April Savoy

Permanent URI for this collection

https://hdl.handle.net/1805/35566

Browse

Browsing April Savoy by Author "Biostatistics, School of Public Health"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    A cognitive systems engineering design approach to improve the usability of electronic order forms for medical consultation
    (Elsevier, 2018-09) Savoy, April; Militello, Laura G.; Patel, Himalaya; Flanagan, Mindy E.; Russ, Alissa L.; Daggy, Joanne K.; Weiner, Michael; Saleem, Jason J.; Biostatistics, School of Public Health
    Background During medical referrals, communication barriers between referring and consulting outpatient clinics delay patients’ access to health care. One notable opportunity for reducing these barriers is improved usefulness and usability of electronic medical consultation order forms. The cognitive systems engineering (CSE) design approach focuses on supporting humans in managing cognitive complexity in sociotechnical systems. Cognitive complexity includes communication, decision-making, problem solving, and planning. Objective The objective of this research was to implement a CSE design approach to develop a template that supports the cognitive needs of referring clinicians and improves referral communication. Methods We conducted interviews and observations with primary care providers and specialists at two major tertiary, urban medical facilities. Using qualitative analysis, we identified cognitive requirements and design guidelines. Next, we designed user interface (UI) prototypes and compared their usability with that of a currently implemented UI at a major Midwestern medical facility. Results Physicians’ cognitive challenges were summarized in four cognitive requirements and 13 design guidelines. As a result, two UI prototypes were developed to support order template search and completion. To compare UIs, 30 clinicians (referrers) participated in a consultation ordering simulation complemented with the think-aloud elicitation method. Oral comments about the UIs were coded for both content and valence (i.e., positive, neutral, or negative). Across 619 comments, the odds ratio for the UI prototype to elicit higher-valenced comments than the implemented UI was 13.5 (95% CI = [9.2, 19.8]), p < .001. Conclusion This study reinforced the significance of applying a CSE design approach to inform the design of health information technology. In addition, knowledge elicitation methods enabled identification of physicians’ cognitive requirements and challenges when completing electronic medical consultation orders. The resultant knowledge was used to derive design guidelines and UI prototypes that were more useful and usable for referring physicians. Our results support the implementation of a CSE design approach for electronic medical consultation orders.