Evidence map›Paper›PMID 40615862›Full record

ArticleBMC medical informatics and decision making2025

medAL-suite: A software solution for creating and deploying complex clinical decision support algorithms.

Ludovico Gennaro Cobuccio, Vincent Faivre, Rainer Tan, Alan Vonlanthen, Fenella Beynon, Emmanuel Barchichat, Alain Fresco, Quentin Girard, Sinan Ucak, Sylvain Schaufelberger and 12 more

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

22 authors.

Ludovico Gennaro Cobuccio *Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Vincent Faivre *Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Rainer TanCentre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Alan VonlanthenCentre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Fenella BeynonSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
Emmanuel BarchichatWavemind, Lausanne, Switzerland.
Alain FrescoWavemind, Lausanne, Switzerland.
Quentin GirardWavemind, Lausanne, Switzerland.
Sinan UcakWavemind, Lausanne, Switzerland.
Sylvain SchaufelbergerCentre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Ibrahim Evans MtebeneIfakara Health Institute, Dar Es Salaam, Tanzania.
Peter AgreaNational Institute for Medical Research, Mbeya Medical Research Center, Mbeya, Tanzania.
Emmanuel KalisaSwiss Tropical and Public Health Institute, Kigali, Rwanda.
Gillian A LevineSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
Martin NorrisSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
Sabine RenggliIfakara Health Institute, Dar Es Salaam, Tanzania.
Alix MiautonCentre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Lisa CleveleySwiss Tropical and Public Health Institute, Allschwil, Switzerland.
Kristina KeitelSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
Julien ThabardCentre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Valérie D'AcremontCentre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Alexandra V KulinkinaSwiss Tropical and Public Health Institute, Allschwil, Switzerland. alexandra.kulinkina@swisstph.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSub-optimal healthcare quality in low-resource settings is attributed in part to poor adherence to clinical guidelines. Clinical decision support systems (CDSS) help to integrate guideline-based algorithms into logical workflows and improve adherence to evidence-based recommendations, and hence quality of care. However, the process of translating paper-based guidelines into electronic algorithmic formats is often complex, inefficient, expensive, and error-prone due to reliance on advanced software development skills and clinical knowledge.

methodsIn response to these challenges, we developed open-source software called the Medical Algorithm Suite (medAL-suite), consisting of four components, with a primary goal of increasing efficiency, accuracy, and transparency of CDSS creation by giving experienced clinicians, rather than software developers, greater control over the process. At the heart of the software suite is the medAL-creator that allows clinicians to design algorithms using a code-free drag-and-drop interface. Algorithms are subsequently automatically deployed in medAL-reader to service level clinicians in health facilities. CDSS implementers use medAL-data and medAL-hub to manage configuration, versioning, and deployment.

resultsSince its development, the medAL-suite has been used to digitalize complex primary care guidelines and deployed in large-scale clinical studies in Tanzania, Rwanda, Kenya, Senegal, and India, leading to notable outcomes such as the reduction of inappropriate antibiotic prescriptions and improvement in care quality. Over 300,000 pediatric outpatient consultations have been completed in Rwanda and Tanzania to date using the digital algorithm. DISCUSSION: The medAL-suite focused on democratized development, process-centric design, point-of-care utility, touch-screen interface, low cost, and low power consumption to contribute to sustainable digital systems in low-resource settings. Important future developments and adaptations as the software evolves should emphasize interoperability and scalability, primarily via integrating CDSS functionality into electronic medical records for a streamlined user experience that supports improved service quality at the point-of-care. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

AlgorithmsDecision Support Systems, ClinicalSoftwareHumansAlgorithmCDSSClinical decision supportClinical guidelinesDigital health

Identifiers

PMID40615862
PMCPMC12226914

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.