Clinical Event Architecture: Perspective Conflict Patterns in Healthcare Information Systems
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V7I1P124Keywords:
Healthcare Information Systems, Electronic Health Records (Ehrs), Event-Driven Architecture, Clinical Decision Support, Domain-Driven Design, Interoperability, Pattern Language, Event Sourcing, Command Query Responsibility Segregation (CQRS)Abstract
Healthcare information systems force diverse stakeholders into single data models, creating fundamental conflicts when the same clinical events require different representations for billing, safety monitoring, regulatory compliance, and clinical workflows. Current approaches rely on complex transformation layers, data duplication, or forcing stakeholders into misfit models, resulting in data quality issues, integration complexity, and compromised decision support. This paper presents a systematic catalog of perspective conflict patterns observed in clinical event systems, documenting four fundamental conflict types: Safety versus Workflow Granularity, Billing versus Clinical Timing, Identity Context Dependence, and Compliance Audit versus Performance Optimization. For each pattern, the paper provides clinical context, competing stakeholder requirements, architectural solutions grounded in event-driven design principles, and trade-off analysis. The paper proposes a reference architecture employing event sourcing with perspective-specific projections that enables multiple valid representations of the same clinical events without transformation complexity. This pattern catalog provides healthcare architects and informaticists with a systematic framework for diagnosing and resolving multi-perspective conflicts in electronic health record systems and clinical decision support platforms.
Downloads
References
[1] B. G. Arndt et al., “Tethered to the EHR: Primary Care Physician Workload Assessment Using EHR Event Log Data and Time-Motion Observations,” The Annals of Family Medicine, vol. 15, no. 5, pp. 419–426, Sep. 2017, doi: https://doi.org/10.1370/afm.2121.
[2] A. Alanazi, W. Alalawi, B. Aldosari, “An Evaluation of Drug-Drug Interaction Alerts Produced by Clinical Decision Support Systems in a Tertiary Hospital,” Cureus, vol. 15, no. 8, Aug. 2023, doi: https://doi.org/10.7759/cureus.43141.
[3] J. Howe et al., "Electronic health record usability issues and potential contribution to patient harm," JAMA, vol. 319, no. 12, pp. 1276-1278, Mar. 2018.
[4] M. Fowler, “Event Sourcing,” martinfowler.com, Dec. 12, 2005. https://martinfowler.com/eaaDev/EventSourcing.html.
[5] E. Evans, Domain-Driven Design: Tackling Complexity in the Heart of Software. Boston, Mass.; Munich: Addison-Wesley, 2003.
[6] T. T. Van Vleck and Noémie Elhadad, “Corpus-Based Problem Selection for EHR Note Summarization,” AMIA Annual Symposium Proceedings, vol. 2010, pp. 817-821, Nov. 2010, Accessed: Feb. 16, 2026. [Online]. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC3041431/.
[7] American Medical Association, "CPT overview and code approval," AMA CPT, 2024. [Online]. Available: https://www.ama-assn.org/practice-management/cpt/cpt-overview-and-code-approval
[8] D. M. Berwick and A. D. Hackbarth, “Eliminating Waste in US Health Care,” JAMA, vol. 307, no. 14, pp. 1513-1516, Apr. 2012, doi: https://doi.org/10.1001/jama.2012.362.
[9] CMS, “Quality Measures | CMS,” www.cms.gov, Sep. 06, 2023. https://www.cms.gov/medicare/quality/measures.
[10] A. W. Wu, T. A. Cavanaugh, S. J. McPhee, B. Lo, and G. P. Micco, “To tell the truth,” Journal of General Internal Medicine, vol. 12, no. 12, pp. 770–775, Dec. 1997, doi: https://doi.org/10.1046/j.1525-1497.1997.07163.x.
[11] The Joint Commission, “National patient safety goals,” The Joint Commission, 2025. https://www.jointcommission.org/standards/national-patient-safety-goals/.
[12] “Guidance Regarding Methods for De-identification of Protected Health Information in Accordance with the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule,” 2012. Available: https://privacysecurityacademy.com/wp-content/uploads/2021/03/HHS-OCR-Guidance-on-De-Identification-of-PHI-2012.pdf.
[13] N. Menachemi and T. Collum, “Benefits and drawbacks of electronic health record systems,” Risk Management and Healthcare Policy, vol. 4, pp. 47–55, May 2011, Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3270933/.
[14] R. H. Dolin et al., “HL7 Clinical Document Architecture, Release 2,” Journal of the American Medical Informatics Association, vol. 13, no. 1, pp. 30–39, Jan. 2006, doi: https://doi.org/10.1197/jamia.m1888.
[15] HL7 International, “Index - FHIR v4.0.1,” Hl7.org, 2019. https://hl7.org/fhir/R4/index.html.
[16] J. Gray et al., “Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals” Data Mining and Knowledge Discovery, vol. 1, no. 1, pp. 29–53, 1997, doi: https://doi.org/10.1023/a:1009726021843.
[17] M. Grissinger, “Guidelines for Standard Order Sets,” Pharmacy and Therapeutics, vol. 39, no. 1, pp. 10-50, 2014, Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC3956384/.
[18] D. A. Kurth, B. K. Karmazyn, C. A. Waldrip, M. Chatfield, and M. E. Lockhart, “ACR Appropriateness Criteria® Methodology,” Journal of the American College of Radiology, vol. 18, no. 11, pp. S240–S250, Nov. 2021, doi: https://doi.org/10.1016/j.jacr.2021.03.021.
[19] J. R. Vest and L. D. Gamm, “Health information exchange: Persistent challenges and new strategies,” Journal of the American Medical Informatics Association, vol. 17, no. 3, pp. 288–294, May 2010, doi: https://doi.org/10.1136/jamia.2010.003673.
[20] U.S. Department of Health and Human Services, “The Security Rule,” HHS.gov, Oct. 20, 2022. https://www.hhs.gov/hipaa/for-professionals/security/index.html.
[21] Institute of Medicine, “Health IT and patient safety: building safer systems for better care.” Washington, D.C.: National Academies Press, 2012.
[22] D. F. Sittig and H. Singh, “A new sociotechnical model for studying health information technology in complex adaptive healthcare systems,” Quality and Safety in Health Care, vol. 19, no. Suppl 3, pp. i68–i74, Oct. 2010, doi: https://doi.org/10.1136/qshc.2010.042085.
