Appl Clin Inform 2010; 01(04): 466-485
DOI: 10.4338/ACI-2010-05-RA-0029
Research Article
Schattauer GmbH

Impact of Clinical Reminder Redesign on Physicians’ Priority Decisions

Sze-jung Wu
1  School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA
,
Mark R. Lehto
1  School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA
,
Yuehwern Yih
1  School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA
,
Jason J. Saleem
2  VA HSR&D Center on Implementing Evidence-based Practice, Roudebush VAMC, Indianapolis, IN 46202, USA
3  School of Engineering & Technology, IUPUI, Indianapolis, IN 46202, USA
4  IU Center for Health Services & Outcomes Research, Regenstrief Institute, Indianapolis, IN 46202, USA
,
B.N. Doebbeling
2  VA HSR&D Center on Implementing Evidence-based Practice, Roudebush VAMC, Indianapolis, IN 46202, USA
4  IU Center for Health Services & Outcomes Research, Regenstrief Institute, Indianapolis, IN 46202, USA
5  Department of Medicine, IU School of Medicine, Indianapolis, IN 46202, USA
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Weitere Informationen

Correspondence to:

Yuehwern Yih, Ph.D.
School of Industrial Engineering
Purdue University
315 N. Grant Street
West Lafayette, IN 47907
Telefon: (765) 494-0826   
Fax: (765) 494-1212   

Publikationsverlauf

received: 05. Mai 2010

accepted: 10. Dezember 2010

Publikationsdatum:
16. Dezember 2017 (online)

 

Summary

Objective: Computerized clinical reminder (CCR) systems can improve preventive service delivery by providing patient-specific reminders at the point of care. However, adherence varies between individual CCRs and is correlated to resolution time amongst other factors. This study aimed to evaluate how a proposed CCR redesign providing information explaining why the CCRs occurred would impact providers’ prioritization of individual CCRs.

Design: Two CCR designs were prototyped to represent the original and the new design, respectively. The new CCR design incorporated a knowledge-based risk factor repository, a prioritization mechanism, and a role-based filter. Sixteen physicians participated in a controlled experiment to compare the use of the original and the new CCR systems. The subjects individually simulated a scenario-based patient encounter, followed by a semi-structured interview and survey.

Measurements: We collected and analyzed the order in which the CCRs were prioritized, the perceived usefulness of each design feature, and semi-structured interview data.

Results: We elicited the prioritization heuristics used by the physicians, and found a CCR system needed to be relevant, easy to resolve, and integrated with workflow. The redesign impacted 80% of physicians and 44% of prioritization decisions. Decisions were no longer correlated to resolution time given the new design. The proposed design features were rated useful or very useful.

Conclusion: This study demonstrated that the redesign of a CCR system using a knowledge-based risk factor repository, a prioritization mechanism, and a role-based filter can impact clinicians’ decision making. These features are expected to ultimately improve the quality of care and patient safety.


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Conflict of interest Statement

The authors declare no conflict of interest in the study.


Correspondence to:

Yuehwern Yih, Ph.D.
School of Industrial Engineering
Purdue University
315 N. Grant Street
West Lafayette, IN 47907
Telefon: (765) 494-0826   
Fax: (765) 494-1212