Evidence map›Paper›PMID 38229095›Full record

ArticleBMC health services research2024

Quality of health service in the local government authorities in Tanzania: a perspective of the healthcare seekers from Dodoma City and Bahi District councils.

Richard F Msacky

Abstract read
In one paragraph

Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
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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

1 author.

Richard F MsackyDepartment of Business Administration, College of Business Education, P.O Box 2077, Dodoma, Tanzania. rimsaki@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImprovement and access to quality healthcare are a global agenda. Sustainable Development Goal (SDG-3) is committed to ensuring good health and well-being of the people by 2030. However, this commitment heavily depends on joint efforts by local authorities and the immediate service providers to communities. This paper is set to inform the status of health service provision in local authorities in Tanzania using the determinants for quality health services in Dodoma City and Bahi District.

methodsA cross-sectional research design was employed to collect data from 400 households in the Local Government Authorities. The five-service quality (SERVQUAL) dimensions of Parasuraman were adopted to gauge the quality of service in public healthcare facilities. Descriptive statistics were used to compute the frequency and mean of the demographic information and the quality of health services, respectively. A binary logistic regression model was used to establish the influence of the demographic dimensions on the quality of health services.

findingsThe findings revealed that quality health services have not been realised for healthcare seekers. Further, the area of residence, education, and occupation are significantly associated with the perceived quality of health service delivery in the Local Government Authorities.

conclusionThe healthcare facilities under the LGAs offer services whose quality is below the healthcare seekers' expectations. The study recommends that the Local Government Authorities in Tanzania strengthen the monitoring and evaluation of health service delivery in public healthcare facilities.

Indexed as

Delivery of Health CareLocal GovernmentCross-Sectional StudiesHealth ServicesHumansTanzaniaHealthcare FacilitiesHealthcare SeekersLocal government authoritiesQualitySERVQUAL Model

Identifiers

PMID38229095
PMCPMC10792885

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.