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Background <p>Diagnostic errors (DEs) are a major threat to hospital patient safety. Identifying admission-based predictors associated with harmful DEs may help improve diagnostic safety in high-risk populations.</p> Objective <p>To assess the association between admission-based predictors derived from structured electronic health record (EHR) data with harmful DEs in high-risk patients receiving general medical care in the hospital.</p> Design <p>Retrospective multivariable analysis of a weighted sample of cases with and without harmful DE from a previously adjudicated cohort.</p> Participants <p>A weighted sample of 4750 high-risk cases (ICU transfers, 90-day deaths, or complex clinical events) of patients admitted to general medicine teams at a tertiary academic medical center between 2019 and 2021.</p> Main Measures <p>Estimated prevalence of harmful DE using inverse probability weighting. Adjusted weighted&#xa0;odds ratios (wORs) for six a priori admission-based predictors using multivariable logistic regression in the weighted sample and across subgroups.</p> Key Results <p>Among 569 sampled cases, 83 harmful DEs were identified, corresponding to a weighted prevalence of 9.1% (95% CI, 6.3–11.9). Having ≥ 2 ambulatory encounters within 14&#xa0;days before admission was independently associated with harmful DE (adjusted wOR, 2.26; 95% CI, 1.12–4.56; <i>p</i> = 0.02). The association between other predictors—including comorbidity burden, prior hospitalization, interhospital transfer, undifferentiated presenting symptoms, and admission to an advanced practice provider service—did not reach statistical significance with harmful DE.</p> Conclusions <p>Recent ambulatory care activity was associated with twice the odds of harmful DE among high-risk patients during hospitalization. Patterns of pre-admission care represent an important signal of vulnerability for proactive diagnostic safety surveillance in this population.</p>

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Frequent Ambulatory Care Visits Predict Harmful Diagnostic Errors in High-Risk Hospitalized Patients: a Retrospective Cohort Study

  • 期刊论文

  • 发表日期：

    2026年5月22日

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  • Abhishek Goyal,
  • Kaitlyn Konieczny,
  • Savanna Plombon,
  • Jorge A. Rodriguez,
  • Marie Leeson,
  • Julie Fiskio,
  • Catherine Yoon,
  • Stuart R. Lipsitz,
  • Anuj K. Dalal

摘要

Background

Diagnostic errors (DEs) are a major threat to hospital patient safety. Identifying admission-based predictors associated with harmful DEs may help improve diagnostic safety in high-risk populations.

Objective

To assess the association between admission-based predictors derived from structured electronic health record (EHR) data with harmful DEs in high-risk patients receiving general medical care in the hospital.

Design

Retrospective multivariable analysis of a weighted sample of cases with and without harmful DE from a previously adjudicated cohort.

Participants

A weighted sample of 4750 high-risk cases (ICU transfers, 90-day deaths, or complex clinical events) of patients admitted to general medicine teams at a tertiary academic medical center between 2019 and 2021.

Main Measures

Estimated prevalence of harmful DE using inverse probability weighting. Adjusted weighted odds ratios (wORs) for six a priori admission-based predictors using multivariable logistic regression in the weighted sample and across subgroups.

Key Results

Among 569 sampled cases, 83 harmful DEs were identified, corresponding to a weighted prevalence of 9.1% (95% CI, 6.3–11.9). Having ≥ 2 ambulatory encounters within 14 days before admission was independently associated with harmful DE (adjusted wOR, 2.26; 95% CI, 1.12–4.56; p = 0.02). The association between other predictors—including comorbidity burden, prior hospitalization, interhospital transfer, undifferentiated presenting symptoms, and admission to an advanced practice provider service—did not reach statistical significance with harmful DE.

Conclusions

Recent ambulatory care activity was associated with twice the odds of harmful DE among high-risk patients during hospitalization. Patterns of pre-admission care represent an important signal of vulnerability for proactive diagnostic safety surveillance in this population.