High-risk prescribing and opioid overdose: prospects for prescription drug monitoring program-based proactive alerts.

ABSTRACT: To develop a simple, valid model to identify patients at high risk of opioid overdose-related hospitalization and mortality, Oregon prescription drug monitoring program, Vital Records, and Hospital Discharge data were linked to estimate 2 logistic models; a first model that included a broad range of risk factors from the literature and a second simplified model. Receiver operating characteristic curves, sensitivity, and specificity of the models were analyzed. Variables retained in the final model were categories such as older than 35 years, number of prescribers, number of pharmacies, and prescriptions for long-acting opioids, benzodiazepines or sedatives, or carisoprodol. The ability of the model to discriminate between patients who did and did not overdose was reasonably good (area unde

SUBMITTER: Geissert P 

PROVIDER: S-EPMC5893429 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature