J Hudspeth1, R El-Kareh2, G Schiff3. 1. Department of Medicine, Boston University , Boston, MA, United States. 2. Department of Medicine, University of California , San Diego, CA, United States. 3. Department of Medicine, Brigham and Women's Hospital , Boston, MA, United States.
Abstract
OBJECTIVE: Missed diagnoses are an important area of care quality resulting in significant morbidity and mortality. Determination of rates and causes has been limited by difficulties in screening, including the effort of manual chart review. We developed and tested a semi- automated review tool to expedite screening for diagnostic errors in an electronic health record (EHR). METHODS: We retrospectively reviewed patients seen in the emergency department (ED) of a teaching hospital over 31 days, using an automated screen to identify those with a prior in-system visit during the 14 days preceding their ED visit. We collected prior and subsequent notes from the institution's EHR for these cases, then populated a specially designed relational database enabling rapid comparison of prior visit records to the sentinel ED visit. Each case was assessed for potential missed or delayed diagnosis, and rated by likelihood as "definite, probable, possible, unlikely or none." RESULTS: A total of 5 066 patient encounters were screened by a clinician using the tool, of which 1 498 (30%) had a clinical encounter within the preceding 14 days. Of these, 37 encounters (2.6% of those reviewed) were "definite" or "probable" missed diagnoses. The rapid review tool took a mean of 1.9 minutes per case for primary review, compared with 11.2 minutes per case for reviews without the automated tool. CONCLUSIONS: Diagnostic errors were present in a significant number of cases presenting to the ED after recent healthcare visits. An innovative review tool enabled a substantially increased efficiency in screening for diagnostic errors.
OBJECTIVE: Missed diagnoses are an important area of care quality resulting in significant morbidity and mortality. Determination of rates and causes has been limited by difficulties in screening, including the effort of manual chart review. We developed and tested a semi- automated review tool to expedite screening for diagnostic errors in an electronic health record (EHR). METHODS: We retrospectively reviewed patients seen in the emergency department (ED) of a teaching hospital over 31 days, using an automated screen to identify those with a prior in-system visit during the 14 days preceding their ED visit. We collected prior and subsequent notes from the institution's EHR for these cases, then populated a specially designed relational database enabling rapid comparison of prior visit records to the sentinel ED visit. Each case was assessed for potential missed or delayed diagnosis, and rated by likelihood as "definite, probable, possible, unlikely or none." RESULTS: A total of 5 066 patient encounters were screened by a clinician using the tool, of which 1 498 (30%) had a clinical encounter within the preceding 14 days. Of these, 37 encounters (2.6% of those reviewed) were "definite" or "probable" missed diagnoses. The rapid review tool took a mean of 1.9 minutes per case for primary review, compared with 11.2 minutes per case for reviews without the automated tool. CONCLUSIONS: Diagnostic errors were present in a significant number of cases presenting to the ED after recent healthcare visits. An innovative review tool enabled a substantially increased efficiency in screening for diagnostic errors.
Entities:
Keywords:
Monitoring and surveillance; data processing; diagnostic error; emergency and disaster care; error management and prevention; human-computer inter action
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