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Background <p>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.</p> Methods <p>In response to these challenges, we developed open-source software called the Medical Algorithm Suite (medAL-<i>suite</i>), 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-<i>creator</i> that allows clinicians to design algorithms using a code-free drag-and-drop interface. Algorithms are subsequently automatically deployed in <i>medAL-reader</i> to service level clinicians in health facilities. CDSS implementers use medAL-<i>data</i> and medAL-<i>hub</i> to manage configuration, versioning, and deployment.</p> Results <p>Since its development, the medAL-<i>suite</i> 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.</p> Discussion <p>The medAL-<i>suite</i> 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.</p> Clinical trial number <p>Not applicable.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月4日

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  • 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

摘要

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.