Evidence map›Paper›PMID 40240982›Full record

ArticleBMC primary care2025

Development and implementation of a digital clinical decision support system to increase the quality of primary healthcare delivery in a refugee setting in Chad.

B Matthys, N Monnier, M Ngaradoumadji, Y Toubangue, P Delcroix, M Pereira, T Schmitz, J Armour-Marshall, M Zahorka, K Sugimoto and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC primary care, 2025. 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. Review
  2. Review
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

14 authors.

B MatthysSwiss Tropical and Public Health Institute, Allschwil, Switzerland. barbara.matthys@swisstph.ch.
N MonnierSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
M NgaradoumadjiCentre de Support en Santé Internationale, N'Djamena, Chad.
Y ToubangueCentre de Support en Santé Internationale, N'Djamena, Chad.
P DelcroixSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
M PereiraSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
T SchmitzSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
J Armour-MarshallLewisham and Greenwich NHS Trust, London, UK.
M ZahorkaSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
K SugimotoCantonal Hospital Winterthur, Winterthur, Switzerland.
M LéchenneSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
D RevaultSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
K WyssSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
A MontolnanSwiss Tropical and Public Health Institute, Allschwil, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital clinical decision support systems (CDSS) enhance the quality of primary healthcare service delivery for vulnerable populations in resource-limited settings. This improvement occurs by strengthening healthcare providers' clinical skills and enabling them to operate more independently while adhering to standard treatment guidelines. From January 2019 to June 2023, we developed and implemented a digital, tablet-based CDSS for children aged 2-59 months. The phases of development, validation, and implementation, as well as lessons learnt and bottlenecks requiring attention, are analysed.

methodsThe project was carried out in three primary healthcare facilities within a health district in southern Chad, covering a population of 48,000, which includes a significant number of refugees from the Central African Republic. The intended end users were nurses, nurse assistants, and midwives, with supervision provided by health district teams.

resultsThe CDSS, based on the WHO's Integrated Management of Childhood Illness (IMCI) and national guidelines, was tailored to the context of available resources and epidemiological patterns. From the outset, the active involvement of a diverse group of local, national, and international technical stakeholders (clinicians, information and communication technology (ICT) specialists, health workers, and district health authorities) facilitated mutual knowledge sharing and product co-creation processes. The CDSS was adapted to the local context, which enhanced local ownership. However, its complexity requires significant effort from clinicians and ICT specialists for development and validation. Additionally, health centres must rely on a technical infrastructure (electricity, internet connection, and server solutions).

conclusionsFrom the outset, a participatory approach involving key stakeholders from the local to the national level of the health system significantly contributed to the successful development and implementation of the CDSS. The sustainability of such an intervention necessitates ongoing long-term commitment. This includes establishing and maintaining the infrastructure, ensuring continuous human resources and technical expertise for implementation and quality assurance, and updating content to reflect advancements in clinical medicine.

Indexed as

Decision Support Systems, ClinicalPrimary Health CareQuality of Health CareRefugeesChadChild, PreschoolHumansInfantChadClinical decision support system (CDSS)Integrated management of childhood illnesses (IMCI)Primary healthcareRefugeesResource-constrained settings

Identifiers

PMID40240982
PMCPMC12004631

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.