medAL-suite: A software solution for creating and deploying complex clinical decision support algorithms
Abstract Background Sub-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 recommendat...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-025-03077-6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849334725137661952 |
|---|---|
| author | Ludovico Gennaro Cobuccio Vincent Faivre Rainer Tan Alan Vonlanthen Fenella Beynon Emmanuel Barchichat Alain Fresco Quentin Girard Sinan Ucak Sylvain Schaufelberger Ibrahim Evans Mtebene Peter Agrea Emmanuel Kalisa Gillian A. Levine Martin Norris Sabine Renggli Alix Miauton Lisa Cleveley Kristina Keitel Julien Thabard Valérie D’Acremont Alexandra V. Kulinkina |
| author_facet | Ludovico Gennaro Cobuccio Vincent Faivre Rainer Tan Alan Vonlanthen Fenella Beynon Emmanuel Barchichat Alain Fresco Quentin Girard Sinan Ucak Sylvain Schaufelberger Ibrahim Evans Mtebene Peter Agrea Emmanuel Kalisa Gillian A. Levine Martin Norris Sabine Renggli Alix Miauton Lisa Cleveley Kristina Keitel Julien Thabard Valérie D’Acremont Alexandra V. Kulinkina |
| author_sort | Ludovico Gennaro Cobuccio |
| collection | DOAJ |
| description | Abstract Background Sub-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. Methods In 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. Results Since 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. |
| format | Article |
| id | doaj-art-dfa474081d3a47b3b56364fd1d7068b2 |
| institution | Kabale University |
| issn | 1472-6947 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj-art-dfa474081d3a47b3b56364fd1d7068b22025-08-20T03:45:30ZengBMCBMC Medical Informatics and Decision Making1472-69472025-07-0125111210.1186/s12911-025-03077-6medAL-suite: A software solution for creating and deploying complex clinical decision support algorithmsLudovico Gennaro Cobuccio0Vincent Faivre1Rainer Tan2Alan Vonlanthen3Fenella Beynon4Emmanuel Barchichat5Alain Fresco6Quentin Girard7Sinan Ucak8Sylvain Schaufelberger9Ibrahim Evans Mtebene10Peter Agrea11Emmanuel Kalisa12Gillian A. Levine13Martin Norris14Sabine Renggli15Alix Miauton16Lisa Cleveley17Kristina Keitel18Julien Thabard19Valérie D’Acremont20Alexandra V. Kulinkina21Centre for Primary Care and Public Health (Unisanté), University of LausanneCentre for Primary Care and Public Health (Unisanté), University of LausanneCentre for Primary Care and Public Health (Unisanté), University of LausanneCentre for Primary Care and Public Health (Unisanté), University of LausanneSwiss Tropical and Public Health InstituteWavemindWavemindWavemindWavemindCentre for Primary Care and Public Health (Unisanté), University of LausanneIfakara Health InstituteNational Institute for Medical Research, Mbeya Medical Research CenterSwiss Tropical and Public Health InstituteSwiss Tropical and Public Health InstituteSwiss Tropical and Public Health InstituteIfakara Health InstituteCentre for Primary Care and Public Health (Unisanté), University of LausanneSwiss Tropical and Public Health InstituteSwiss Tropical and Public Health InstituteCentre for Primary Care and Public Health (Unisanté), University of LausanneCentre for Primary Care and Public Health (Unisanté), University of LausanneSwiss Tropical and Public Health InstituteAbstract Background Sub-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. Methods In 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. Results Since 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.https://doi.org/10.1186/s12911-025-03077-6Clinical decision supportAlgorithmDigital healthClinical guidelinesCDSS |
| spellingShingle | Ludovico Gennaro Cobuccio Vincent Faivre Rainer Tan Alan Vonlanthen Fenella Beynon Emmanuel Barchichat Alain Fresco Quentin Girard Sinan Ucak Sylvain Schaufelberger Ibrahim Evans Mtebene Peter Agrea Emmanuel Kalisa Gillian A. Levine Martin Norris Sabine Renggli Alix Miauton Lisa Cleveley Kristina Keitel Julien Thabard Valérie D’Acremont Alexandra V. Kulinkina medAL-suite: A software solution for creating and deploying complex clinical decision support algorithms BMC Medical Informatics and Decision Making Clinical decision support Algorithm Digital health Clinical guidelines CDSS |
| title | medAL-suite: A software solution for creating and deploying complex clinical decision support algorithms |
| title_full | medAL-suite: A software solution for creating and deploying complex clinical decision support algorithms |
| title_fullStr | medAL-suite: A software solution for creating and deploying complex clinical decision support algorithms |
| title_full_unstemmed | medAL-suite: A software solution for creating and deploying complex clinical decision support algorithms |
| title_short | medAL-suite: A software solution for creating and deploying complex clinical decision support algorithms |
| title_sort | medal suite a software solution for creating and deploying complex clinical decision support algorithms |
| topic | Clinical decision support Algorithm Digital health Clinical guidelines CDSS |
| url | https://doi.org/10.1186/s12911-025-03077-6 |
| work_keys_str_mv | AT ludovicogennarocobuccio medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT vincentfaivre medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT rainertan medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT alanvonlanthen medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT fenellabeynon medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT emmanuelbarchichat medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT alainfresco medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT quentingirard medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT sinanucak medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT sylvainschaufelberger medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT ibrahimevansmtebene medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT peteragrea medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT emmanuelkalisa medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT gillianalevine medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT martinnorris medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT sabinerenggli medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT alixmiauton medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT lisacleveley medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT kristinakeitel medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT julienthabard medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT valeriedacremont medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms AT alexandravkulinkina medalsuiteasoftwaresolutionforcreatinganddeployingcomplexclinicaldecisionsupportalgorithms |