Rachel Richesson, associate professor; PhD student Brian Douthit; and Daniel Hatch, biostatistician III; published an article entitled "Measuring implementation feasibility of clinical decision support alerts for clinical practice recommendation" in the Journal of the American Medical Informatics Association. Co-authors include Catherine Staes, University of Utah College of Nursing; Traci Thoureen, Duke University Medical Center; Kensaku Kawamoto and Guilherme Del Fiol; University of Utah School of Medicine.

Abstract:

Objective: The study sought to describe key features of clinical concepts and data required to implement clinical practice recommendations as clinical decision support (CDS) tools in electronic health record systems and to identify recommendation features that predict feasibility of implementation.

Materials and Methods: Using semistructured interviews, CDS implementers and clinician subject matter experts from 7 academic medical centers rated the feasibility of implementing 10 American College of Emergency Physicians Choosing Wisely Recommendations as electronic health record-embedded CDS and estimated the need for additional data collection. Ratings were combined with objective features of the guidelines to develop a predictive model for technical implementation feasibility.

Results: A linear mixed model showed that the need for new data collection was predictive of lower implementation feasibility. The number of clinical concepts in each recommendation, need for historical data, and ambiguity of clinical concepts were not predictive of implementation feasibility.

Conclusions: The availability of data and need for additional data collection are essential to assess the feasibility of CDS implementation. Authors of practice recommendations and guidelines can enable organizations to more rapidly assess data availability and feasibility of implementation by including operational definitions for required data.