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An analysis of government-sponsored health insurance enrolment and claims data from Meghalaya: Insights into the provision of health care in North East India

INTRODUCTION: The Megha Health Insurance Scheme (MHIS) was launched in 2013 in the North-East Indian state of Meghalaya to reduce household out-of-pocket expenditure on health and provide access to high-quality essential healthcare. Despite substantial expansion of the MHIS since the scheme’s incept...

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Autores principales: Dutta, Eliza K., Kumar, Sampath, Venkatachalam, Selvaraju, Downey, Laura E., Albert, Sandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9165869/
https://www.ncbi.nlm.nih.gov/pubmed/35657934
http://dx.doi.org/10.1371/journal.pone.0268858
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author Dutta, Eliza K.
Kumar, Sampath
Venkatachalam, Selvaraju
Downey, Laura E.
Albert, Sandra
author_facet Dutta, Eliza K.
Kumar, Sampath
Venkatachalam, Selvaraju
Downey, Laura E.
Albert, Sandra
author_sort Dutta, Eliza K.
collection PubMed
description INTRODUCTION: The Megha Health Insurance Scheme (MHIS) was launched in 2013 in the North-East Indian state of Meghalaya to reduce household out-of-pocket expenditure on health and provide access to high-quality essential healthcare. Despite substantial expansion of the MHIS since the scheme’s inception, there is a lack of comprehensive documentation and evaluation of the scheme’s performance against its Universal Health Care (UHC) objectives. METHODS: We analysed six years of enrolment and claims data (2013–2018) covering three phases of the scheme to understand the pattern of enrolment, utilisation and care provision under the MHIS during this period. De-identified data files included information on age, sex, district of residence, the district of provider hospital, type of hospital, date of admission, status at discharge, claimed category of care, package codes, and amount claimed. Descriptive statistics were generated to investigate key trends in enrolment, service utilisation, and Government health spending under the MHIS. RESULTS: Approximately 55% of the eligible population are currently enrolled in MHIS. Enrolment increased consistently from phase I through III and remained broadly stable across districts, gender, age group and occupation categories, with a small decline in males 19–60 years. Claims were disproportionately skewed towards private provision; 57% of all claims accrued to the 18 empanelled private hospitals and 39% to the 159 public sector facilities. The package ‘General Ward Unspecified’ was responsible for the highest volume of claims and highest financial dispensation across all three phases of the scheme. This likely indicates substantial administrative error and is potentially masking both true burden of disease and accurate financial provision for care under the MHIS. Anti-rabies injections for dog/cat bite contributed to 11% of total claims under MHIS III, and 1.6% of all claims under MHIS II. This warrants investigation to better understand the burden of animal bites on the Meghalayan population and inform the implementation of cost-effective strategies to reduce this burden. CONCLUSIONS: This paper describes the first analysis of health insurance enrolment and claims data in the state of Meghalaya. The analysis has generated an important evidence base to inform future MHIS enrolment and care provision policies as the scheme expands to provide Universal Health Coverage to the state’s entire population.
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spelling pubmed-91658692022-06-05 An analysis of government-sponsored health insurance enrolment and claims data from Meghalaya: Insights into the provision of health care in North East India Dutta, Eliza K. Kumar, Sampath Venkatachalam, Selvaraju Downey, Laura E. Albert, Sandra PLoS One Research Article INTRODUCTION: The Megha Health Insurance Scheme (MHIS) was launched in 2013 in the North-East Indian state of Meghalaya to reduce household out-of-pocket expenditure on health and provide access to high-quality essential healthcare. Despite substantial expansion of the MHIS since the scheme’s inception, there is a lack of comprehensive documentation and evaluation of the scheme’s performance against its Universal Health Care (UHC) objectives. METHODS: We analysed six years of enrolment and claims data (2013–2018) covering three phases of the scheme to understand the pattern of enrolment, utilisation and care provision under the MHIS during this period. De-identified data files included information on age, sex, district of residence, the district of provider hospital, type of hospital, date of admission, status at discharge, claimed category of care, package codes, and amount claimed. Descriptive statistics were generated to investigate key trends in enrolment, service utilisation, and Government health spending under the MHIS. RESULTS: Approximately 55% of the eligible population are currently enrolled in MHIS. Enrolment increased consistently from phase I through III and remained broadly stable across districts, gender, age group and occupation categories, with a small decline in males 19–60 years. Claims were disproportionately skewed towards private provision; 57% of all claims accrued to the 18 empanelled private hospitals and 39% to the 159 public sector facilities. The package ‘General Ward Unspecified’ was responsible for the highest volume of claims and highest financial dispensation across all three phases of the scheme. This likely indicates substantial administrative error and is potentially masking both true burden of disease and accurate financial provision for care under the MHIS. Anti-rabies injections for dog/cat bite contributed to 11% of total claims under MHIS III, and 1.6% of all claims under MHIS II. This warrants investigation to better understand the burden of animal bites on the Meghalayan population and inform the implementation of cost-effective strategies to reduce this burden. CONCLUSIONS: This paper describes the first analysis of health insurance enrolment and claims data in the state of Meghalaya. The analysis has generated an important evidence base to inform future MHIS enrolment and care provision policies as the scheme expands to provide Universal Health Coverage to the state’s entire population. Public Library of Science 2022-06-03 /pmc/articles/PMC9165869/ /pubmed/35657934 http://dx.doi.org/10.1371/journal.pone.0268858 Text en © 2022 Dutta et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Dutta, Eliza K.
Kumar, Sampath
Venkatachalam, Selvaraju
Downey, Laura E.
Albert, Sandra
An analysis of government-sponsored health insurance enrolment and claims data from Meghalaya: Insights into the provision of health care in North East India
title An analysis of government-sponsored health insurance enrolment and claims data from Meghalaya: Insights into the provision of health care in North East India
title_full An analysis of government-sponsored health insurance enrolment and claims data from Meghalaya: Insights into the provision of health care in North East India
title_fullStr An analysis of government-sponsored health insurance enrolment and claims data from Meghalaya: Insights into the provision of health care in North East India
title_full_unstemmed An analysis of government-sponsored health insurance enrolment and claims data from Meghalaya: Insights into the provision of health care in North East India
title_short An analysis of government-sponsored health insurance enrolment and claims data from Meghalaya: Insights into the provision of health care in North East India
title_sort analysis of government-sponsored health insurance enrolment and claims data from meghalaya: insights into the provision of health care in north east india
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9165869/
https://www.ncbi.nlm.nih.gov/pubmed/35657934
http://dx.doi.org/10.1371/journal.pone.0268858
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