Zheng K et al. 2009 "An interface-driven analysis of user interactions with an electronic health records system."
Reference
Zheng K, Padman R, Johnson MP, et al. An interface-driven analysis of user interactions with an electronic health records system. J Am Med Inform Assoc 2009;16(2):228-237.
Abstract
"Objectives: This study sought to investigate user interactions with an electronic health records (EHR) system by uncovering hidden navigational patterns in the EHR usage data automatically recorded as clinicians navigated through the system's software user interface (UI) to perform different clinical tasks.
Design: A homegrown EHR was adapted to allow real-time capture of comprehensive UI interaction events. These events, constituting time-stamped event sequences, were used to replay how the EHR was used in actual patient care settings. The study site is an ambulatory primary care clinic at an urban teaching hospital. Internal medicine residents were the primary EHR users.
Measurements: Computer-recorded event sequences reflecting the order in which different EHR features were sequentially accessed.
Methods: We apply sequential pattern analysis (SPA) and a first-order Markov chain model to uncover recurring UI navigational patterns.
Results: Of 17 main EHR features provided in the system, SPA identified 3 bundled features: "Assessment and Plan" and "Diagnosis," "Order" and "Medication," and "Order" and "Laboratory Test." Clinicians often accessed these paired features in a bundle together in a continuous sequence. The Markov chain analysis revealed a global navigational pathway, suggesting an overall sequential order of EHR feature accesses. "History of Present Illness" followed by "Social History" and then "Assessment and Plan" was identified as an example of such global navigational pathways commonly traversed by the EHR users.
Conclusion: Users showed consistent UI navigational patterns, some of which were not anticipated by system designers or the clinic management. Awareness of such unanticipated patterns may help identify undesirable user behavior as well as reengineering opportunities for improving the system's usability."
Design: A homegrown EHR was adapted to allow real-time capture of comprehensive UI interaction events. These events, constituting time-stamped event sequences, were used to replay how the EHR was used in actual patient care settings. The study site is an ambulatory primary care clinic at an urban teaching hospital. Internal medicine residents were the primary EHR users.
Measurements: Computer-recorded event sequences reflecting the order in which different EHR features were sequentially accessed.
Methods: We apply sequential pattern analysis (SPA) and a first-order Markov chain model to uncover recurring UI navigational patterns.
Results: Of 17 main EHR features provided in the system, SPA identified 3 bundled features: "Assessment and Plan" and "Diagnosis," "Order" and "Medication," and "Order" and "Laboratory Test." Clinicians often accessed these paired features in a bundle together in a continuous sequence. The Markov chain analysis revealed a global navigational pathway, suggesting an overall sequential order of EHR feature accesses. "History of Present Illness" followed by "Social History" and then "Assessment and Plan" was identified as an example of such global navigational pathways commonly traversed by the EHR users.
Conclusion: Users showed consistent UI navigational patterns, some of which were not anticipated by system designers or the clinic management. Awareness of such unanticipated patterns may help identify undesirable user behavior as well as reengineering opportunities for improving the system's usability."
Objective
"To investigate user interactions with an electronic health records (EHR) system by uncovering hidden navigational patterns in the EHR usage data automatically recorded as clinicians navigated through the system's software user interface (UI) to perform different clinical tasks."
Type Clinic
Primary care
Type Specific
Internal medicine
Size
Large
Geography
Urban
Other Information
The clinic is part of the Western Pennsylvania Hospital, an urban teaching hospital in Pittsburgh.
Type of Health IT
Electronic health records (EHR)
Type of Health IT Functions
"The clerical staff and nurses in the clinic used the system to schedule appointments, manage workflow, and collect pre-encounter assessments such as vital signs; the residents and attending physicians used the system to document clinical findings, prescribe medications, enter orders, and generate patient-specific chronic disease management and preventive care reminders." It has a Web-based user interface and the following features: assessment and plan, retaking blood pressure, diagnosis and problem list, medication side effects, family history, allergies, history of present illness, laboratory test, medications, orders, procedures, encounter memo, social history, office tests, vaccinations, physical examination, and review of systems.
Workflow-Related Findings
Analysis of EHR use shows that clinicians tended to avoid structured data entry, leading to less than optimal sequences of clinical documentation. "This finding suggests that either certain critical patient care procedures (e.g., physical examination) were not routinely performed, or they were performed but not properly documented, or were not documented in a desirable sequence. In either case, quality of care may be undermined and patients may be exposed to a higher risk of adverse events."
Despite the importance attributed by end users on the design team and being given one of the most prominent screen positions, "'Encounter Memo' was seldom used. 'Encounter Memo' allows clinicians to document contextual information that may not fit in any other categories, or transitory information that does not need to, or should not, appear in a patient's permanent record; for example, handoff notes."
Study Design
Only postintervention (no control group)
Study Participants
Thirty internal medicine residents participated in the study.