A Microservice-Based Architecture for Clinical Decision Support System for Addressing Non-Specific Musculoskeletal Disorders: The SupportPrim Project

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Abstract There is a dearth of applied interdisciplinary research on the implementation of a clinical decision support system (CDSS) that employs case-based reasoning (CBR) based on patient data from a subjective questionnaire for non-specific musculoskeletal disorders (MSDs). Furthermore, there are numerous practical obstacles to creating a CDSS system for such a complex and challenging domain, which can impede progress due to several cold-start issues. This applied research introduces a microservice-based backend architecture developed for the interdisciplinary SupportPrim project that mitigates critical real-world challenges while providing a scalable, resilient, and viable CDSS. The implemented CDSS is deployed for randomized controlled trial (RCT) in Norwegian primary care using subjective patient-reported non-specific MSD patient data. The microservice architecture provides scalability, reliability, and a user-centric approach that aligns with the dynamic nature of clinical workflows. The research is based on the applied research methodology while leveraging a design thinking approach to iteratively develop a scalable backend framework that can accommodate the idiosyncrasies of subjective patient data and facilitate the implementation of CBR systems in the CDSS. The results of a laboratory deployment of SupportPrim patient data in the Norwegian primary healthcare setting support the technical competency of the proposed architecture in finding patients with similar non-specific MSDs. Medical researchers have demonstrated the competence of the proposed architecture in the SupportPrim project through iterative experiments carried out by domain experts and the RCT within the Norwegian healthcare system, and clinicians have reported good acceptability and usability of the CDSS. This research might serve as a guide for further investigation and development of an adaptable and scalable patient-centered CDSS employing a CBR system.
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A Microservice-Based Architecture for Clinical Decision Support System for Addressing Non-Specific Musculoskeletal Disorders: The SupportPrim Project | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A Microservice-Based Architecture for Clinical Decision Support System for Addressing Non-Specific Musculoskeletal Disorders: The SupportPrim Project Amar Jaiswal, Ingebrigt Meisingset This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4122773/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract There is a dearth of applied interdisciplinary research on the implementation of a clinical decision support system (CDSS) that employs case-based reasoning (CBR) based on patient data from a subjective questionnaire for non-specific musculoskeletal disorders (MSDs). Furthermore, there are numerous practical obstacles to creating a CDSS system for such a complex and challenging domain, which can impede progress due to several cold-start issues. This applied research introduces a microservice-based backend architecture developed for the interdisciplinary SupportPrim project that mitigates critical real-world challenges while providing a scalable, resilient, and viable CDSS. The implemented CDSS is deployed for randomized controlled trial (RCT) in Norwegian primary care using subjective patient-reported non-specific MSD patient data. The microservice architecture provides scalability, reliability, and a user-centric approach that aligns with the dynamic nature of clinical workflows. The research is based on the applied research methodology while leveraging a design thinking approach to iteratively develop a scalable backend framework that can accommodate the idiosyncrasies of subjective patient data and facilitate the implementation of CBR systems in the CDSS. The results of a laboratory deployment of SupportPrim patient data in the Norwegian primary healthcare setting support the technical competency of the proposed architecture in finding patients with similar non-specific MSDs. Medical researchers have demonstrated the competence of the proposed architecture in the SupportPrim project through iterative experiments carried out by domain experts and the RCT within the Norwegian healthcare system, and clinicians have reported good acceptability and usability of the CDSS. This research might serve as a guide for further investigation and development of an adaptable and scalable patient-centered CDSS employing a CBR system. Physical sciences/Mathematics and computing/Computer science Physical sciences/Mathematics and computing/Software Physical sciences/Mathematics and computing/Information technology Health sciences/Health occupations Health sciences/Signs and symptoms/Pain Health sciences/Health care/Therapeutics/Pain management Physical sciences/Engineering/Biomedical engineering Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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