User-Centered Development of a Behavioral Economics Inspired Electronic Health Record Clinical Decision Support Module

Changing physician behaviors is difficult. Electronic health record (EHR) clinical decision support (CDS) offers an opportunity to promote guideline adherence. Behavioral economics (BE) has shown success as an approach to supporting evidence-based decision-making with little additional cognitive burden. We applied a user-centered approach to incorporate BE “nudges” into a CDS module in two “vanguard” sites utilizing: (1) semi-structured interviews with key informants (n=8); (2) a design thinking workshop; and (3) semi-structured group interviews with clinicians. In the 133 day development phase at two clinics, the navigator section fired 299 times for 27 unique clinicians. The inbasket refill alert fired 124 times for 22 clinicians. Fifteen prescriptions for metformin were written by 11 clinicians. Our user-centered approach yielded a BE- driven CDS module with relatively high utilization by clinicians. Next steps include the addition of two modules and continued tracking of utilization, and assessment of clinical impact of the module.

[1]  P. Gollwitzer,et al.  Changing Physician Behavior With Implementation Intentions: Closing the Gap Between Intentions and Actions. , 2016, Academic medicine : journal of the Association of American Medical Colleges.

[2]  D. Mann,et al.  User Centered Clinical Decision Support Tools , 2014, Applied Clinical Informatics.

[3]  F. McAlister,et al.  Treated glycosylated hemoglobin levels in individuals with diabetes mellitus vary little by health status , 2016, Medicine.

[4]  Mohamed Khalifa,et al.  Improving Utilization of Clinical Decision Support Systems by Reducing Alert Fatigue: Strategies and Recommendations , 2016, ICIMTH.

[5]  L. Moja,et al.  Effectiveness of computerized decision support systems linked to electronic health records: a systematic review and meta-analysis. , 2014, American journal of public health.

[6]  Sei J. Lee,et al.  Potential overtreatment of diabetes mellitus in older adults with tight glycemic control. , 2015, JAMA internal medicine.

[7]  D. Berwick.  American Geriatrics Society Identifies Five Things That Healthcare Providers and Patients Should Question , 2013, Journal of the American Geriatrics Society.

[8]  R. Hess,et al.  Design and implementation of electronic health record integrated clinical prediction rules (iCPR): a randomized trial in diverse primary care settings , 2017, Implementation Science.

[9]  V. Montori,et al.  Intensive Treatment and Severe Hypoglycemia Among Adults With Type 2 Diabetes. , 2016, JAMA internal medicine.

[10]  V. Hasselblad,et al.  Effect of Clinical Decision-Support Systems , 2012, Annals of Internal Medicine.

[11]  Devin M Mann,et al.  Rationale, design, and implementation protocol of an electronic health record integrated clinical prediction rule (iCPR) randomized trial in primary care , 2011, Implementation science : IS.

[12]  Devin M Mann,et al.  Innovating From Within: A Process Model for User-Centered Digital Development in Academic Medical Centers , 2018, JMIR human factors.