Background: Risk of overdose, suicide, and other adverse outcomes are elevated among sub-populations prescribed opioid analgesics. To address this, the Veterans Health Administration (VHA) developed the Stratification Tool for Opioid Risk Mitigation (STORM)-a provider-facing dashboard that utilizes predictive analytics to stratify patients prescribed opioids based on risk for overdose/suicide.
Objective: To evaluate the impact of the case review mandate on serious adverse events (SAEs) and all-cause mortality among high-risk Veterans.
Design: A 23-month stepped-wedge cluster randomized controlled trial in all 140 VHA medical centers between 2018 and 2020.
Participants: A total of 44,042 patients actively prescribed opioid analgesics with high STORM risk scores (i.e., percentiles 1% to 5%) for an overdose or suicide-related event.
Intervention: A mandate requiring providers to perform case reviews on opioid analgesic-prescribed patients at high risk of overdose/suicide.
Main measures: Nine serious adverse events (SAEs), case review completion, number of risk mitigation strategies, and all-cause mortality.
Key results: Mandated review inclusion was associated with a significant decrease in all-cause mortality within 4 months of inclusion (OR: 0.78; 95% CI: 0.65-0.94). There was no detectable effect on SAEs. Stepped-wedge analyses found that mandated review patients were five times more likely to receive a case review than non-mandated patients with similar risk (OR: 5.1; 95% CI: 3.64-7.23) and received more risk mitigation strategies than non-mandated patients (0.498; CI: 0.39-0.61).
Conclusions: Among VHA patients prescribed opioid analgesics, identifying high risk patients and mandating they receive an interdisciplinary case review was associated with a decrease in all-cause mortality. Results suggest that providers can leverage predictive analytic-targeted population health approaches and interdisciplinary collaboration to improve patient outcomes.
Trial registration: ISRCTN16012111.
Keywords: mortality; opioids; predictive algorithms; risk mitigation; serious adverse events; veterans.
© 2022. The Author(s), under exclusive licence to Society of General Internal Medicine.