Concerns about opioid-related adverse events, including overdose, prompted the Veterans Health Administration (VHA) to launch an Opioid Safety Initiative and Overdose Education and Naloxone Distribution program. To mitigate risks associated with opioid prescribing, a holistic approach that takes into consideration both risk factors (e.g., dose, substance use disorders) and risk mitigation interventions (e.g., urine drug screening, psychosocial treatment) is needed. This article describes the Stratification Tool for Opioid Risk Mitigation (STORM), a tool developed in VHA that reflects this holistic approach and facilitates patient identification and monitoring. STORM prioritizes patients for review and intervention according to their modeled risk for overdose/suicide-related events and displays risk factors and risk mitigation interventions obtained from VHA electronic medical record (EMR)-data extracts. Patients' estimated risk is based on a predictive risk model developed using fiscal year 2010 (FY2010: 10/1/2009-9/30/2010) EMR-data extracts and mortality data among 1,135,601 VHA patients prescribed opioid analgesics to predict risk for an overdose/suicide-related event in FY2011 (2.1% experienced an event). Cross-validation was used to validate the model, with receiver operating characteristic curves for the training and test data sets performing well (>.80 area under the curve). The predictive risk model distinguished patients based on risk for overdose/suicide-related adverse events, allowing for identification of high-risk patients and enrichment of target populations of patients with greater safety concerns for proactive monitoring and application of risk mitigation interventions. Results suggest that clinical informatics can leverage EMR-extracted data to identify patients at-risk for overdose/suicide-related events and provide clinicians with actionable information to mitigate risk. (PsycINFO Database Record
Objective To describe how use of antidepressants, benzodiazepines, and other anxiolytic/sedative-hypnotics among older adults (age ≥65) has changed over time among visits to primary care providers and psychiatrists in the United States. Method Data came from the National Ambulatory Medical Care Survey (years 2003–2005 and 2010–2012), a nationally-representative cross-section of outpatient physician visits. Analysis focused on visits to primary care providers (n=14,282) and psychiatrists (n=1,095) at which an antidepressant, benzodiazepine, or other anxiolytic/sedative-hypnotic was prescribed, which were stratified by demographic and clinical characteristic (including ICD-9-CM diagnosis) and compared across study intervals. Odds of medication use were calculated for each stratum, adjusting for demographic and clinical characteristics. Results The visit rate by older adults to primary care providers where any of the medications were prescribed rose from 16.4% to 21.8% (AOR 1.43, p<0.001), while remaining steady among psychiatrists (75.4% v. 68.5%; AOR 0.69, p=0.11). Primary care visits rose for antidepressants (9.9% to 12.3%; AOR 1.28, p=0.01) and other anxiolytic/sedative-hypnotics (3.4% to 4.7%; AOR 1.39, p=0.01), but the largest growth was among benzodiazepines (5.6% to 8.7%; AOR 1.62, p<0.001). Among patients in primary care, increases primarily occurred among men, non-Hispanic white patients, and both those with pain diagnoses as well as those without any mental health or pain diagnoses. Conclusion From 2003–2012, use of the most common psychotropic medications among older adults seen in primary care increased, concentrated among patients with no mental health or pain diagnosis. As the population of older adults grows and receives mental health treatment in primary care, it is critical to examine the appropriateness of psychotropic use.
Key PointsQuestionDoes provision of pharmacogenomic testing for drug-gene interactions affect selection of antidepressant medication and response of depressive symptoms in patients with major depressive disorder (MDD)?FindingsIn this randomized clinical trial that included 1944 patients with MDD, provision of pharmacogenomic tests for drug interactions compared with usual care resulted in prescriptions with no predicted drug-gene interactions in 45% vs 18%, respectively, a difference that was statistically significant. Remission of symptoms reached a maximum difference of 16.5% vs 11.2% at 12 weeks but was not significantly different at 24 weeks.MeaningPharmacogenomic testing for drug-gene interactions in MDD reduced prescription of medications with predicted drug-gene interactions but had small and nonpersistent effects on symptom remission.
Background/Objectives To establish the rate of new and continuation benzodiazepine use among older adults seen by non-psychiatrist physicians, as well as identify patient subpopulations at risk for new and continuation benzodiazepine use. Design, Setting, Participants Cross-sectional analysis of the National Ambulatory Medical Care Survey (2007–2010) of all visits by adults to office-based non-psychiatrist physicians (n=98,818), then limited to those at which a benzodiazepine was prescribed (new or continuation). Measurements Percentage of benzodiazepine visits among all outpatient encounters by patient age and corresponding annual visit rate per 1,000 population. Analysis was then limited to adults ≥65; demographic, clinical, and visits characteristics were used to compare visits of benzodiazepine users with non-users and continuation users with new users. Results The proportion of benzodiazepine visits ranged from 3.2% (95% confidence interval [CI] 2.7–3.7%) among those 18–34 up to 6.6% (CI 5.8–7.6%) among adults ≥80 and the proportion of continuation visits increased with age, rising to 90.2% (CI 86.2–93.1%) among those ≥80. The population-based visit rate ranged from 61.7 (CI 50.7–72.7) per 1,000 persons among the youngest adults to 463.7 (CI 385.4–542.0) among those ≥80. Only 16.0% (CI 13.5–18.8%) of continuation users had any mental health diagnosis. Among all benzodiazepine users, less than 1% (CI .4–1.8%) were provided or referred to psychotherapy, while 10.0% (CI 7. 2–13.3%) were also prescribed an opioid. Conclusion In the US, few older adult benzodiazepine users receive a clinical mental health diagnosis and almost none are provided or referred to psychotherapy. Prescribing to older adults continues despite decades of evidence documenting safety concerns, effective alternative treatments, and effective methods for tapering even chronic users.
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