The Impact of Domain Knowledge on Structured Data Collection and Templated Note Design
20 February 2013
accepted: 13 June 2013
16 December 2017 (online)
Objective: The objective of this case report is to evaluate the importance of specialized domain knowledge when designing and using structured templated notes in a clinical environment.
Methods: To analyze the impact of specialization on structured note generation we compared notes generated for three scenarios: 1) We compared the templated history of present illness (HPI) for patients presenting with a dermatology concern to the dermatologist versus the emergency department. 2) We compared the evaluation of chest pain by ED physicians versus cardiologists. 3) Finally, we compared the data elements asked for in the evaluation of the gastrointestinal system between cardiologists and the liver transplant service (LTS). We used the SNOMED CT representation via BioPortal to evaluate specificity and grouping between data elements and specialized physician groups.
Results: We found few similarities in structured data elements designed by and for the specific physician groups. The distinctness represented both differences in granularity as well as fundamental differences in data elements requested. When compared to ED physicians, dermatologists had different and more granular elements while cardiologists requested much more granular data. Comparing cardiologists and LTS, there were differences in the data elements requested.
Conclusion: This case study supports the importance of domain knowledge in EHR design and implementation. That different specialities should want and use different information is well supported by cognitive science literature. Despite this, it is rare for domain knowledge to be considered in EHR implementation. Physicians with correct domain knowledge should be involved in the design process of templated notes.
- 1 Baron RJ. Meaningful use of health information technology is managing information.. JAMA: The Journal of the American Medical Association 2010; 304: 89.
- 2 Centers for Medicare & Medicaid Services, Department of Health and Human Services. Medicare and Medicaid Programs; Electronic Health Record Incentive Program; Proposed rule. 2010; 1844.
- 3 Krohn R. Closing the “Loop” of Clinical Performance Improvement.. EDITOR’S INTRODUCTION 20: 12.
- 4 Epic Charting Tools: Comparing their ease of use and Suitability for ImproveCareNow Activities. August 17, 2010.
- 5 Henry SB. et al. A template-based approach to support utilization of clinical practice guidelines within an electronic health record.. Journal of the American Medical Informatics Association 1998; 5: 237.
- 6 Knowledge representation for platform-independent structured reporting.. Proceedings of the AMIA Annual Fall Symposium:: American Medical Informatics Association; 1996
- 7 Grabenbauer L. et al. Adoption of EHR –a qualitative study of academic and private physicians and health administrators.. Appl Clin Inf 2011; 2: 165-176.
- 8 Grabenbauer L, Skinner A, Windle J. Electronic health record adoption –maybe it’s not about the money physician super-users, electronic health records and patient care.. Appl Clin Inf 2011; 2: 460-471.
- 9 Snow, RRE.. Toward assessment of cognitive and conative structures in learning.. Educational Researcher. 1989; 18: 9.
- 10 Liberti A. et al. The PRISMA statement for reporting systemic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration.. Annals of Internal Medicine 2009; 151. 4: W-65.
- 11 Harriger M. Beyond Scripting: Using Python to create a medical information system with graphical template and database schema design 2006:. http://wiki.python.org/moin/PyCon2006/Talks.
- 12 Stearns MQ, Price C, Spackman KA, Wang AY. SNOMED clinical terms: overview of the development process and project status.. Proceedings of the AMIA Symposium. American Medical Informatics Association. 2001; 662.
- 13 Benson T. Principles of Health Interoperability HL7 and SNOMED.. Springer Verlag. 2010; 11. 5.1: 186.
- 14 Noy NF. et al. BioPortal: ontologies and integrated data resources at the click of a mouse.. Nucleic acids research 2009; 37 (Suppl. 02) W170-W173.
- 15 SNOMED CT Collaborative Efforts.. Standards Facilitate Collaboration, Public Health Data Standards;. March 17-18, 2004
- 16 Braunwald E. et al. ACC/AHA 2002 guideline update for the management of patients with unstable angina and non-ST-segment elevation myocardial infarction summary article: a report of the American College of Cardiology/American Heart Association task force on practice guidelines (Committee on the Management of Patients With Unstable Angina).. J Am Coll Cardiol 2002; 40: 1366.
- 17 Antman EM. et al. The TIMI risk score for unstable angina/non–ST elevation MI.. JAMA: the journal of the American Medical Association 2000; 284: 835.
- 18 Geary U, Kennedy U. Clinical decision-making in emergency medicine.. Emergencias 2010; 22: 56-60.
- 19 Shortliffe EH, Cimino JJ. Biomedical informatics: computer applications in health care and biomedicine.. Springer Verlag;: 2006
- 20 Fincher-Kiefer R, Post TA, Greene TR, Voss JF. On the role of prior knowledge and task demands in the processing of text. 1.. Journal of Memory and Language 1988; 27: 416-428.
- 21 Identifying and overcoming obstacles to point-of-care data collection for eye care professionals.. AMIA Annual Symposium Proceedings:: American Medical Informatics Association;; 2005
- 22 O’Malley AS. et al. Are Electronic Medical Records Helpful for Care Coordination? Experiences of Physician Practices.. J Gen Intern Med 2010; 25 (03) 177-185.
- 23 Beck IL, Carpenter PA. Cognitive approaches to understanding reading.. American Psychologist 1986; 41: 1098-1105.
- 24 Brown AL. et al. Learning, remembering, and understanding.. In J. H. Flavell & E. M. Markman (Eds.), Handbook of child psychology: Vol. 3. Cognitive development. (4th ed., pp. 77-166). New York: Wiley..
- 25 Larkin JH. et al. Expert and novice performance in solving physics problems.. Science 1980; 208: 1335-1342.
- 26 Eslami S, Abu-Hanna A, de Keizer NF. Evaluation of outpatient computerized physician medication order entry systems: a systematic review.. J Am Med Inform Assoc 2007; 14: 400-406.
- 27 Atienza AA. et al. E-health research and patient-centered care examining theory, methods, and application.. Am J Prev Med 2010;38(1): 85–88. doi: 10.1016/j.amepre.2009.10.027.S0749-3797(09)00749-1
- 28 Voss JF, Vesonder GT, Spilich GJ. Text generation and recall by high-knowledge and low-knowledge individuals.. Journal of Verbal Learning and Verbal Behavior 1980; 19: 651-667.
- 29 Rosenbloom ST. et al. Using SNOMED CT to represent two interface terminologies.. Journal of the American Medical Informatics Association 2009; 16: 81-88.
- 30 Rothwell DJ. Managing information with SNOMED: understanding the model.. Proceedings of the AMIA Annual Fall Symposium: American Medical Informatics Association; 1996: 80-83.
- 31 Guarino N, Giaretta P. Ontologies and knowledge bases: Towards a terminological clarification.. Towards Very Large Knowledge Bases Knowledge Building and Knowledge Sharing 1995; 1: 25-32.
- 32 Musen MA. Domain ontologies in software engineering: use of Protege with the EON architecture.. Methods of Information in Medicine 1998; 37: 540-550.
- 33 Musen MA. Dimensions of knowledge sharing and reuse.. Computers and biomedical research 1992; 25: 435-467.
- 34 Gray J. et al. Domain-specific modeling.. Handbook of Dynamic System Modeling; 2007
- 35 Nylenna M. Aasland OG: Primary care physicians and their information-seeking behaviour.. Scandinavian Journal of Primary Health Care 2000; 18 (Suppl. 01) 9-13.
- 36 Han YY. et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system [published correction appears in Pediatrics. 2006; 117: 594].. Pediatrics 2005; 116: 1506-1512.
- 37 Sittig DF. et al. Lessons from “Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system”.. Pediatrics 2006; 118: 797-801.
- 38 Grabenbauer L. et al. A qualitative analysis of academic and private physicians and administrators’ perceptions of health information technology.. AMIA Annual Symposium proceedings AMIA Symposium AMIA Symposium; 2007
- 39 Garde S. et al. Towards Semantic Interoperability for Electronic Health Records: Domain Knowledge Governance for openEHR Archetypes.. Methods Inf Med 2007; 46 (03) 332-343.