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Understanding CBHI hospitalisation patterns: a comparison of insured and uninsured women in Gujarat, India

BACKGROUND: Community-based health insurance has been associated with increased hospitalisation in low-income settings, but with limited analysis of the illnesses for which claims are submitted. A review of claims submitted to VimoSEWA, an inpatient insurance scheme in Gujarat, India, found that fev...

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Autores principales: Desai, Sapna, Sinha, Tara, Mahal, Ajay, Cousens, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4114097/
https://www.ncbi.nlm.nih.gov/pubmed/25064209
http://dx.doi.org/10.1186/1472-6963-14-320
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author Desai, Sapna
Sinha, Tara
Mahal, Ajay
Cousens, Simon
author_facet Desai, Sapna
Sinha, Tara
Mahal, Ajay
Cousens, Simon
author_sort Desai, Sapna
collection PubMed
description BACKGROUND: Community-based health insurance has been associated with increased hospitalisation in low-income settings, but with limited analysis of the illnesses for which claims are submitted. A review of claims submitted to VimoSEWA, an inpatient insurance scheme in Gujarat, India, found that fever, diarrhoea and hysterectomy, the latter at a mean age of 37 years, were the leading reasons for claims by adult women. We compared the morbidity, outpatient treatment-seeking and hospitalisation patterns of VimoSEWA-insured women with uninsured women. METHODS: We utilised data from a cross-sectional survey of 1,934 insured and uninsured women in Gujarat, India. Multivariable logistic regression identified predictors of insurance coverage and the association of insurance with hospitalisation. Self-reported data on morbidity, outpatient care and hospitalisation were compared between insured and uninsured women. RESULTS: Age, marital status and occupation of adult women were associated with insurance status. Reported recent morbidity, type of illness and outpatient treatment were similar among insured and uninsured women. Multivariable analysis revealed strong evidence of a higher odds of hospitalisation amongst the insured (OR = 2.7; 95% ci. 1.6, 4.7). The leading reason for hospitalisation for uninsured and insured women was hysterectomy, at a similar mean age of 36, followed by common ailments such as fever and diarrhoea. Insured women appeared to have a higher probability of being hospitalised than uninsured women for all causes, rather than specifically for fever, diarrhoea or hysterectomy. Length of stay was similar while choice of hospital differed between insured and uninsured women. CONCLUSIONS: Despite similar reported morbidity patterns and initial treatment-seeking behaviour, VimoSEWA members were more likely to be hospitalised. The data did not provide strong evidence that inpatient hospitalisation replaced outpatient treatment for common illnesses or that insurance was the primary inducement for hysterectomy in the population. Rather, it appears that VimoSEWA members behaved differently in deciding if, and where, to be hospitalised for any condition. Further research is required to explore this decision-making process and roles, if any, played by adverse selection and moral hazard. Lastly, these hospitalisation patterns raise concerns regarding population health needs and access to quality preventive and outpatient services.
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spelling pubmed-41140972014-07-30 Understanding CBHI hospitalisation patterns: a comparison of insured and uninsured women in Gujarat, India Desai, Sapna Sinha, Tara Mahal, Ajay Cousens, Simon BMC Health Serv Res Research Article BACKGROUND: Community-based health insurance has been associated with increased hospitalisation in low-income settings, but with limited analysis of the illnesses for which claims are submitted. A review of claims submitted to VimoSEWA, an inpatient insurance scheme in Gujarat, India, found that fever, diarrhoea and hysterectomy, the latter at a mean age of 37 years, were the leading reasons for claims by adult women. We compared the morbidity, outpatient treatment-seeking and hospitalisation patterns of VimoSEWA-insured women with uninsured women. METHODS: We utilised data from a cross-sectional survey of 1,934 insured and uninsured women in Gujarat, India. Multivariable logistic regression identified predictors of insurance coverage and the association of insurance with hospitalisation. Self-reported data on morbidity, outpatient care and hospitalisation were compared between insured and uninsured women. RESULTS: Age, marital status and occupation of adult women were associated with insurance status. Reported recent morbidity, type of illness and outpatient treatment were similar among insured and uninsured women. Multivariable analysis revealed strong evidence of a higher odds of hospitalisation amongst the insured (OR = 2.7; 95% ci. 1.6, 4.7). The leading reason for hospitalisation for uninsured and insured women was hysterectomy, at a similar mean age of 36, followed by common ailments such as fever and diarrhoea. Insured women appeared to have a higher probability of being hospitalised than uninsured women for all causes, rather than specifically for fever, diarrhoea or hysterectomy. Length of stay was similar while choice of hospital differed between insured and uninsured women. CONCLUSIONS: Despite similar reported morbidity patterns and initial treatment-seeking behaviour, VimoSEWA members were more likely to be hospitalised. The data did not provide strong evidence that inpatient hospitalisation replaced outpatient treatment for common illnesses or that insurance was the primary inducement for hysterectomy in the population. Rather, it appears that VimoSEWA members behaved differently in deciding if, and where, to be hospitalised for any condition. Further research is required to explore this decision-making process and roles, if any, played by adverse selection and moral hazard. Lastly, these hospitalisation patterns raise concerns regarding population health needs and access to quality preventive and outpatient services. BioMed Central 2014-07-26 /pmc/articles/PMC4114097/ /pubmed/25064209 http://dx.doi.org/10.1186/1472-6963-14-320 Text en Copyright © 2014 Desai et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
spellingShingle Research Article
Desai, Sapna
Sinha, Tara
Mahal, Ajay
Cousens, Simon
Understanding CBHI hospitalisation patterns: a comparison of insured and uninsured women in Gujarat, India
title Understanding CBHI hospitalisation patterns: a comparison of insured and uninsured women in Gujarat, India
title_full Understanding CBHI hospitalisation patterns: a comparison of insured and uninsured women in Gujarat, India
title_fullStr Understanding CBHI hospitalisation patterns: a comparison of insured and uninsured women in Gujarat, India
title_full_unstemmed Understanding CBHI hospitalisation patterns: a comparison of insured and uninsured women in Gujarat, India
title_short Understanding CBHI hospitalisation patterns: a comparison of insured and uninsured women in Gujarat, India
title_sort understanding cbhi hospitalisation patterns: a comparison of insured and uninsured women in gujarat, india
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4114097/
https://www.ncbi.nlm.nih.gov/pubmed/25064209
http://dx.doi.org/10.1186/1472-6963-14-320
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