Provider comments reveal barriers to EHR nudge effectiveness: process evaluation of a null deprescribing trial

De-implementation-reducing low-value or harmful care-is critical but difficult in clinical practice. Clinical decision support (CDS) "nudges" in electronic health records (EHRs) aim to promote guideline-concordant deprescribing, but effects are inconsistent. In a pragmatic randomized controlled trial across a large health system, we tested a suite of EHR-based CDS nudges to support Choosing Wisely-aligned deprescribing of glycemic medications in older adults with type 2 diabetes. Although a prior pilot showed modest improvement in guideline concordance (5.1%), the full trial found no significant changes in prescribing; this process evaluation examines clinicians' comments on alerts to explain why.

We conducted a mixed-methods process evaluation of comments within EHR-based alerts from a null-result RCT that promoted Choosing Wisely deprescribing for older adults with type 2 diabetes. Among 66,634 alerts firing across EHR encounters (December 2016-July 2023), providers commented on 764 (1.2%). Two researchers independently coded comments using reflexive thematic analysis, identifying four themes (three negative). Exploratory logistic and multinomial regressions examined predictors of commenting, valence, and themes among acknowledged firings, adjusting for patient, provider, and encounter factors.

Thematic analysis of comments revealed three barriers to deprescribing: (1) disagreement with Choosing Wisely guidelines (308 comments, e.g., perceived low overtreatment risk); (2) workflow misalignment (203 comments, e.g., wrong provider responsibility); and (3) patient preferences (69 comments). Logistic regression showed multiple concurrent OPAs reduced action odds by 31.6% (OR 0.684, 95% CI 0.560-0.835); comments were 2.57 times more likely to be negative than positive (OR 2.565, 95% CI 1.637-4.018). Disparities in engagement were found, with female providers, patients, and socially vulnerable individuals less likely to comment.

This process evaluation demonstrates scalable real-time feedback for clinical decision support refinement in de-implementation, with regressions identifying context-specific predictors. Provider disagreement, alert firings misaligned to workflows, and patient resistance hinder effectiveness. Future work should refine clinical decision support design to address complexity, enhance guideline explainability to build provider concordance, align with provider roles and workflows, and include patient-centered approaches.

The NYU School of Medicine Institutional Review Board (i17-01308) approved the trial, which has the clinicaltrials.gov ID NCT04181307 (https://clinicaltrials.gov/study/NCT04181307), with a first record date of November 26, 2019.