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Development and validation of an electronic health records-based opioid use disorder algorithm by expert clinical adjudication among patients with prescribed opioids.

Publication ,  Journal Article
Ranapurwala, SI; Alam, IZ; Pence, BW; Carey, TS; Christensen, S; Clark, M; Chelminski, PR; Wu, L-T; Greenblatt, LH; Korte, JE; Wolfson, M ...
Published in: Pharmacoepidemiol Drug Saf
May 2023

BACKGROUND: In the US, over 200 lives are lost from opioid overdoses each day. Accurate and prompt diagnosis of opioid use disorders (OUD) may help prevent overdose deaths. However, international classification of disease (ICD) codes for OUD are known to underestimate prevalence, and their specificity and sensitivity are unknown. We developed and validated algorithms to identify OUD in electronic health records (EHR) and examined the validity of OUD ICD codes. METHODS: Through four iterations, we developed EHR-based OUD identification algorithms among patients who were prescribed opioids from 2014 to 2017. The algorithms and OUD ICD codes were validated against 169 independent "gold standard" EHR chart reviews conducted by an expert adjudication panel across four healthcare systems. After using 2014-2020 EHR for validating iteration 1, the experts were advised to use 2014-2017 EHR thereafter. RESULTS: Of the 169 EHR charts, 81 (48%) were reviewed by more than one expert and exhibited 85% expert agreement. The experts identified 54 OUD cases. The experts endorsed all 11 OUD criteria from the Diagnostic and Statistical Manual of Mental Disorders-5, including craving (72%), tolerance (65%), withdrawal (56%), and recurrent use in physically hazardous conditions (50%). The OUD ICD codes had 10% sensitivity and 99% specificity, underscoring large underestimation. In comparison our algorithm identified OUD with 23% sensitivity and 98% specificity. CONCLUSIONS AND RELEVANCE: This is the first study to estimate the validity of OUD ICD codes and develop validated EHR-based OUD identification algorithms. This work will inform future research on early intervention and prevention of OUD.

Duke Scholars

Published In

Pharmacoepidemiol Drug Saf

DOI

EISSN

1099-1557

Publication Date

May 2023

Volume

32

Issue

5

Start / End Page

577 / 585

Location

England

Related Subject Headings

  • Pharmacology & Pharmacy
  • Opioid-Related Disorders
  • Humans
  • Electronic Health Records
  • Drug Overdose
  • Delivery of Health Care
  • Analgesics, Opioid
  • Algorithms
  • 4202 Epidemiology
  • 3214 Pharmacology and pharmaceutical sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Ranapurwala, S. I., Alam, I. Z., Pence, B. W., Carey, T. S., Christensen, S., Clark, M., … Marshall, S. W. (2023). Development and validation of an electronic health records-based opioid use disorder algorithm by expert clinical adjudication among patients with prescribed opioids. Pharmacoepidemiol Drug Saf, 32(5), 577–585. https://doi.org/10.1002/pds.5591
Ranapurwala, Shabbar I., Ishrat Z. Alam, Brian W. Pence, Timothy S. Carey, Sean Christensen, Marshall Clark, Paul R. Chelminski, et al. “Development and validation of an electronic health records-based opioid use disorder algorithm by expert clinical adjudication among patients with prescribed opioids.Pharmacoepidemiol Drug Saf 32, no. 5 (May 2023): 577–85. https://doi.org/10.1002/pds.5591.
Ranapurwala SI, Alam IZ, Pence BW, Carey TS, Christensen S, Clark M, et al. Development and validation of an electronic health records-based opioid use disorder algorithm by expert clinical adjudication among patients with prescribed opioids. Pharmacoepidemiol Drug Saf. 2023 May;32(5):577–85.
Ranapurwala, Shabbar I., et al. “Development and validation of an electronic health records-based opioid use disorder algorithm by expert clinical adjudication among patients with prescribed opioids.Pharmacoepidemiol Drug Saf, vol. 32, no. 5, May 2023, pp. 577–85. Pubmed, doi:10.1002/pds.5591.
Ranapurwala SI, Alam IZ, Pence BW, Carey TS, Christensen S, Clark M, Chelminski PR, Wu L-T, Greenblatt LH, Korte JE, Wolfson M, Douglas HE, Bowlby LA, Capata M, Marshall SW. Development and validation of an electronic health records-based opioid use disorder algorithm by expert clinical adjudication among patients with prescribed opioids. Pharmacoepidemiol Drug Saf. 2023 May;32(5):577–585.

Published In

Pharmacoepidemiol Drug Saf

DOI

EISSN

1099-1557

Publication Date

May 2023

Volume

32

Issue

5

Start / End Page

577 / 585

Location

England

Related Subject Headings

  • Pharmacology & Pharmacy
  • Opioid-Related Disorders
  • Humans
  • Electronic Health Records
  • Drug Overdose
  • Delivery of Health Care
  • Analgesics, Opioid
  • Algorithms
  • 4202 Epidemiology
  • 3214 Pharmacology and pharmaceutical sciences