Evidence That Nurses Need to Participate in Diagnosis: Lessons From Malpractice Claims.

Academic Article


  • OBJECTIVES: There is a pressing need for nurses to contribute as equals to the diagnostic process. The purpose of this article is twofold: (a) to describe the contributing factors in diagnosis-related and failure-to-monitor malpractice claims in which nurses are named the primary responsible party and (b) to describe actions healthcare leaders can take to enhance the role of nurses in diagnosis. METHODS: We conducted a review of the Controlled Risk Insurance Company Strategies' repository of malpractice claims, which contain approximately 30% of United States claims. We analyzed the malpractice claims related to diagnosis (n = 139) and physiologic monitoring (n = 647) naming nurses as the primary responsible party from 2007 to 2016. We used logistic regression to determine the association of contributing factors to likelihood of death, indemnity, and expenses incurred. RESULTS: Diagnosis-related cases listing communication among providers as a contributing factor were associated with a significantly higher likelihood of death (odds ratio [OR] = 3.01, 95% confidence interval [CI] = 1.50-6.03). Physiologic monitoring cases listing communication among providers as a contributing factor were associated with significantly higher likelihood of death (OR = 2.21, 95% CI = 1.49-3.27), higher indemnity incurred (U.S. $86,781, 95% CI = $18,058-$175,505), and higher expenses incurred (U.S. $20,575, 95% CI = $3685-$37,465). CONCLUSIONS: Nurses are held legally accountable for their role in diagnosis. Raising system-wide awareness of the critical role and responsibility of nurses in the diagnostic process and enhancing nurses' knowledge and skill to fulfill those responsibilities are essential to improving diagnosis.
  • Authors

  • Gleason, Kelly Therese
  • Jones, Rebecca
  • Rhodes, Christopher
  • Greenberg, Penny
  • Harkless, Gene
  • Goeschel, Chris
  • Cahill, Maureen
  • Graber, Mark
  • Status

    Publication Date

  • December 1, 2021
  • Published In


  • Clinical Competence
  • Humans
  • Insurance Claim Review
  • Logistic Models
  • Malpractice
  • Nursing Diagnosis
  • Retrospective Studies
  • United States
  • Digital Object Identifier (doi)

    Start Page

  • e959
  • End Page

  • e963
  • Volume

  • 17
  • Issue

  • 8