Evidence map›Paper›PMID 27591202›Full record

SynthesisHealth policy and planning2016

District decision-making for health in low-income settings: a systematic literature review.

Deepthi Wickremasinghe, Iram Ejaz Hashmi, Joanna Schellenberg, Bilal Iqbal Avan

Registry-linked trialOpen access · bronzeAbstract readSystematic Review
In one paragraph

Synthesis in Health policy and planning, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05310682 (Data-Informed Platform for Health), which is not on this map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 1 pooled it
20.3field-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.

NCT05310682 naunknown statusnot on this mapstarted 2020, after this paper: background citation

Data-Informed Platform for Health (DIPH)

TypeinterventionalSponsorLondon School of Hygiene and Tropical MedicineRan2020 to 2022Enrolled24ConditionsBehaviorArmsData informed Platfrom for health
3 · Its place in the literature

Who cites it

48 citing papers in PubMed, 1 synthesis or guideline pooled it, 134 citations in OpenAlex.

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  19. Routine use of DHIS2 data: a scoping review.BMC health services research · 2022
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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

4 authors at 1 institution in 1 country.

Deepthi WickremasingheIDEAS Project, London School of Hygiene & Tropical Medicine, UK bilal.avan@lshtm.ac.uk.
Iram Ejaz HashmiIDEAS Project, London School of Hygiene & Tropical Medicine, UK bilal.avan@lshtm.ac.uk.
Joanna SchellenbergIDEAS Project, London School of Hygiene & Tropical Medicine, UK bilal.avan@lshtm.ac.uk.
Bilal Iqbal AvanIDEAS Project, London School of Hygiene & Tropical Medicine, UK bilal.avan@lshtm.ac.uk.
London School of Hygiene & Tropical Medicine · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health management information systems (HMIS) produce large amounts of data about health service provision and population health, and provide opportunities for data-based decision-making in decentralized health systems. Yet the data are little-used locally. A well-defined approach to district-level decision-making using health data would help better meet the needs of the local population. In this second of four papers on district decision-making for health in low-income settings, our aim was to explore ways in which district administrators and health managers in low- and lower-middle-income countries use health data to make decisions, to describe the decision-making tools they used and identify challenges encountered when using these tools. A systematic literature review, following PRISMA guidelines, was undertaken. Experts were consulted about key sources of information. A search strategy was developed for 14 online databases of peer reviewed and grey literature. The resources were screened independently by two reviewers using pre-defined inclusion criteria. The 14 papers included were assessed for the quality of reported evidence and a descriptive evidence synthesis of the review findings was undertaken. We found 12 examples of tools to assist district-level decision-making, all of which included two key stages-identification of priorities, and development of an action plan to address them. Of those tools with more steps, four included steps to review or monitor the action plan agreed, suggesting the use of HMIS data. In eight papers HMIS data were used for prioritization. Challenges to decision-making processes fell into three main categories: the availability and quality of health and health facility data; human dynamics and financial constraints. Our findings suggest that evidence is available about a limited range of processes that include the use of data for decision-making at district level. Standardization and pre-testing in diverse settings would increase the potential that these tools could be used more widely.

Indexed as

Decision MakingAdministrative PersonnelDelivery of Health CareDeveloping CountriesEthiopiaEvidence-Based PracticeHealth PrioritiesHealth ResourcesHumansIndiaNigeriaPovertydecentralizationDecision-makingevidence-based policyhealth planninghealth systemslow-income

Identifiers

PMID27591202
PMCPMC5009221
OpenAlexW2515027529

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.