Evidence map›Paper›PMID 36997953›Full record

ArticleBMC health services research2023

Investigating rapid diagnostic testing in Kenya's health system, 2018-2020: validating non-reporting in routine data using a health facility service assessment survey.

Angela K Moturi, Bibian N Robert, Felix Bahati, Peter M Macharia, Emelda A Okiro

Abstract read
In one paragraph

Article in BMC health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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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

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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

5 authors.

Angela K Moturi *Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya. amoturi@kemri-wellcome.org.
Bibian N Robert *Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.
Felix BahatiHealth Services Research Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.
Peter M MachariaPopulation Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.
Emelda A OkiroPopulation Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.

Funding

Gates Foundation INV-033803Wellcome Trust 201866Wellcome Trust 201866/Z/16/ZWellcome Trust 203077Wellcome Trust 212176Wellcome Trust 224272
6 · The paper itself

Abstract

backgroundUnderstanding the availability of rapid diagnostic tests (RDTs) is essential for attaining universal health care and reducing health inequalities. Although routine data helps measure RDT coverage and health access gaps, many healthcare facilities fail to report their monthly diagnostic test data to routine health systems, impacting routine data quality. This study sought to understand whether non-reporting by facilities is due to a lack of diagnostic and/or service provision capacity by triangulating routine and health service assessment survey data in Kenya.

methodsRoutine facility-level data on RDT administration were sourced from the Kenya health information system for the years 2018-2020. Data on diagnostic capacity (RDT availability) and service provision (screening, diagnosis, and treatment) were obtained from a national health facility assessment conducted in 2018. The two sources were linked and compared obtaining information on 10 RDTs from both sources. The study then assessed reporting in the routine system among facilities with (i) diagnostic capacity only, (ii) both confirmed diagnostic capacity and service provision and (iii) without diagnostic capacity. Analyses were conducted nationally, disaggregated by RDT, facility level and ownership.

resultsTwenty-one per cent (2821) of all facilities expected to report routine diagnostic data in Kenya were included in the triangulation. Most (86%) were primary-level facilities under public ownership (70%). Overall, survey response rates on diagnostic capacity were high (> 70%). Malaria and HIV had the highest response rate (> 96%) and the broadest coverage in diagnostic capacity across facilities (> 76%). Reporting among facilities with diagnostic capacity varied by test, with HIV and malaria having the lowest reporting rates, 58% and 52%, respectively, while the rest ranged between 69% and 85%. Among facilities with both service provision and diagnostic capacity, reporting ranged between 52% and 83% across tests. Public and secondary facilities had the highest reporting rates across all tests. A small proportion of health facilities without diagnostic capacity submitted testing reports in 2018, most of which were primary facilities.

conclusionNon-reporting in routine health systems is not always due to a lack of capacity. Further analyses are required to inform other drivers of non-reporting to ensure reliable routine health data.

Indexed as

HIV InfectionsMalariaDiagnostic Tests, RoutineHealth FacilitiesHealth ServicesHumansKenyaRapid Diagnostic TestsHealth facility surveyKenyaRapid diagnostic testRoutine dataTriangulation

Identifiers

PMID36997953
PMCPMC10061357

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