Currently accepted at: Journal of Medical Internet Research
Date Submitted: Jun 3, 2025
Open Peer Review Period: Jun 4, 2025 - Jul 30, 2025
Date Accepted: May 4, 2026
(closed for review but you can still tweet)
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/78506
The final accepted version (not copyedited yet) is in this tab.
The Implementation of Business Process Model and Notation (BPMN) for Modeling Patient Healthcare Trajectories: A Systematic Review
ABSTRACT
Background:
Healthcare systems are increasingly confronted with the challenge of managing complex clinical processes. One proposed solution is a patient-centered management intervention called a care pathway that needs process mapping to support process improvement. Although the adoption and use of Business Process Model and Notation (BPMN) for modeling patient healthcare trajectories has increased, evidence of the benefits of implementing it in healthcare organization management systems are still unclear.
Objective:
This review sought to examine effectiveness by mapping evidence of implementation factors linking intended purpose to expected or demonstrated outcomes.
Methods:
A systematic review of the use of BPMN for modeling patient care trajectories was conducted across Medline (Ovid), Embase (Embase.com), Academic Search Premier, ABI/Inform (ProQuest), Web of Science, and Google Scholar. We followed the Cochrane Methods Group and the PRISMA guidelines. Quality appraisal was performed using the Mixed Methods Appraisal Tool (MMAT). Data were charted using a customized form and were analyzed thematically with both qualitative and semi-quantitative syntheses.
Results:
After screening, 53 studies were included. Our findings suggest that BPMN offers significant benefits in healthcare. Its use allows healthcare professionals to gain a comprehensive understanding of patient care pathways, making it easier to identify inefficiencies and areas for improvement. The definition of processes ensures that workflows remain consistent across different settings, thereby reducing variation and improving the quality of care. Several studies have demonstrated BPMN’s effectiveness in process optimization, highlighting its ability to streamline workflows, reduce redundancies, and enhance operational efficiency. Moreover, when integrated with decision-support tools, BPMN enhances clinical decision-making by enabling better adherence to guidelines and best practices. Another important advantage is BPMN’s interoperability with existing healthcare IT standards, such as HL7, which facilitates seamless integration with EHRs and other digital health systems. However, in a managerial perspective, users must also carefully weigh the trade-offs between BPMN’s benefits and its limitations, particularly in highly complex healthcare settings. Despite advantages, several challenges persist, including issues related to scalability, integration with advanced decision-making frameworks and the complexity of modeling dynamic healthcare environments. While BPMN is a widely adopted modeling approach, alternative methodologies offer complementary or competing advantages, such as Petri Nets, UML or Business Process Execution Language. Therefore, there are several opportunities for enhancing BPMN’s applicability in healthcare, such as the creation of domain-specific BPMN extensions or the integration of artificial intelligence and machine learning into BPMN models.
Conclusions:
This review highlights BPMN’s potential as a valuable tool for modeling patient healthcare trajectories. Its ability to standardize and optimize processes makes it a promising framework for improving clinical and operational efficiency. However, trade-offs between benefits and limits of BPMN characterized its implementation in patient care trajectories, giving rise to opportunities for the development and integration of new tools.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.