Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2022 Aug 22;9(4):446-457.
doi: 10.1515/dx-2022-0032. eCollection 2022 Nov 1.

A structured approach to EHR surveillance of diagnostic error in acute care: an exploratory analysis of two institutionally-defined case cohorts

Maria A Malik  1 , Daniel Motta-Calderon  1   2 , Nicholas Piniella  1 , Alison Garber  1 , Kaitlyn Konieczny  1 , Alyssa Lam  1 , Savanna Plombon  1 , Kevin Carr  1 , Catherine Yoon  1 , Jacqueline Griffin  3 , Stuart Lipsitz  1   4 , Jeffrey L Schnipper  1   4 , David W Bates  1   4 , Anuj K Dalal  1   4
Affiliations
Review

A structured approach to EHR surveillance of diagnostic error in acute care: an exploratory analysis of two institutionally-defined case cohorts

Maria A Malik et al. Diagnosis (Berl). .

Abstract

Objectives: To test a structured electronic health record (EHR) case review process to identify diagnostic errors (DE) and diagnostic process failures (DPFs) in acute care.

Methods: We adapted validated tools (Safer Dx, Diagnostic Error Evaluation Research [DEER] Taxonomy) to assess the diagnostic process during the hospital encounter and categorized 13 postulated e-triggers. We created two test cohorts of all preventable cases (n=28) and an equal number of randomly sampled non-preventable cases (n=28) from 365 adult general medicine patients who expired and underwent our institution's mortality case review process. After excluding patients with a length of stay of more than one month, each case was reviewed by two blinded clinicians trained in our process and by an expert panel. Inter-rater reliability was assessed. We compared the frequency of DE contributing to death in both cohorts, as well as mean DPFs and e-triggers for DE positive and negative cases within each cohort.

Results: Twenty-seven (96.4%) preventable and 24 (85.7%) non-preventable cases underwent our review process. Inter-rater reliability was moderate between individual reviewers (Cohen's kappa 0.41) and substantial with the expert panel (Cohen's kappa 0.74). The frequency of DE contributing to death was significantly higher for the preventable compared to the non-preventable cohort (56% vs. 17%, OR 6.25 [1.68, 23.27], p<0.01). Mean DPFs and e-triggers were significantly and non-significantly higher for DE positive compared to DE negative cases in each cohort, respectively.

Conclusions: We observed substantial agreement among final consensus and expert panel reviews using our structured EHR case review process. DEs contributing to death associated with DPFs were identified in institutionally designated preventable and non-preventable cases. While e-triggers may be useful for discriminating DE positive from DE negative cases, larger studies are required for validation. Our approach has potential to augment institutional mortality case review processes with respect to DE surveillance.

Keywords: EHR surveillance; diagnostic error; e-triggers; mortality case review.

PubMed Disclaimer

Conflict of interest statement

Competing interests: Authors state no conflict of interest.

Figures

Figure 1:
Figure 1:
Consort diagram.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Patient Safety Network. Patient safety 101. Agency for healthcare research and quality . . 2019. https://psnet.ahrq.gov/primer/patient-safety-101 Available from:
    1. Shojania KG, Burton EC, McDonald KM, Goldman L. Changes in rates of autopsy-detected diagnostic errors over time: a systematic review. JAMA. 2003;289:2849–56. doi: 10.1001/jama.289.21.2849. - DOI - PubMed
    1. Singh H, Sittig DF. Advancing the science of measurement of diagnostic errors in healthcare: the Safer Dx framework. BMJ Qual Saf. 2015;24:103–10. doi: 10.1136/bmjqs-2014-003675. - DOI - PMC - PubMed
    1. Raffel KE, Kantor MA, Barish P, Esmaili A, Lim H, Xue F, et al. Prevalence and characterisation of diagnostic error among 7-day all-cause hospital medicine readmissions: a retrospective cohort study. BMJ Qual Saf. 2020 doi: 10.1136/bmjqs-2020-010896. - DOI - PubMed
    1. Graber ML. The incidence of diagnostic error in medicine. BMJ Qual Saf. 2013;22:ii21–7. doi: 10.1136/bmjqs-2012-001615. - DOI - PMC - PubMed

Publication types

LinkOut - more resources