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Weight of Risk Factors for Adjusting Capitation in Primary Health Care: A Systematic Review

Background: Capitation payment is the best-known strategy for paying providers in primary health care. Since health care needs and personal characteristics play an essential role in health care utilization and resource spending, there is a growing tendency on risk adjustment models among health rese...

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Autores principales: Khezri, Ali, Mahboub-ahari, Alireza, Tabrizi, Jafar Sadegh, Nosratnejad, Shirin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Iran University of Medical Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386772/
https://www.ncbi.nlm.nih.gov/pubmed/35999922
http://dx.doi.org/10.47176/mjiri.36.2
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author Khezri, Ali
Mahboub-ahari, Alireza
Tabrizi, Jafar Sadegh
Nosratnejad, Shirin
author_facet Khezri, Ali
Mahboub-ahari, Alireza
Tabrizi, Jafar Sadegh
Nosratnejad, Shirin
author_sort Khezri, Ali
collection PubMed
description Background: Capitation payment is the best-known strategy for paying providers in primary health care. Since health care needs and personal characteristics play an essential role in health care utilization and resource spending, there is a growing tendency on risk adjustment models among health researchers. The objective of this systematic review was to examine the weights used for risk adjustment in primary health care capitation payment. Methods: We systematically searched Scopus, ProQuest, Web of Science, and PubMed in March 2018. Two authors independently apprised the included articles and they also evaluated, identified, and categorized different factors on capitation payments mentioned in the included studies. Results: A total of 742 studies were identified and 12 were included in the systematic review after the screening process. Risk factors for capitation adjustment included age, gender, and income with the weighted average being 1.76 and 1.03, respectively. Moreover, the weighted average disease incidence adjusted clinical groups (ACGs), diagnostic cost groups (DCGs), principal in patient diagnostic cost groups (PIP-DCGs), and hierarchical coexisting conditions (HCCs) were reported as 1.31, 24.7-.99, 10.4-.65, and 11.7-1.01, respectively. Conclusion: In low-income countries, the most effective factors used in capitation adjustment are age and sex. Moreover, the most applied factor in high-income countries is adjusted clinical groups, and income factors can have a better impact on the reduction of costs in low-income countries. Each country can select its most efficient factors based on the weight of the factor, income level, and geographical condition.
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spelling pubmed-93867722022-08-22 Weight of Risk Factors for Adjusting Capitation in Primary Health Care: A Systematic Review Khezri, Ali Mahboub-ahari, Alireza Tabrizi, Jafar Sadegh Nosratnejad, Shirin Med J Islam Repub Iran Systematic Review Article Background: Capitation payment is the best-known strategy for paying providers in primary health care. Since health care needs and personal characteristics play an essential role in health care utilization and resource spending, there is a growing tendency on risk adjustment models among health researchers. The objective of this systematic review was to examine the weights used for risk adjustment in primary health care capitation payment. Methods: We systematically searched Scopus, ProQuest, Web of Science, and PubMed in March 2018. Two authors independently apprised the included articles and they also evaluated, identified, and categorized different factors on capitation payments mentioned in the included studies. Results: A total of 742 studies were identified and 12 were included in the systematic review after the screening process. Risk factors for capitation adjustment included age, gender, and income with the weighted average being 1.76 and 1.03, respectively. Moreover, the weighted average disease incidence adjusted clinical groups (ACGs), diagnostic cost groups (DCGs), principal in patient diagnostic cost groups (PIP-DCGs), and hierarchical coexisting conditions (HCCs) were reported as 1.31, 24.7-.99, 10.4-.65, and 11.7-1.01, respectively. Conclusion: In low-income countries, the most effective factors used in capitation adjustment are age and sex. Moreover, the most applied factor in high-income countries is adjusted clinical groups, and income factors can have a better impact on the reduction of costs in low-income countries. Each country can select its most efficient factors based on the weight of the factor, income level, and geographical condition. Iran University of Medical Sciences 2022-02-02 /pmc/articles/PMC9386772/ /pubmed/35999922 http://dx.doi.org/10.47176/mjiri.36.2 Text en © 2022 Iran University of Medical Sciences https://creativecommons.org/licenses/by-nc-sa/1.0/This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial-ShareAlike 1.0 License (CC BY-NC-SA 1.0), which allows users to read, copy, distribute and make derivative works for non-commercial purposes from the material, as long as the author of the original work is cited properly.
spellingShingle Systematic Review Article
Khezri, Ali
Mahboub-ahari, Alireza
Tabrizi, Jafar Sadegh
Nosratnejad, Shirin
Weight of Risk Factors for Adjusting Capitation in Primary Health Care: A Systematic Review
title Weight of Risk Factors for Adjusting Capitation in Primary Health Care: A Systematic Review
title_full Weight of Risk Factors for Adjusting Capitation in Primary Health Care: A Systematic Review
title_fullStr Weight of Risk Factors for Adjusting Capitation in Primary Health Care: A Systematic Review
title_full_unstemmed Weight of Risk Factors for Adjusting Capitation in Primary Health Care: A Systematic Review
title_short Weight of Risk Factors for Adjusting Capitation in Primary Health Care: A Systematic Review
title_sort weight of risk factors for adjusting capitation in primary health care: a systematic review
topic Systematic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386772/
https://www.ncbi.nlm.nih.gov/pubmed/35999922
http://dx.doi.org/10.47176/mjiri.36.2
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