Evidence map›Paper›PMID 32566223›Full record

ArticleArchives of public health = Archives belges de sante publique2020

Implementing electronic decision-support tools to strengthen healthcare network data-driven decision-making.

Diego Rios-Zertuche, Alvaro Gonzalez-Marmol, Francisco Millán-Velasco, Karla Schwarzbauer, Ignez Tristao

Open access · goldAbstract read
In one paragraph

Article in Archives of public health = Archives belges de sante publique, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.9field-weighted citation impact, top 10% 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

4 citing papers in PubMed, 16 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

5 authors at 3 institutions in 3 countries.

Diego Rios-ZertucheSalud Mesoamerica Initiative, Inter-American Development Bank, 1300 New York Ave NW, SE0631, Washington, DC 20577 USA.
Alvaro Gonzalez-MarmolSalud Mesoamerica Initiative, Inter-American Development Bank, 1300 New York Ave NW, SE0631, Washington, DC 20577 USA.
Francisco Millán-VelascoInstituto de Salud del Estado de Chiapas, Tuxtla Gutiérrez, Mexico.
Karla SchwarzbauerSalud Mesoamerica Initiative, Inter-American Development Bank, Tegucigalpa, Honduras.
Ignez TristaoInter-American Development Bank, Buenos Aires, Argentina.
Inter-American Development Bank · USCentral Bank of Argentina · ARInstituto de Salud del Estado de México · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMinistries of health in low- and middle-income countries often lack timely quality data for data-driven decision making in healthcare networks. We describe the design and implementation of decision-support electronic tools by the Ministry of Health of the State of Chiapas, in Mexico, as part of Salud Mesoamerica Initiative.

methodsThree electronic decision-support tools were designed through an iterative process focused on streamlined implementation: 1) to collect and report health facility data at health facilities; 2) to compile and analyze data at health district and central level; and, 3) to support stratified sampling of health facilities. Data was collected for five composite indicators measuring availability of equipment, medicines, and supplies for maternal and child health. Quality Assurance Teams collected data, evaluated results and supported quality improvement. Data was also analyzed at the central level and health districts for decision-making.

resultsData from 300 health facilities in four health districts was collected and analyzed (November 2014-June 2015). The first wave revealed gaps on availability of equipment and supplies in more than half of health facilities. Electronic tools provided the ministry of health officers new ways to visualize data, identify patterns and make hypothesis on root-causes. Between the first and second measurement, the number of missing items decreased, and actions performed by quality improvement teams became more proactive. In the final measurement, 89.7-100% of all health facilities achieved all the required items for each indicator.

conclusionsOur experience could help guide others seeking to implement electronic decision-support tools in low- and middle-income countries. Electronic decision-support tools supported data-driven decision-making by identifying gaps on heatmaps and graphs at the health facility, subdistrict, district or state level. Through a rapid improvement process, the Ministry of Health met targets of externally verified indicators. Using available information technology resources facilitated prompt implementation and adoption of technology.

Indexed as

Child healthData-drivenData visualizationDecision-makingDecision-support toolsEvidence-basedHealth information systemsLow-income countriesMaternal healthMiddle-income countries

Identifiers

PMID32566223
PMCPMC7301503
OpenAlexW3036730073

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.