Semantic Integration of BPMN Models and FHIR Data to Enable Personalized Decision Support for Malignant Melanoma

Autor: Catharina Lena Beckmann, Daniel Keuchel, Wa Ode Iin Arliani Soleman, Sylvia Nürnberg, Britta Böckmann
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Information, Vol 14, Iss 12, p 649 (2023)
Druh dokumentu: article
ISSN: 2078-2489
DOI: 10.3390/info14120649
Popis: With digital patient data increasing due to new diagnostic methods and technology, showing the right data in the context of decision support at the point of care becomes an even greater challenge. Standard operating procedures (SOPs) modeled in BPMN (Business Process Model and Notation) contain evidence-based treatment guidance for all phases of a certain diagnosis, while physicians need the parts relevant to a specific patient at a specific point in the clinical process. Therefore, integration of patient data from electronic health records (EHRs) providing context to clinicians is needed, which is stored and communicated in HL7 (Health Level Seven) FHIR (Fast Healthcare Interoperability Resources). To address this issue, we propose a method combining an integration of stored data into BPMN and a loss-free transformation from BPMN into FHIR, and vice versa. Based on that method, an identification of the next necessary decision point in a specific patient context is possible. We verified the method for treatment of malignant melanoma by using an extract of a formalized SOP document with predefined decision points and validated FHIR references with real EHR data. The patient data could be stored and integrated into the BPMN element ‘DataStoreReference’. Our loss-free transformation process therefore is the foundation for combining evidence-based knowledge from formalized clinical guidelines or SOPs and patient data from EHRs stored in FHIR. Processing the SOP with the available patient data can then lead to the next upcoming decision point, which will be displayed to the physician integrated with the corresponding data.
Databáze: Directory of Open Access Journals
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