Focus Section Health IT Usability: Applying a Task-Technology Fit Model to Adapt an Electronic Patient Portal for Patient Work.
Academic Article
Overview
abstract
OBJECTIVES: Although electronic patient portals are offered by most health care organizations, poor usability and poor fit to patient needs may pose barriers to adoption. We collaborated with an academic hospital to conduct iterative user evaluation of a newly deployed portal designed to deliver inpatient data upon hospital discharge. METHODS: Three evaluators applied heuristic usability evaluation and conducted 23 individual user testing sessions with patients with chronic disease or managing the care of family members with chronic disease. Evaluation and development/improvement were conducted iteratively. User testing and analysis of qualitative data were both conducted from the perspective of a task-technology fit framework, to assess the degree of fit between the portal and patient work. RESULTS: Ability to complete health information management tasks, perceived usability, and positive comments from users improved over the course of the iterative development. However, patients still encountered significant difficulties accomplishing certain tasks such as setting up proxy accounts. The problems were most severe when patients did not start with a clear understanding of tasks that they could accomplish. In exploring the portal, novice users frequently described anecdotes from their own medical history or constructed fictional narratives about a hypothetical patient. CONCLUSION: Chronic illness imposes a significant workload on patients, and applying a task-technology framework for evaluation of a patient portal helped improve the portal's fit to patient needs. However, it also revealed that patients often lack a clear understanding of tasks that would help them accomplish personal health information management. Portal developers may need to educate patients about types of patient work involving medical centers, in a way that developers of clinical information systems do not need to do. An approach to doing this might be to provide narratives about hypothetical patients.
