Evidence map›Paper›PMID 40283786›Full record

ArticleInternational journal of environmental research and public health2025

Linking Household and Service Provisioning Assessments to Estimate a Metric of Effective Health Coverage: A Metric for Monitoring Universal Health Coverage.

Veenapani Rajeev Verma, Shyamkumar Sriram, Umakant Dash

Abstract read
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Article in International journal of environmental research and public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Veenapani Rajeev VermaDepartment of Humanities and Social Sciences, Indian Institute of Technology Madras, Chennai 600036, India.ORCID 0000-0002-4595-900X
Shyamkumar SriramCollege of Health and Public Service, University of North Texas, Denton, TX 76203, USA.ORCID 0000-0003-4906-1405
Umakant DashInstitute of Rural Management Anand, Gujrat 388001, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe framework of measuring effective coverage is conceptually straightforward, yet translation into a single metric is quite intractable. An estimation of a metric linking need, access, utilization, and service quality is imperative for measuring the progress towards Universal Health Coverage. A coverage metric obtained from a household survey alone is not succinct as it only captures the service contact which cannot be considered as actual service delivery as it ignores the comprehensive assessment of provider-client interaction. The study was thus conducted to estimate a one-composite metric of effective coverage by linking varied datasets.

methodsThe study was conducted in a rural, remote, and fragile setting in India. Tools encompassing a household survey, health facility assessment, and patient exit survey were administered to ascertain measures of contact coverage and quality. A gamut of techniques linking the varied surveys were employed such as (a) exact match linking and (b) ecological linking using GIS approaches via administrative boundaries, Euclidean buffers, travel time grid, and Kernel density estimates. A composite metric of effective coverage was estimated using linked datasets, adjusting for structural and process quality estimates. Further, the horizontal inequities in effective coverage were computed using Erreygers' concentration index. The concordance between linkage approaches were examined using Wald tests and Lin's concordance correlation.

resultsA significantly steep decline in measurement estimates was found from crude coverage to effective coverage for an entire slew of linking approaches. The drop was more exacerbated for structural-quality-adjusted measures vis-à-vis process-quality-adjusted measures. Overall, the estimates for effective coverage and inequity-adjusted effective coverage were 36.4% and 33.3%, respectively. The composite metric of effective coverage was lowest for postnatal care (10.1%) and highest for immunization care (78.7%). A significant absolute deflection ranging from -2.1 to -5.5 for structural quality and -1.9 to -8.9 for process quality was exhibited between exact match linking and ecological linking.

conclusionsPoor quality of care was divulged as a major factor of decline in coverage. Policy recommendations such as bolstering the quality via the effective implementation of government flagship programs along with initiatives such as integrated incentive schemes to attract and retain workforce and community-based monitoring are suggested.

Indexed as

Health Services AccessibilityUniversal Health InsuranceFamily CharacteristicsHumansIndiaRural Populationeffective health coveragefragile settinggeospatial linking techniquesinequities in effective coveragemultidimensional composite metricquality of careuniversal health coverage

Identifiers

PMID40283786
PMCPMC12027280

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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.