Evidence map›Paper›PMID 29995899›Full record

ArticlePloS one2018

The impact of community-based health insurance on the utilization of medically trained healthcare providers among informal workers in Bangladesh.

Sayem Ahmed, Abdur Razzaque Sarker, Marufa Sultana, Sanchita Chakrovorty, Mohammad Wahid Ahmed, Farzana Dorin, Andrew J Mirelman, Ziaul Islam, Mohammad Hafizur Rahman, Louis W Niessen and 2 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 3 pooled it
14.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 3 syntheses or guidelines pooled it, 70 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 7 institutions in 5 countries.

Sayem AhmedHealth Economics and Financing Research Group, Universal health Coverage, Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.ORCID 0000-0001-9499-1500
Abdur Razzaque SarkerHealth Economics and Financing Research Group, Universal health Coverage, Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
Marufa SultanaHealth Economics and Financing Research Group, Universal health Coverage, Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
Sanchita ChakrovortyHealth Economics and Financing Research Group, Universal health Coverage, Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
Mohammad Wahid AhmedHealth Economics and Financing Research Group, Universal health Coverage, Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
Farzana DorinHealth Economics and Financing Research Group, Universal health Coverage, Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
Andrew J MirelmanCentre for Health Economics, University of York, York, United Kingdom.
Ziaul IslamHealth Economics and Financing Research Group, Universal health Coverage, Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
Mohammad Hafizur RahmanHealth Economics Unit, Ministry of Health and family Welfare, Dhaka, Bangladesh.
Louis W NiessenDepartment of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
Clas RehnbergHealth Economics and Policy Research Group, Department of Learning, Informatics, Management and Ethics (LIME), Karolinska Institutet, Stockholm, Sweden.
Jahangir A M KhanHealth Economics and Financing Research Group, Universal health Coverage, Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
International Centre for Diarrhoeal Disease Research · BDLiverpool School of Tropical Medicine · GBDeakin University · AUKarolinska Institutet · SEMinistry of Health and Family Welfare · BDUniversity of Strathclyde · GBUniversity of York · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We aimed to estimate the impact of a Community-Based Health Insurance (CBHI) scheme on utilization of healthcare from medically trained providers (MTP) by informal workers. A quasi-experimental study was conducted where insured households were included in the intervention group and uninsured households in comparison group. In total 1,292 (646 insured and 646 uninsured) households were surveyed from Chandpur district comprising urban and rural areas after 1 year period of CBHI introduction. Matching of the characteristics of insured and uninsured groups was performed using a propensity score matching approach to minimize the observed baseline differences among the groups. Multilevel logistic regression model, with adjustment for individual and household characteristics was used for estimating association between healthcare utilization from the MTP and insurance enrolment. The utilization of healthcare from MTP was significantly higher in the insured group (50.7%) compared to the uninsured group (39.4%). The regression analysis demonstrated that the CBHI beneficiaries were 2.111 (95% CI: 1.458-3.079) times more likely to utilize healthcare from MTP.CBHI scheme increases the utilization of MTP among informal workers. Ensuring such healthcare for these workers and their dependents is a challenge in many low and middle income countries. The implementation and scale-up of CBHI schemes have the potential to address this challenge of universal health coverage.

Indexed as

Community NetworksHealth PersonnelInsurance, HealthUniversal Health InsuranceBangladeshFemaleHumansMaleMedically UninsuredPublic Health

Identifiers

PMID29995899
PMCPMC6040718
OpenAlexW2880576664

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.