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Development of a 5-Step Electronic Medical Record-Based Algorithm to Identify Patients with Opioid Use Disorder in
Kimberly Fryer1, Chinyere N Reid1, Chaitanya Chaphalkar1
1University of South Florida, Tampa, Florida.
Objectives:
This study aimed to develop and validate an algorithm for the identification of opioid use disorder (OUD) in pregnant patients using electronic medical record (EMR) data.
Materials And Methods:
A cohort of pregnant patients from a single institution was used to develop and validate the algorithm. Five algorithm components were used, and chart reviews were conducted to confirm OUD diagnoses based on established criteria. Positive predictive values (PPV) of each of the algorithm's components were assessed.
Results:
Of the 334 charts identified by the algorithm, 256 true cases were confirmed. The overall PPV of the algorithm was 76.6%, with 100% accuracy for outpatient medication lists, and high PPVs ranging from 81.3% to 93.4% across other algorithm components.
Discussion And Conclusion:
The study highlights the significance of a multifaceted approach in identifying OUD among pregnant patients, aiming to improve patient care and target interventions for patients at risk.
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