Improving Allergy Documentation: A Retrospective Electronic Health Record System-Wide Patient Safety Initiative.
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ABSTRACT: Objectives
Documentation of allergies in a coded, non-free-text format in the electronic health record (EHR) triggers clinical decision support to prevent adverse events. Health system-wide patient safety initiatives to improve EHR allergy documentation by specifically decreasing free-text allergy entries have not been reported. The goal of this initiative was to systematically reduce free-text allergen entries in the EHR allergy module.Methods
We assessed free-text allergy entries in a commercial EHR used at a multihospital integrated health care system in the greater Boston area. Using both manual and automated methods, a multidisciplinary consensus group prioritized high-risk and frequently used free-text allergens for conversion to coded entries, added new allergen entries, and deleted duplicate allergen entries. Environmental allergies were moved to the patient problem list.Results
We identified 242,330 free-text entries, which included a variety of environmental allergies (42%), food allergies (18%), contrast media allergies (13%), "no known allergy" (12%), drug allergies (2%), and "no contrast allergy" (2%). Most free-text entries were entered by medical assistants in ambulatory settings (34%) and registered nurses in perioperative settings (20%). We remediated a total of 52,206 free-text entries with automated methods and 79,578 free-text entries with manual methods.Conclusions
Through this multidisciplinary intervention, we identified and remediated 131,784 free-text entries in our EHR to improve clinical decision support and patient safety. Additional strategies are required to completely eliminate free-text allergy entry, and establish systematic, consistent, and safe guidelines for documenting allergies.
SUBMITTER: Li L
PROVIDER: S-EPMC7704710 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ImportanceElectronic health records are a potentially valuable source of information for identifying patients with opioid use disorder (OUD).ObjectiveTo evaluate whether proxy measures from electronic health record data can be used reliably to identify patients with probable OUD based on Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) criteria.Design, setting, and participantsThis retrospective cross-sectional study analyzed individuals within the Geisinger health system who were prescribed opioids between December 31, 2000, and May 31, 2017, using a mixed-methods approach. The cohort was identified from 16 253 patients enrolled in a contract-based, Geisinger-specific medication monitoring program (GMMP) for opioid use, including patients who maintained or violated contract terms, as well as a demographically matched control group of 16 253 patients who were prescribed opioids but not enrolled in the GMMP. Substance use diagnoses and psychiatric comorbidities were assessed using automated electronic health record summaries. A manual medical record review procedure using DSM-5 criteria for OUD was completed for a subset of patients. The analysis was conducted beginning from June 5, 2017, until May 29, 2020.Main outcomes and measuresThe primary outcome was the prevalence of OUD as defined by proxy measures for DSM-5 criteria for OUD as well as the prevalence of comorbidities among patients prescribed opioids within an integrated health system.ResultsAmong the 16 253 patients enrolled in the GMMP (9309 women [57%]; mean [SD] age, 52 [14] years), OUD diagnoses as defined by diagnostic codes were present at a much lower rate than expected (291 [2%]), indicating the necessity for alternative diagnostic strategies. The DSM-5 criteria for OUD can be assessed using manual medical record review; a manual review of 200 patients in the GMMP and 200 control patients identifed a larger percentage of patients with probable moderate to severe OUD (GMMP, 145 of 200 [73%]; and control, 27 of 200 [14%]) compared with the prevalence of OUD assessed using diagnostic codes.Conclusions and relevanceThese results suggest that patients with OUD may be identified using information available in the electronic health record, even when diagnostic codes do not reflect this diagnosis. Furthermore, the study demonstrates the utility of coding for DSM-5 criteria from medical records to generate a quantitative DSM-5 score that is associated with OUD severity.
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