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Electronic Health Record-Based Screening for Substance Abuse.

Farrokh Alemi1, Sanja Avramovic1, Mark D Schwartz2

  • 1Health Informatics Program, Department of Health Administration and Policy, George Mason University, Fairfax, Virginia.

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|October 5, 2018
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Summary

Predictive modeling using electronic health records (EHRs) can effectively screen for substance abuse. This approach accurately identifies current and potential substance use disorders in large veteran populations.

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opioid abusepredictive modelsprescription abusescreeningsubstance abuseveterans

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Area of Science:

  • Health Informatics
  • Predictive Analytics
  • Public Health

Background:

  • Traditional substance abuse screening methods in primary care are challenging to implement.
  • Electronic Health Records (EHRs) contain vast amounts of data that can be leveraged for health assessments.

Purpose of the Study:

  • To evaluate the efficacy of predictive modeling using EHR data for substance abuse screening.
  • To assess the accuracy of a modified naive Bayes model in identifying substance abuse.

Main Methods:

  • Utilized a large dataset from Veterans Affairs Informatics and Computing Infrastructure (VINCI) (2006-2016).
  • Employed a modified naive Bayes model to predict substance abuse based on inpatient and outpatient diagnoses and demographic data.
  • Validated model accuracy using the area under the receiver operating characteristic (AROC) curve.

Main Results:

  • The predictive model demonstrated high accuracy in identifying substance abuse: AROC of 0.884 for inpatient, 0.825 for outpatient, and 0.840 for combined data.
  • Cross-validated accuracy remained robust even when excluding data post-diagnosis (AROC 0.822 inpatient, 0.817 outpatient).
  • Numerous physical and mental illnesses were significantly associated with substance abuse, aligning with existing literature.

Conclusions:

  • EHR data is a valuable resource for detecting existing substance abuse.
  • Predictive modeling using EHR data offers a promising tool for identifying individuals at risk of future substance abuse.
  • This methodology can enhance substance abuse screening in healthcare settings.