Evaluation of a Korean version of a tool for assessing the incorporation of human factors into a medication-related decision support system: the I-MeDeSA

I. Cho; J. Lee; H. Han; S. Phansalkar; D.W. Bates

doi:10.4338/ACI-2014-01-RA-0005

Applied Clinical Informatics, Inhaltsverzeichnis

Appl Clin Inform 2014; 05(02): 571-588
DOI: 10.4338/ACI-2014-01-RA-0005

Research Article

Schattauer GmbH

Evaluation of a Korean version of a tool for assessing the incorporation of human factors into a medication-related decision support system: the I-MeDeSA

I. Cho

¹Department of Nursing, School of Medicine, Inha University, Incheon, Korea

²Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, MA, USA

³Harvard Medical School, Boston, MA, USA

,

J. Lee

²Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, MA, USA

³Harvard Medical School, Boston, MA, USA

⁴Department of Emergency Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea

⁵Department of Biomedical Informatics, Asan Medical Center, Seoul, Korea

,

H. Han

⁶Department of Pharmacy, Asan Medical Center, Seoul, Korea

,

S. Phansalkar

²Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, MA, USA

³Harvard Medical School, Boston, MA, USA

⁷Partners Healthcare Systems, Wellesley, MA, USA

⁸Wolters Kluwer Health, Indianapolis, IN, USA

,

D.W. Bates

²Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, MA, USA

³Harvard Medical School, Boston, MA, USA

⁷Partners Healthcare Systems, Wellesley, MA, USA

› Institutsangaben

Abstract

Summary

Objective: The Instrument for Evaluating Human-Factor Principles in Medication-Related Decision Support Alerts (I-MeDeSA) was developed recently in the US with a view towards improving considerations of human-factor principles when designing alerts for clinical decision support (CDS) systems. This study evaluated the generalizability of this tool, in cooperation with its authors, across cultures by applying it to a Korean system. We also examined opportunities to promote user acceptance of the system.

Methods: We developed a Korean version of the I-MeDeSA (K-I-MeDeSA) and used it to evaluate drug-drug interaction alerts in a large academic tertiary hospital in Seoul. We involved four reviewers (A, B, C, and D). Two (A and B) conducted the initial independent scoring, while the other two (C and D) performed a final review and assessed feedback from the initial reviewers. The obtained scores were compared with those from 13 previously reported CDS systems. The feedback was summarized qualitatively.

Results: The translation of the I-MeDeSA had excellent interrater agreement in terms of face validity (scale-level content validity index = 0.95). The system’s K-I-MeDeSA score was 10 out of 26, with a good agreement between reviewers (κ = 0.77), which showed a lack of human-factor considerations. The reviewers readily identified two of the nine principles that needed primary improvement: prioritization and text-based information. The reviewers also expressed difficulty judging the following four principles: alarm philosophy, visibility, color, and learnability and confusability. Conclusion: The K-I-MeDeSA was semantically and operationally equivalent to the original tool. Only minor cultural problems were identified, leading the reviewers to suggest the need for clarification of certain words plus a more detailed description of the tool’s rationale and exemplars. Further evaluation is needed to empirically assess whether the implementation of changes in an electronic health record system could improve the adoption of CDS alerts.

Citation: Cho I, Lee J, Han H, Phansalkar S, Bates DW. Evaluation of a Korean version of a tool for assessing the incorporation of human factors into a medicationrelated decision support system: the I-MeDeSA. Appl Clin Inf 2014; 5: 571–588 http://dx.doi.org/10.4338/ACI-01-RA-0005

Keywords

Clinical decision support - interfaces and usability - human-computer interaction - computerized order entry - alert fatigue

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Referenzen

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