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Electronic health record-based surveillance of diagnostic errors in primary care
  1. Hardeep Singh1,
  2. Traber Davis Giardina1,
  3. Samuel N Forjuoh2,
  4. Michael D Reis2,
  5. Steven Kosmach3,
  6. Myrna M Khan1,
  7. Eric J Thomas4
  1. 1Houston VA HSR&D Center of Excellence, Michael E DeBakey Veterans Affairs Medical Center and the Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
  2. 2Department of Family & Community Medicine, Scott & White Healthcare, Texas A&M Health Science Center, College of Medicine, Temple, Texas, USA
  3. 3Division of Biostatistics, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
  4. 4University of Texas at Houston – Memorial Hermann Center for Healthcare Quality and Safety, and Division of General Medicine, Department of Medicine, University of Texas Medical School at Houston, Houston, Texas, USA
  1. Correspondence to Hardeep Singh, Baylor College of Medicine, VA Medical Center (152), 2002 Holcombe Blvd, Houston, TX 77030, USA; hardeeps{at}


Background Diagnostic errors in primary care are harmful but difficult to detect. The authors tested an electronic health record (EHR)-based method to detect diagnostic errors in routine primary care practice.

Methods The authors conducted a retrospective study of primary care visit records ‘triggered’ through electronic queries for possible evidence of diagnostic errors: Trigger 1: A primary care index visit followed by unplanned hospitalisation within 14 days and Trigger 2: A primary care index visit followed by ≥1 unscheduled visit(s) within 14 days. Control visits met neither criterion. Electronic trigger queries were applied to EHR repositories at two large healthcare systems between 1 October 2006 and 30 September 2007. Blinded physician–reviewers independently determined presence or absence of diagnostic errors in selected triggered and control visits. An error was defined as a missed opportunity to make or pursue the correct diagnosis when adequate data were available at the index visit. Disagreements were resolved by an independent third reviewer.

Results Queries were applied to 212 165 visits. On record review, the authors found diagnostic errors in 141 of 674 Trigger 1-positive records (positive predictive value (PPV)=20.9%, 95% CI 17.9% to 24.0%) and 36 of 669 Trigger 2-positive records (PPV=5.4%, 95% CI 3.7% to 7.1%). The control PPV of 2.1% (95% CI 0.1% to 3.3%) was significantly lower than that of both triggers (p≤0.002). Inter-reviewer reliability was modest, though higher than in comparable previous studies (к=0.37 (95% CI 0.31 to 0.44)).

Conclusions While physician agreement on diagnostic error remains low, an EHR-facilitated surveillance methodology could be useful for gaining insight into the origin of these errors.

  • Diagnostic errors
  • primary care
  • patient safety
  • electronic health records
  • triggers
  • automated surveillance
  • error detection
  • information technology
  • trigger tools
  • diagnostic errors
  • health services research
  • diabetes mellitus
  • statistical process control
  • statistics
  • simulation
  • quality improvement methodologies
  • healthcare quality improvement
  • teamwork
  • safety culture
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  • The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs or any other funding agency.

  • Funding The study was supported by an NIH K23 career development award (K23CA125585) to HS, Agency for Health Care Research and Quality Health Services Research Demonstration and Dissemination Grant (R18HS17244-02) to EJT and in part by the Houston VA HSR&D Center of Excellence (HFP90-020). These sources had no role in the design and conduct of the study; collection, management, analysis and interpretation of the data; and preparation, review or approval of the manuscript.

  • Competing interests None.

  • Ethics approval Baylor College of Medicine IRB.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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