Evidence map›Paper›PMID 30426889›Full record

ArticleGlobal health action2018

Assessing geographical inequity in availability of hospital services under the state-funded universal health insurance scheme in Chhattisgarh state, India, using a composite vulnerability index.

Sulakshana Nandi, Helen Schneider, Samir Garg

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Article in Global health action, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
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14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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  14. Does the Distribution of Empanelled Hospitals have an Impact on the Utilization of Services under State Insurance Scheme?Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine
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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Sulakshana Nandia School of Public Health , University of the Western Cape , Bellville , South Africa.ORCID 0000-0002-4366-4566
Helen Schneiderc School of Public Health, UWC/MRC Health Services to Systems Unit , University of the Western Cape , Bellville , South Africa.
Samir Gargd State Health Resource Centre , Chhattisgarh , Raipur , India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCountries are increasingly adopting health insurance schemes for achieving Universal Health Coverage. India's state-funded health insurance scheme covers hospital care provided by 'empanelled' private and public hospitals.

objectiveThis paper assesses geographical equity in availability of hospital services under the universal health insurance scheme in Chhattisgarh state.

methodsThe study makes use of district data from the insurance scheme and government surveys. Selected socio-economic indicators are combined to form a composite vulnerability index, which is used to rank and group the state's 27 districts into tertiles, named as highest, middle and lowest vulnerability districts (HVDs, MVDs, LVDs). Indicators of hospital service availability under the scheme - insurance coverage, number of empanelled private/public hospitals, numbers and amounts of claims - are compared across districts and tertiles. Two measures of inequality, difference and ratio, are used to compare availability between tertiles.

resultsThe study finds that there is a geographical pattern to vulnerability in Chhattisgarh state. Vulnerability increases with distance from the state's centre towards the periphery. The highest vulnerability districts have the highest insurance coverage, but the lowest availability of empanelled hospitals (3.4 hospitals per 100,000 enrolled in HVDs, vs 8.2/100,000 enrolled in LVDs). While public sector hospitals are distributed equally, the distribution of private hospitals across tertiles is highly unequal, with higher availability in LVDs. The number of claims (per 100,000 enrolled) in the HVDs is 3.5-times less than that in the LVDs. The claim amounts show a similar pattern.

conclusionsAlthough insurance coverage is higher in the more vulnerable districts, availability of hospital services is inversely proportional to vulnerability and, therefore, the need for these services. Equitable enrolment in health insurance schemes does not automatically translate into equitable access to healthcare, which is also dependent on availability and specific dynamics of service provision under the scheme.

Indexed as

Vulnerable PopulationsHealthcare DisparitiesHealth Services AccessibilityHealth Services ResearchHospitals, PrivateHospitals, PublicHumansIndiaUniversal Health Insuranceavailability of health servicesHealth equityhealth insuranceuniversal health coveragevulnerable populations

Identifiers

PMID30426889
PMCPMC6237177

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.