Development of a Risk Index for Serious Prescription Opioid-Induced Respiratory Depression or Overdose in Veterans' Health Administration Patients

Barbara Zedler, Lin Xie, Li Wang, Andrew Joyce, Catherine Vick, Janet Brigham, Furaha Kariburyo, Onur Baser, Lenn Murrelle

Research output: Contribution to journalArticle

57 Scopus citations

Abstract

Objective: Develop a risk index to estimate the likelihood of life-threatening respiratory depression or overdose among medical users of prescription opioids. Subjects, Design, and Methods: A case-control analysis of administrative health care data from the Veterans' Health Administration identified 1,877,841 patients with a pharmacy record for an opioid prescription between October 1, 2010 and September 30, 2012. Overdose or serious opioid-induced respiratory depression (OSORD) occurred in 817. Ten controls were selected per case (n=8,170). Items for an OSORD risk index (RIOSORD) were selected through logistic regression modeling, with point values assigned to each predictor. Modeling of risk index scores produced predicted probabilities of OSORD; risk classes were defined by the predicted probability distribution. Results: Fifteen variables most highly associated with OSORD were retained as items, including mental health disorders and pharmacotherapy; impaired drug metabolism or excretion; pulmonary disorders; specific opioid characteristics; and recent hospital visits. The average predicted probability of experiencing OSORD ranged from 3% in the lowest risk decile to 94% in the highest, with excellent agreement between predicted and observed incidence across risk classes. The model's C-statistic was 0.88 and Hosmer-Lemeshow goodness-of-fit statistic 10.8 (P>0.05). Conclusion: RIOSORD performed well in identifying medical users of prescription opioids within the Veterans' Health Administration at elevated risk of overdose or life-threatening respiratory depression, those most likely to benefit from preventive interventions. This novel, clinically practical, risk index is intended to provide clinical decision support for safer pain management. It should be assessed, and refined as necessary, in a more generalizable population, and prospectively evaluated.

Original languageEnglish (US)
Pages (from-to)1566-1579
Number of pages14
JournalPain Medicine (United States)
Volume16
Issue number8
DOIs
StatePublished - Aug 1 2015
Externally publishedYes

Keywords

  • Index
  • Opioid
  • Overdose
  • Questionnaire
  • Respiratory Depression
  • Risk

ASJC Scopus subject areas

  • Clinical Neurology
  • Anesthesiology and Pain Medicine

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