A.
Kiragu, Zana Wangari
Laing, Richard
author_sort Wirtz, Veronika J.
collection PubMed
description BACKGROUND: National and county governments in Kenya have introduced various health insurance schemes to protect households against financial hardship as a result of large health expenditure. This study examines the relationship between health insurance and medicine expenditure in eight counties in Kenya. METHODS: A cross‐sectional study of collected primary data via household survey in eight counties was performed. Three measures of medicine expenditure were analysed: the probability of any out‐of‐pocket expenditure (OOPE) on medicines in the last 4 weeks; amount of OOPE on medicines; and OOPE on medicines as a proportion of total OOPE on health. RESULTS: Out of the 452 individuals, those with health insurance (n = 225) were significantly different from individuals without health insurance (n = 227): overall, they were older, had a higher level of educational attainment and possessed more assets. Adjusting for covariates, individuals with health insurance had a reduced probability of OOPE on medicines (0.40, CI95% 0.197–0.827) and spent proportionally less on medicines out of total health expenditure (0.50, CI95% 0.301–0.926). CONCLUSIONS: Kenya has made great strides to scale up Universal Health Coverage including access to medicines. Prioritising enrollment of low‐income individuals with non‐communicable diseases can accelerate access to medicines and financial protection.
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spelling pubmed-92983472022-07-21 Probability and amount of medicines expenditure according to health insurance status in Kenya: A household survey in eight counties Wirtz, Veronika J. Servan‐Mori, Edson Mungai, John Mboya, John Rockers, Peter C. Onyango, Monica A. Kiragu, Zana Wangari Laing, Richard Int J Health Plann Manage Research Articles BACKGROUND: National and county governments in Kenya have introduced various health insurance schemes to protect households against financial hardship as a result of large health expenditure. This study examines the relationship between health insurance and medicine expenditure in eight counties in Kenya. METHODS: A cross‐sectional study of collected primary data via household survey in eight counties was performed. Three measures of medicine expenditure were analysed: the probability of any out‐of‐pocket expenditure (OOPE) on medicines in the last 4 weeks; amount of OOPE on medicines; and OOPE on medicines as a proportion of total OOPE on health. RESULTS: Out of the 452 individuals, those with health insurance (n = 225) were significantly different from individuals without health insurance (n = 227): overall, they were older, had a higher level of educational attainment and possessed more assets. Adjusting for covariates, individuals with health insurance had a reduced probability of OOPE on medicines (0.40, CI95% 0.197–0.827) and spent proportionally less on medicines out of total health expenditure (0.50, CI95% 0.301–0.926). CONCLUSIONS: Kenya has made great strides to scale up Universal Health Coverage including access to medicines. Prioritising enrollment of low‐income individuals with non‐communicable diseases can accelerate access to medicines and financial protection. John Wiley and Sons Inc. 2021-10-21 2022-03 /pmc/articles/PMC9298347/ /pubmed/34674309 http://dx.doi.org/10.1002/hpm.3368 Text en © 2021 The Authors. The International Journal of Health Planning and Management published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Wirtz, Veronika J.
Servan‐Mori, Edson
Mungai, John
Mboya, John
Rockers, Peter C.
Onyango, Monica A.
Kiragu, Zana Wangari
Laing, Richard
Probability and amount of medicines expenditure according to health insurance status in Kenya: A household survey in eight counties
title Probability and amount of medicines expenditure according to health insurance status in Kenya: A household survey in eight counties
title_full Probability and amount of medicines expenditure according to health insurance status in Kenya: A household survey in eight counties
title_fullStr Probability and amount of medicines expenditure according to health insurance status in Kenya: A household survey in eight counties
title_full_unstemmed Probability and amount of medicines expenditure according to health insurance status in Kenya: A household survey in eight counties
title_short Probability and amount of medicines expenditure according to health insurance status in Kenya: A household survey in eight counties
title_sort probability and amount of medicines expenditure according to health insurance status in kenya: a household survey in eight counties
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9298347/
https://www.ncbi.nlm.nih.gov/pubmed/34674309
http://dx.doi.org/10.1002/hpm.3368
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