Distinct components of alert fatigue in physicians' responses to a noninterruptive clinical decision support alert

J Am Med Inform Assoc. 2022 Dec 13;30(1):64-72. doi: 10.1093/jamia/ocac191.

Abstract

Objective: Clinical decision support (CDS) alerts may improve health care quality but "alert fatigue" can reduce provider responsiveness. We analyzed how the introduction of competing alerts affected provider adherence to a single depression screening alert.

Materials and methods: We analyzed the audit data from all occurrences of a CDS alert at a large academic health system. For patients who screen positive for depression during ambulatory visits, a noninterruptive alert was presented, offering a number of relevant documentation actions. Alert adherence was defined as the selection of any option offered within the alert. We assessed the effect of competing clinical guidance alerts presented during the same encounter and the total of all CDS alerts that the same provider had seen in the prior 90 days, on the probability of depression screen alert adherence, adjusting for physician and patient characteristics.

Results: The depression alert fired during 55 649 office visits involving 418 physicians and 40 474 patients over 41 months. After adjustment, physicians who had seen the most alerts in the prior 90 days were much less likely to respond (adjusted OR highest-lowest quartile, 0.38; 95% CI 0.35-0.42; P < .001). Competing alerts in the same visit further reduced the likelihood of adherence only among physicians in the middle two quartiles of alert exposure in the prior 90 days.

Conclusions: Adherence to a noninterruptive depression alert was strongly associated with the provider's cumulative alert exposure over the past quarter. Health systems should monitor providers' recent alert exposure as a measure of alert fatigue.

Keywords: alert; alert fatigue; clinical decision support; depression; physicians; regression modeling.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Decision Support Systems, Clinical*
  • Electronic Health Records
  • Humans
  • Medical Order Entry Systems*
  • Physicians*