Difference between revisions of "An Interface-driven Analysis of User Interactions with an Electronic Health Record System"
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Revision as of 22:39, 10 February 2015
This is a review of An Interface-driven Analysis of User Interactions with an Electronic Health Record System. [1]
Background
This article is a qualitative study that evaluates a research team’s initial implementation to a clinical decision support(CDS) system. The team includes researchers & practitioners at the Western Pennsylvania Hospital.
Methods
Electronic health record (EHR) data usage was analyzed for 10 months. The study included/ was measured by event sequences, pattern, chain analysis, usage rate and pattern encounters.
Results
The “empirical data” showed popular pathways: Assessment and Plan, Order, Diagnosis and Medication Side Effects. Some of the most frequently assessed features were Retaking BP, Procedure, and Encounter Memo. Those features made up 70% to all EHR user interactions.
Conclusion
This research brought negatives to light. Poor user interface and application flow are the main reasons why many Health IT implementations fail. The results show hidden patterns such as those demonstrated by clinicians when they were navigating. Unanticipated patterns gave understanding to user behavior and recommendation standards. Overall, lessons were learned and the system was re-engineered with designs to fix the issues.
Comments
I think this was a great research article. The department I work in manages hospital owned ambulatory clinics and I have had exposure to more than 8 EHRs. They all behave differently. The workflow is similar but I hear complaints from the physicians and staff all the time. I feel this paper focused on the clinician factors of the system and not so much patterns or activity of the front staff, office managers and the technological analysts. Even though their input isn’t as important as the clinicians or the providers, their patters could have identified areas of improvement for registration, billing and scheduling.
References
- ↑ Zheng, K., Padman, R., Johnson, M., & Diamond, H. (2009). An Interface-driven Analysis of User Interactions with an Electronic Health Record System. http://jamia.oxfordjournals.org/content/16/2/228
