Predictive Models for Time to First Opioid Use Disorder or Opioid Overdose Among Older Adults - Scorecard - MDSpire

Forecasting Models for Initial Onset of Opioid Use Disorder or Overdose in the Elderly Population

  • By

  • Chien-Wei Chiang

  • Guy Brock

  • Siegfried Schmidt

  • Roger B. Fillingim

  • Stephan Schmidt

  • Yu-Jung Jenny Wei

  • July 16, 2026

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Clinical Scorecard: Forecasting Models for Initial Onset of Opioid Use Disorder or Overdose in the Elderly Population

At a Glance

CategoryDetail
ConditionOpioid Use Disorder (OUD) and Opioid Overdose (OD)
Key MechanismsMisuse of prescription opioids is the primary pathway leading to OUD or OD among older adults.
Target PopulationOlder adults aged 65 years or older with chronic pain and prescribed opioid therapy.
Care SettingPrognostic study using longitudinal cohort data linked with Medicare claims.

Key Highlights

  • Age-adjusted rate of deaths involving synthetic opioids increased 14-fold from 2000 to 2020 among older adults.
  • High-risk opioid use occurs in less than 5% of older adults before OUD or OD onset.
  • Current prediction models primarily developed for younger adults may not apply to older individuals.
  • Patient-reported factors such as pain intensity and depressive symptoms are potential predictors of OUD or OD.
  • The study utilized survival analyses to predict time to first OUD or OD.

Guideline-Based Recommendations

Diagnosis

  • Use a conservative algorithm to define OUD based on inpatient and outpatient encounter criteria.

Management

  • Monitor prescription opioid use and assess for factors such as uncontrolled pain.

Monitoring & Follow-up

  • Follow up on patients with chronic pain receiving opioid prescriptions for signs of OUD or OD.

Risks

  • Consider the unique risk factors for OUD or OD in older adults, distinct from younger populations.

Patient & Prescribing Data

Older adults aged 65 years or older with chronic pain.

Less than 5% of older adults exhibit high-risk opioid use prior to OUD or OD onset.

Clinical Best Practices

  • Incorporate patient-reported measures in assessing risk for OUD or OD.
  • Utilize longitudinal data to account for time-varying predictors in older adults.

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