Assessing opioid overdose risk: a review of clinical prediction models utilizing patient-level data.

摘要: Drug, and specifically opioid-related, overdoses remain a major public health problem in the United States. Multiple studies have examined individual risk factors associated with overdose risk, but research developing clinical prediction tools for has only emerged last few years. We conducted comprehensive review of literature on patient-level opioid-related an emphasis models Studies that developed and/or validated were closely reviewed evaluated to determine state field. identified 12 reported risk. Published from variety data sources, including Veterans Health Administration data, Medicare commercial insurance statewide linked datasets. model performance using measures discrimination, usually at good-to-excellent levels, though they did not always assess calibration. C-statistics better included predictors (c-statistics: 0.75–0.95) compared without them 0.69–0.82). External validation was rare, we found no evaluating implementation or into practice. A common feature these high rate false positives, largely because is rare general population. Thus, efforts implement practice should take account published overestimate many low-risk patients. Future assessing employ external address In order translate findings benefit, future focus based models, implementing practice, impact treatment decisions, patient outcomes, and, ultimately, opioid rates.