Leveraging Drools Workbench for Effective Clinical Decision Support System Design

This paper explores the conception, development, and real-world evaluation of a Clinical Decision Support System (CDSS) aimed at enhancing health-care decision-making. Utilizing the Drools Workbench for rule-based logic, a visual clinical flowchart, and seamless integration with Fast Healthcare Interoperability Resources (FHIR) input, the CDSS offers a robust solution for dynamic and evidence-based decision support. In this paper, we present a generalized method for creating complex CDSS using Drools Workbench. Our approach begins with original clinical guidelines, which are converted into clinical flowcharts and computer interpretable guidelines. We then perform a guideline reconciliation process on these computer interpretable guidelines to accommodate comorbidity requirements. Clinical concepts extracted from the reconciled guidelines are translated into Domain-Specific Language (DSL) files in Drools Workbench. Based on these DSL files and computer interpretable guidelines, we create a set of business processes that form a comprehensive CDSS for individual diseases. By running multiple CDSS within a single system, we develop a CDSS for comorbidities. Functional testing is conducted by both technical personnel and healthcare professionals to ensure that the output aligns with real-world practices. The innovation of this paper lies in presenting a more general method for creating CDSS with minimal programmer assistance, addressing not just a single disease but a range of diseases, with consideration of their comorbidities.

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Published
2024-11-13
DOI
https://doi.org/10.1145/3696593.3696605
Primary Topic
Artificial Intelligence in Healthcare
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article
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article

Leveraging Drools Workbench for Effective Clinical Decision Support System Design

Theodoros N. Arvanitis, Omid Pournik, Chao Tong, Gökhan Yilmaz et al.
Artificial Intelligence in Healthcare
article

Leveraging Drools Workbench for Effective Clinical Decision Support System Design

Theodoros N. Arvanitis, Omid Pournik, Chao Tong, Gökhan Yilmaz, Julio Muñoz García, Araitz Largo Arana
article en

Abstract

This paper explores the conception, development, and real-world evaluation of a Clinical Decision Support System (CDSS) aimed at enhancing health-care decision-making. Utilizing the Drools Workbench for rule-based logic, a visual clinical flowchart, and seamless integration with Fast Healthcare Interoperability Resources (FHIR) input, the CDSS offers a robust solution for dynamic and evidence-based decision support. In this paper, we present a generalized method for creating complex CDSS using Drools Workbench. Our approach begins with original clinical guidelines, which are converted into clinical flowcharts and computer interpretable guidelines. We then perform a guideline reconciliation process on these computer interpretable guidelines to accommodate comorbidity requirements. Clinical concepts extracted from the reconciled guidelines are translated into Domain-Specific Language (DSL) files in Drools Workbench. Based on these DSL files and computer interpretable guidelines, we create a set of business processes that form a comprehensive CDSS for individual diseases. By running multiple CDSS within a single system, we develop a CDSS for comorbidities. Functional testing is conducted by both technical personnel and healthcare professionals to ensure that the output aligns with real-world practices. The innovation of this paper lies in presenting a more general method for creating CDSS with minimal programmer assistance, addressing not just a single disease but a range of diseases, with consideration of their comorbidities.

Ta Solutions (China) (CN), Software Research and Development Consulting (TR), University of Birmingham (GB)
Peace, Justice and strong institutions
Openalex Percentile: Top 58%
Artificial Intelligence in Healthcare
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