Root Cause Analysis of Adverse Events Involving Opioid Overdoses in the Veterans Health Administration

ObjectiveThe Veterans Health Administration (VHA) serves a population with compounding risk factors for opioid misuse, including chronic pain, substance use disorders, and mental health conditions. The objective of this study was to analyze opioid-related adverse events and root causes to inform mitigation strategies associated with opioid prescribing and administration.MethodsThe researchers conducted a retrospective analysis of root cause analysis reports of opioid overdose events between August 1, 2012, and September 30, 2019. These adverse events were investigated locally by multidisciplinary hospital teams and reported by VHA facility patient safety managers to the National Center for Patient Safety for further aggregation and analysis. Type of event, location, and root causes were categorized.ResultsEighty-two adverse event reports were identified. Patients were primarily male with an average age of 61.4 years. Staff medication administration errors were the most common event type (57.3%), with most events resulting from process errors (65.9%) occurring in the health care setting (85.4%). Overall 36 events (43.9%) resulted in major or catastrophic harm. There were 172 root causes identified. The most common root causes were staff not following existing policy or lack of existing hospital policy on opioid management (18.0%); staff lacked training in areas such as managing the use or administration of opioids, correct use of opioid dispensing equipment, and recognition and proper response to an overdose (12.2%); and poor communication of opioid prescribing or administration during handoffs between clinical teams (11.6%). A lack of standardization in processes, training, and policies on opioid prescribing and screening, medication administration, equipment/pumps purchase and use, and contraband searches was a common theme throughout.ConclusionErrors in prescribing and administration of opioid medication can result in significant harm. A lack of standardized opioid administration practices and training, controlled substance policies, and interdisciplinary communication were frequent factors in adverse opioid events and should be a focus for future prevention.     

Long-Term Opioid Use and Dementia Risk in Patients With Chronic Pain

ObjectiveThis study aimed to investigate the association between long-term opioid use and the risk of dementia in patients with chronic pain.DesignA head-to-head propensity score–matched (PSM) comparative cohort study was conducted to examine the effect of long-term opioid use on dementia risk. A time-varying Cox regression analysis was performed to calculate adjusted hazard ratios (aHRs) with 95% CIs to identify independent predictors of dementia risk.Setting and ParticipantsThe study included 41,636 patients after PSM, with 20,968 in the opioid use group (≥180 defined daily doses per year) and 20,968 in the non–opioid use group.MethodsMultivariate Cox regression analysis was conducted to compare the dementia risk between the opioid use and non–opioid use groups. The incidence of dementia was calculated as the number of cases per 10,000 person-years for each group. Adjusted incidence ratios were determined to assess the dementia risk associated with opioid use.ResultsThe multivariate Cox regression analysis showed that the aHR for dementia risk in the opioid use group, compared with the non–opioid use group, was 1.86 (95% CI 1.25-2.09; P < .001). The incidence of dementia was higher among opioid users (44.09 per 10,000 person-years) compared with nonusers (38.85 per 10,000 person-years). The adjusted incidence ratio for dementia risk in the opioid use group, compared with the nonuse group, was 1.13 (95% CI: 1.07-1.21, P < .001).Conclusions and ImplicationsLong-term opioid use may be associated with an increased risk of dementia in patients with chronic pain. These findings highlight the need for cautious prescribing and monitoring of opioid use in this population, considering the potential long-term cognitive implications.     

Post-Acute Care Setting After Hip Fracture Hospitalization and Subsequent Opioid Use in Older Adults

ObjectivePain management in post-acute care (PAC) requires careful balance, with both opioid use and inadequate pain treatment linked to poor outcomes. We describe opioid use among older adults following discharge from PAC for hip fracture in skilled nursing facilities (SNFs) and inpatient rehabilitation facilities (IRFs).DesignRetrospective cohort.Setting and ParticipantsMedicare beneficiaries with Medicare Provider Analysis (MedPAR) claims, aged 66 years and older with a hip fracture hospitalization between 2012 and 2018 followed by PAC in SNFs or IRFs and then discharge to the community.MethodsIndividuals were followed from PAC discharge for up to 1 year to assess opioid use. Covariate-standardized risk ratios (RR) and risk differences (RD) for opioid use within 7 days of PAC discharge were estimated via parametric g-formula with modified Poisson regression, and hazard ratios (HRs) for any post-PAC opioid use and long-term opioid use via Fine-Gray sub-distribution hazards regression.ResultsOf 101,021 individuals, 80% (n = 80,495) were discharged from SNFs and 20% (n = 20,526) from IRFs. Opioids were dispensed to 50,433 patients (50%) overall and the 1-year cumulative incidence was notably higher in IRF (68%) than SNF (46%) patients. The adjusted risk of discharge from PAC with an opioid was 41% lower after SNFs versus IRFs [RR: 0.59; 95% confidence limits (CLs): 0.57–0.61; and RD: −0.16; 95% CLs: −0.17 to −0.15]. The adjusted rate of any opioid use in the year after PAC discharge was 44% lower (HR: 0.56; 95% CLs: 0.54–0.57) and of long-term opioid use was 17% lower (HR: 0.83; 95% CLs: 0.80–0.87) after SNFs versus IRFs.Conclusions and ImplicationsOpioid use is highly prevalent upon discharge from PAC after hip fracture, with lower use after SNF versus IRF care. Future research should assess the benefits and harms of post-PAC opioid prescribing and whether care practices during PAC can be improved to optimize long-term opioid use.     

Predictive Accuracy of Frailty Tools for Adverse Outcomes in a Cohort of Adults 80 Years and Older: A Decision Curve Analysis

ObjectivesTo compare the predictive performance of 3 frailty identification tools for mortality, hospitalization, and functional decline in adults aged ≥80 years using risk reclassification statistics and decision curve analysis.DesignPopulation-based, prospective cohort.SettingBELFRAIL study, Belgium.Participants560 community-dwelling adults aged ≥80 years.MeasurementsFrailty by Cardiovascular Health Study (CHS) phenotype, Longitudinal Aging Study Amsterdam (LASA) markers, and Groeningen Frailty Indicator (GFI); mortality until 5.1 ± 0.25 years from baseline and hospitalization until 3.0 ± 0.25 years; and functional status assessed by activities of daily living at baseline and after 1.7 ± 0.21 years.ResultsFrailty prevalence was 7.3% by CHS phenotype, 21.6% by LASA markers, and 22% by GFI. Participants determined to be frail by each tool had a significantly higher risk for all-cause mortality and first hospitalization. For functional decline, only frail by GFI had a higher adjusted odds ratio. Harrell 's C-statistic for mortality and hospitalization and area under receiver operating characteristic curve for functional decline were similar for all tools and <0.70. Reclassification statistics showed improvement only by LASA markers for hospitalization and mortality. In decision curve analysis, all tools had higher net benefit than the 2 default strategies of “treat all” and “treat none” for mortality risk ≥20%, hospitalization risk ≥35%, and functional decline probability ≥10%, but their curves overlapped across all relevant risk thresholds for these outcomes.Conclusions and ImplicationsIn a cohort of adults aged ≥80 years, 3 frailty tools based on different conceptualizations and assessment sources had comparable but unsatisfactory discrimination for predicting mortality, hospitalization, and functional decline. All showed clinical utility for predicting these outcomes over relevant risk thresholds, but none was significantly superior. Future research on frailty tools should include a focus on the specific group of adults aged ≥80 years, and the predictive accuracy for adverse outcomes of different tools needs a comprehensive assessment that includes decision curve analysis.