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Usability Evaluation and Implementation of a Health Information Technology Dashboard of Evidence-Based Quality Indicators

Schall, Mark Christopher Jr PhD, AEP; Cullen, Laura DNP, RN, FAAN; Pennathur, Priyadarshini PhD; Chen, Howard MS; Burrell, Keith BA; Matthews, Grace MSN, RN-BC

CIN: Computers, Informatics, Nursing: June 2017 - Volume 35 - Issue 6 - p 281–288
doi: 10.1097/CIN.0000000000000325
FEATURES

Health information technology dashboards that integrate evidence-based quality indicators can efficiently and accurately display patient risk information to promote early intervention and improve overall quality of patient care. We describe the process of developing, evaluating, and implementing a dashboard designed to promote quality care through display of evidence-based quality indicators within an electronic health record. Clinician feedback was sought throughout the process. Usability evaluations were provided by three nurse pairs and one physician from medical-surgical areas. Task completion times, error rates, and ratings of system usability were collected to compare the use of quality indicators displayed on the dashboard to the indicators displayed in a conventional electronic health record across eight experimental scenarios. Participants rated the dashboard as “highly usable” following System Usability Scale (mean, 87.5 [SD, 9.6]) and Poststudy System Usability Questionnaire (mean, 1.7 [SD, 0.5]) criteria. Use of the dashboard led to reduced task completion times and error rates in comparison to the conventional electronic health record for quality indicator–related tasks. Clinician responses to the dashboard display capabilities were positive, and a multifaceted implementation plan has been used. Results suggest application of the dashboard in the care environment may lead to improved patient care.

Author Affiliations: Department of Industrial and Systems Engineering, Auburn University, Alabama (Dr Schall); Department of Nursing Services and Patient Care, University of Iowa Hospitals and Clinics (Dr Cullen); Departments of Mechanical and Industrial Engineering (Dr Pennathur) and Occupational and Environmental Health (Mr Chen), University of Iowa; and Health Care Information Systems (Mr Burrell) and Department of Nursing Services and Patient Care (Ms Matthews), University of Iowa Hospitals and Clinics, Iowa City.

The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article.

Corresponding author: Mark Christopher Schall, Jr, PhD, AEP, Department of Industrial and Systems Engineering, Auburn University, 3301F Shelby Center for Engineering Technology, Auburn, AL 36849 (mark-schall@auburn.edu).

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