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OBJECTIVES: Explore the indications for long-stay gabapentin use and elucidate the factors spurring the rapid increase in gabapentin prescribing in nursing homes (NHs). METHODS: National cross-sectional survey of NH prescribers distributed anonymously using SurveyMonkey. Sampling for convenience was obtained through crowdsourcing, leveraging collaborations with NH clinician organizations. Developed by a multidisciplinary team, pilot data/existing literature informed survey content. RESULTS: A total of 131 surveys completed. Participants: 71% white, 52% female, 71% physicians. Off-label gabapentin prescribing was ubiquitous. Nearly every clinician used gabapentin for neuropathic pain, most for any form of pain. Many clinicians also prescribe gabapentin to moderate psychiatric symptoms and behaviors. Clinicians' prescribing was influenced by opioid, antipsychotic, and anxiolytic reduction policies because gabapentin was perceived as an unmonitored and safer alternative. CONCLUSIONS: Off-label gabapentin increases are closely linked to opioid reduction efforts as more NH clinicians utilize gabapentin as an unmonitored opioid alternative. Our results highlight, however, the less recognized significance of long-stay prescribing for psychiatric symptoms and the similar contribution of psychotropic reduction initiatives, a phenomenon warranting further scrutiny. CLINICAL IMPLICATIONS: Clinicians perceive gabapentin as safer than the drugs it is replacing. Whether this is true remains unclear; the individual- and population-level risks of increased gabapentin use are largely unknown.

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The Centers for Medicare & Medicaid Services (CMS) grades nursing home performance in antipsychotic prescribing quarterly, publishing findings as a quality measure. While scores have improved since 2011, marked performance variation between facilities persists. To assess quality gap changes between best- and worst-performing deciles, we compared quarterly prescribing changes between these groups pre-pandemic (April 2011 to March 2020) and during the pandemic (April 2020 to March 2022). Antipsychotic quality measure scores, improving pre-pandemic, deteriorated during the pandemic. The pre-pandemic quality gap between the best- and worst-performing deciles narrowed as the worst-performing decile improved faster than the best-performing decile. During the pandemic, the quality gap widened as the worst-performing decile relapsed more than the best-performing decile (p < .0001). The pandemic disrupted quality performance gains and compounded disparities between facilities. A better understanding of the factors allowing high performers to weather pandemic stressors better than poor performers may reveal opportunities to improve nursing home quality and equity for all residents.

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OBJECTIVES: To describe nursing home (NH) characteristics associated with antipsychotic use and test whether associations changed after implementation of the National Partnership to Improve Dementia Care's antipsychotic reduction initiative (ARI). METHODS: Longitudinal quasi-experimental design using data from multiple sources and piecewise linear mixed models were used for statistical analyses. RESULTS: There was a significant decrease in monthly antipsychotic use across the study period (pre-ARI b = -0.0003, p <.001; post-ARI b = -0.0012, p <.001), which held after adjusting for NH characteristics. Registered nurse hours (b = -0.0026, p <.001), licensed practical nurse hours (b = -0.0019, p <.001), facility chain membership (b = -0.0013, p <.01), and health inspection ratings (b = -0.0003, p >.01) were associated with decreased antipsychotic use. Post-ARI changes in associations between NH characteristics and antipsychotic use were small and not statistically significant. CONCLUSIONS: Decreases in antipsychotic use were associated with most NH characteristics, and associations persisted post-ARI. Further research is warranted to examine the interactions between ARI policy and NH characteristics on antipsychotic prescribing, as well as other NH factors, such as facility prescribing cultures and clinical specialty of staff. CLINICAL IMPLICATIONS: Decreases in monthly antipsychotic use were observed following the ARI. The decreases in monthly antipsychotic use were associated with most NH characteristics, and these associations persisted during the post-ARI period.

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OBJECTIVES: Nursing home residents have been disproportionately affected by the COVID-19 pandemic. Despite recognition as a priority group for receipt of the COVID-19 vaccine, vaccine uptake and COVID-19 cases, hospitalizations, and deaths in nursing home facilities were variable across nursing homes. This study has 2 objectives: (1) to describe nursing facility characteristics associated with higher vs lower vaccination rates and (2) to estimate facility characteristics associated with COVID-19 cases, hospitalizations, and deaths, stratified by vaccination rate. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: Facility-level data from 12,811 US nursing home facilities. METHODS: Using the CMS's Nursing Home COVID-19 Public File, we analyzed nursing home COVID-19 vaccination rates and outcomes from June 13, 2021, to September 19, 2021. We performed multivariable logistic regressions and identified facility characteristics associated with increased vaccination uptake and COVID-19 outcomes. RESULTS: Nursing homes with average vaccination rates ≤80% experienced higher total average COVID-19 cases, hospitalizations, and deaths compared to facilities with >80% average vaccination rates during the Delta surge. Moreover, facility factors, such as higher average age of residents, proportion of non-white residents, nurse staffing hours, and occupancy rates, were variably associated with increased risk of COVID-19 outcomes. CONCLUSIONS AND IMPLICATIONS: Facilities with higher resident vaccination rates experienced lower average COVID-19 cases, hospitalizations, and deaths in US nursing homes. Access to vaccines may play a role in mitigating harm associated with infectious diseases. Additionally, facility factors associated with increased adverse outcomes were variably associated with increased odds of COVID-19 outcomes, often, irrespective of vaccination level. As the COVID-19 pandemic continues to evolve and as the possibility of other infectious disease variants emerge, this research provides insight into facility factors, including vaccine uptake, that may mitigate adverse outcomes.

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AIM: In this study, we aimed to provide a nationally representative estimate of the economic burden of chronic obstructive pulmonary disease (COPD) by examining direct medical costs among individuals aged 45 years and older in the USA. METHODS: Medical Expenditure Panel Survey (2017-2018) data were used to estimate the direct medical costs associated with COPD. All-cause (unadjusted) cost and COPD-specific (adjusted) cost were determined for the various service categories using a regression-based approach among patients with COPD. We developed a weighted two-part model and adjusted for various demographic, socioeconomic, and clinical characteristics. RESULTS: The study sample consisted of 23,590 patients, of which 1073 had COPD. Patients with COPD had a mean age of 67.4 years (standard error (SE): 0.41), and the total all-cause mean medical cost per patient per year (PPPY) was 2018 US $19,449 (SE: US $865), of which US $6145 (SE: US $295) was for prescription drugs. Using the regression approach, the mean total COPD-specific cost was US $4322 (SE: US $577) PPPY, with prescription drugs contributing US $1887 (SE: 216) PPPY. These results represented an annual total COPD-specific cost of US $24.0 billion, with prescription drugs contributing US $10.5 billion. The mean annual out-of-pocket spending accounted for 7.5% (mean: US $325) of the total COPD-specific cost; for COPD-specific prescription drug cost, 11.3% (mean: US $212) was out-of-pocket cost. CONCLUSION: COPD poses a significant economic burden on healthcare payers and patients 45 years of age and older in the USA. While prescription drugs accounted for almost half of the total cost, more than 10% of the prescription drug cost was out-of-pocket.

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BACKGROUND: In July 2012, the Centers for Medicare & Medicaid services launched an antipsychotic reduction initiative (ARI) to improve care for nursing facility residents with Alzheimer's disease and related dementias (ADRD). We examined the impact of this policy on antipsychotic and psychotropic medication (PM) utilization and diagnosis patterns in long-stay nursing facility residents with ADRD and other conditions in which antipsychotics are indicated. METHODS: Using an 80% sample of fee-for-service Medicare beneficiaries with Part D, we conducted a retrospective cohort study of nursing facility residents with ADRD, bipolar disorder, psychosis, Parkinson's disease, and residents exempt from the policy due to diagnoses of schizophrenia, Tourette syndrome, and/or Huntington's disease. We used interrupted time-series analyses to compare changes in diagnoses, antipsychotic use, and PM utilization before (January 1, 2011-June 30, 2012) and after (July 1, 2012-September 30, 2015) ARI implementation. RESULTS: We identified 874,487 long-stay nursing facility residents with a diagnosis of ADRD (n = 358,518), exempt (n = 92,859), bipolar (n = 128,298), psychosis (n = 93,402), and Parkinson's disease (n = 80,211). In all cohorts, antipsychotic use declined prior to the ARI; upon policy implementation, antipsychotic use reductions were sustained throughout the study period, including statistically significant ARI-associated accelerated declines in all cohorts. PM changes varied by cohort, with ARI-associated increases in non-benzodiazepine sedatives and/or muscle relaxants noted in ADRD, psychosis, and Parkinson's cohorts. Although anticonvulsant use increased throughout the study period in all groups, with the exception of the bipolar cohort, these increases were not associated with ARI implementation. Findings are minimally explained by increased post-ARI membership in the psychosis and Parkinson's cohorts. CONCLUSIONS: Our study documents antipsychotic use significantly declined in non-ADRD clinical and exempt cohorts, where such reductions may not be clinically warranted. Furthermore, ARI-associated compensatory increases in PMs do not offset these reductions. Changes in PM utilization and diagnostic make-up of residents using PMs require further investigation to assess the potential for adverse clinical and economic outcomes.

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OBJECTIVE: Individuals who are family history positive (FHP) for substance use problems have increased risk for substance use, substance use disorders (SUDs), and psychopathology. Links between FHP status and prescription drug misuse (PDM) have not been well investigated; this study examined PDM in adults 50 and older by FHP status. METHODS: Data were from the US NESARC-III (n = 14,667). Participants reported their opioid PDM, tranquilizer/sedative PDM, SUD, psychopathology, and family history status (i.e. first- and second-degree relatives with alcohol/substance use problems). Prevalence rates were estimated by FHP status, and logistic regressions compared FHP and family history negative (FHN) groups. RESULTS: FHP status was associated with significantly higher rates of PDM (e.g. past-year opioid PDM, FHP: 3.8%, FHN: 1.5%) and SUD from PDM (e.g. past-year SUD, FHP: 1.2%, FHN: 0.2%); also, prevalence varied by family history density, with the highest rates in those with three or more relatives with substance use problems (e.g. past-year opioid PDM: 5.5%). Overall, 32.2% of FHP individuals with past-year PDM had past-year co-occurring SUD and psychopathology diagnoses, versus 11.0% of FHN individuals. CONCLUSION: FHP status could inform treatment decisions in adults 50 and older with conditions for which prescription opioids or tranquilizer/sedatives are indicated.

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BACKGROUND: The extent to which a positive delirium screening and new diagnosis of Alzheimer's disease or related dementias (ADRD) increases the risk for re-hospitalization, long-term nursing home placement, and death remains unknown. OBJECTIVE: To compare long-term outcomes among newly admitted skilled nursing facility (SNF) patients with delirium, incident ADRD, and both conditions. DESIGN, SETTING, AND PARTICIPANTS: A retrospective cohort study of Medicare beneficiaries who entered a SNF from hospital with a minimum 14-day stay (n = 100,832) from 2015 to 2016. MAIN MEASURES: Return to home, hospital readmission, admission to a long-term care facility, or death. KEY RESULTS: Patients with delirium were as likely to be discharged home as patients diagnosed with ADRD (HR: 0.63, 95% CI: 0.59, 0.67; HR: 0.65, 95% CI: 0.64, 0.67). Patients with both delirium and ADRD were less likely to be discharged home (HR: 0.49, 95% CI: 0.47, 0.52) and showed increased risk of death (HR: 1.30, 95% CI: 1.17, 1.45). Patients with ADRD, regardless of delirium screening status, had increased risk for long-term nursing home care transfer (HR: 1.66, 95% CI: 1.63, 1.70; HR: 1.76, 95% CI: 1.69, 1.82). Patients with delirium and no ADRD showed increased risk of transfer to long-term nursing home care (HR: 1.25, 95% CI: 1.18, 1.33). The rate of deaths was higher among patients who screened positive for delirium without ADRD compared to the no delirium and no ADRD groups (HR: 2.35, 95% CI: 2.11, 2.61). CONCLUSION: A positive delirium screening increased risk of death and transfer to long-term care in the first 100 days after admission regardless of incident ADRD diagnosis. Patients with delirium and/or ADRD also are less likely to be discharged home. Our study builds on the evidence base that delirium is important to address in older adults as it is associated with negative outcomes.

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OBJECTIVES: This study examines the association between antipsychotic (AP) medication use and care transitions in the nursing home (NH) population. METHODS: This cross-sectional study used data from a 5% random sample of Medicare beneficiaries between 2011 and 2015. Propensity score adjusted negative binomial regression was performed and conditional probabilities of having a first transition from the NH to specific locations were calculated. RESULTS: Among 150,284 eligible beneficiaries, the majority were female (67%), white (84%), and >75 years old (63%). Controlling for resident characteristics, the odds of having any transition was 5% lower among those with AP use [IRR (95% confidence interval (CI))=0.95(0.94-0.96)] relative to those with no AP use. Residents with AP use had higher proportions of transitions to hospital (22.7% vs. 19.5%, p < 0.01), emergency department (19.6% vs. 10.7%, p < 0.01), and different NH (1.5% vs. 0.4%, p < 0.01), and lower proportions of transition to non-healthcare locations compared to those without AP use. CONCLUSIONS: Findings demonstrate that residents with AP use had higher probabilities of transitions to more costly care settings such as the emergency department and hospital compared to those without AP use. Future longitudinal studies will help to inform clinical interventions aimed at improving the quality of care for this population.

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OBJECTIVES: To determine whether staff and resident COVID-19 vaccination rates varied by racial heterogeneity of nursing homes, defined as proportion of residents who are White. METHODS: Cross-sectional study using data from the Medicare COVID-19 Nursing Home Database and LTCFocus.org to examine facility-level resident and staff vaccination status. General linear regression models assessed analyses of variance and tests for trend on proportion of residents and staff fully vaccinated as of June 13, 2021 by proportion of White residents in each facility. RESULTS: Over 12,000 (n=12,278) nursing homes provided resident measures and 8,838 reported staff measures. The mean (standard deviation [SD]) resident vaccination rate of nursing homes in the lowest and highest quantiles of White residents was significantly different at 72.74% (20.59%) and 85.65% (16.70%), respectively. Staff vaccination rates of nursing homes in the lowest and highest quantiles of White residents were not significantly different at 58.34% (25.09%) and 56.06% (19.32%), respectively. CONCLUSIONS: A higher proportion of White residents per facility was associated with higher resident COVID-19 vaccination rates reflecting continued disparities in quality of care during the pandemic.

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BACKGROUND: Suboptimal maintenance medication (MM) adherence remains a clinical problem among Medicare beneficiaries with chronic obstructive pulmonary disease (COPD). OBJECTIVE: To inform risk-based personalized decision-making, this study sought to develop and validate prediction models of nonadherence to COPD MMs for Medicare beneficiaries. METHODS: This was a retrospective cohort study of beneficiaries aged 65 years and older with COPD and inhaled MMs. Nonadherence (proportion of days covered < 0.8) was measured in 12 months following the first MM fill after COPD diagnosis. Logistic and least absolute shrinkage selector operator regressions were implemented, and area under the receiver operating characteristic curve (AUROC) evaluated model accuracy, as well as positive predictive values and negative predictive values. Our models evaluated different sets of predictors for two cohorts: those with an MM prescription before COPD diagnosis (prevalent users) and those without (new users). RESULTS: Among 16,157 prevalent and 40,279 new users of MMs, 11,271 (69.8%) and 34,009 (84.4%), respectively, were nonadherent. The best-performing logistic models achieved AUROCs of 0.8714 and 0.881, positive predictive values of 0.881 and 0.881, and negative predictive values of 0.559 and 0.578, respectively, for prevalent and new users. The least absolute shrinkage selector operator models had similar accuracy. Models with baseline-only predictors had average performance (AUROC < 0.72). The most important predictors were initial MM adherence, short-acting bronchodilator use, and asthma. CONCLUSIONS: To our knowledge, this study is the first to develop predictive models of nonadherence to COPD MMs. Generated models achieved good discrimination and underlined the importance of early adherence. Well-performed models can be useful for care decision-making and interventions to improve COPD medication adherence after the first critical few months following a treatment episode. DISCLOSURES: All authors declared no conflicts of interest.

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OBJECTIVES: In an era of heightened opioid prescribing scrutiny, ensuring safe and adequate pain management is challenging. Understanding opioid use in patients with cancer can facilitate effective pain management regimens while minimizing safety concerns. This study characterized patterns of and factors associated with opioid use following a new cancer diagnosis. STUDY DESIGN: Retrospective cohort study. METHODS: Our study included patients with a new cancer diagnosis aged 18 to 64 years in IQVIA PharMetrics Plus 2007-2013 who were continuously enrolled 12 months before receiving their cancer diagnosis and 24 months after. Study outcomes included opioid prevalence and measures of potentially high-risk opioid use (total days supplied, number of prescriptions, and morphine equivalent daily dose [MEDD]). Descriptive analyses and logistic regression were implemented. RESULTS: Of 191,616 eligible individuals, 93,739 (48.9%) received opioid prescriptions; of these, 56,025 (59.8%) were new opioid users. Opioid users received 4.6 prescriptions on average, covering 65 total days with a mean MEDD of 31.8 mg. Only 2387 (2.5%) patients received higher than recommended (≥ 90 mg) MEDD. Predictors of opioid use post cancer included prior opioid use, select comorbidities, use of nonopioid pain treatment adjuvants (muscle relaxants, sedative/hypnotics, anticonvulsants, antidepressants, and steroids), cancer site, and metastatic cancer. CONCLUSIONS: Fewer than half of patients received opioids in the 2 years following cancer onset. Among users, we found a relatively small proportion of potentially problematic opioid use. Further research is warranted to assess the adequacy of cancer pain treatment and determinants of high-risk opioid use.

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Background: Gabapentin, opioids, and/or benzodiazepines are commonly prescribed for a variety of pain and psychiatric conditions. Despite the high likelihood of co-prescription of these medications, little is known about co-utilization of gabapentin (GABA), opioids (OP), and benzodiazepines (BZD) and associated public health outcomes. Methods: Using Medicare CCW Data, 2013-2016, we conducted a nested case-control study to examine the association between concurrent utilization of GABA, OP, and BZD and respiratory depression, opioid, and substance-related overdose among Medicare disabled beneficiaries. Cases and controls were Fee-for-service disabled beneficiaries who had a diagnosis of acute pain (AP), chronic pain (CP) or mental health conditions (MH) and received GABA, OP or BZD. Cases with respiratory depression, opioid or substance-related overdose were matched with up to 4 controls on socio-demographics, year of cohort entry and disease risk score. Primary exposure was concurrent medication utilization defined as an overlap of at least one day in prescriptions for GABA, OP and BZD. Findings: Across all cohorts, the majority of cases and controls were under 65, female, dually eligible and had prior histories of pain and mental health conditions. GABA+OP+BZD use was associated with increased odds of respiratory depression [AOR(95%CI)-AP: 1.35 (1.19-1.52), CP:1.24 (1.11-1.38) and MH: 1.16 (1.02-1.32) vs. OP only], opioid-related overdose [AP: 1.43 (1.04-1.98), CP: 1.47 (1.07-2.00) and MH: 1.44 (1.04-2.00) vs. OP only], and substance-related overdose [AP: 1.77 (1.26-2.50), CP: 1.70 (1.24-2.34) and MH: 1.92 (1.31-2.82) vs. GABA only]. While there were cohort differences in the association between GABA+OP and both respiratory depression and opioid-related overdose, GABA+OP and GABA+BZD use were associated with significantly higher odds of substance-related overdose across all clinical cohorts. Interpretation: Among Medicare disabled beneficiaries, concurrent utilization of gabapentin, opioids, and benzodiazepines is associated with multiple adverse outcomes. Given this, it is imperative that the benefits and risks of co-prescribing these medications be comprehensively examined. Funding: None.

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BACKGROUND: Our goal was to describe specific patterns associated with co-prescriptions of gabapentin, opioids, and benzodiazepines among disabled Medicare beneficiaries. METHODS: Using 2013-2015 Medicare data, we conducted a retrospective cohort study among fee-for-service disabled beneficiaries continuously enrolled in Medicare Parts A, B, and D. The index date was defined as the earliest fill date for a gabapentin, opioid, or benzodiazepine prescription. Monotherapy, dual therapy, and tri-therapy were defined as utilization of one, two, and three medication classes, respectively. Augmentation was defined as a prescription for a different medication class in addition to prescription for initial medication; switching referred to a change in prescription for a different medication class with no subsequent fills of initial medication. We used descriptive statistics, Kaplan Meier analyses and Cox proportional hazards to examine the association between initial therapy and monotherapy, dual therapy, tri-therapy, switching and augmentation. RESULTS: Among 151,552 disabled beneficiaries, gabapentin initiators were more likely to augment therapy (50.1%) when compared to opioid (28.7%) and benzodiazepine (38.7%) users. When compared to opioid initiators, the risk of augmentation (HR[95%CI]: 1.85[1.82-1.89]) and switching (1.62 [1.51-1.73]) was significantly higher among gabapentin initiators. Risk of augmentation was also significantly higher among beneficiaries with co-morbid pain and mental health conditions (p < 0.01). Overall, the majority of beneficiaries augmented and switched within 2-months and 4-months after initiating therapy, respectively. CONCLUSIONS: Given safety concerns associated with gabapentin, opioids, and benzodiazepines, it is imperative that the benefits and risks of co-prescribing these medications be examined comprehensively, especially for those in vulnerable sub-groups.

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BACKGROUND: Prescription drug monitoring programs (PDMPs) have been shown to reduce opioid use in the general and noncancer populations. However, evidence of PDMP impacts on patients with cancer remains limited. OBJECTIVE: The aim of the study was to examine the impact of PDMP mandates on individual-level opioid use among patients with cancer. METHODS: This is a retrospective cohort study of patients with newly diagnosed cancer aged 18-65 years in the IQVIA PharMetrics Plus database (IQVIA Inc; nationally representative data of the U.S. commercially insured population in 49 states) between 2013 and 2015. The primary exposure was PDMP rigor (ranked from highest to lowest rigor): provider query + registration, query only, registration only, and unexposed. The study outcomes included (1) prevalent use among all individuals; and among opioid users (2) total days supplied, (3) daily morphine equivalent dose (MED), and (4) cumulative MED. RESULTS: Of the eligible cohort (n=28,353), 37.5% (10,656) received opioids after a cancer diagnosis. The individuals exposed to these mandates were as follows: query + registration: 3899 (13.8%); query only: 3459 (12.2%); registration only: 2764 (9.7%); and no mandates: 18,231 (64.3%). The PDMP mandates had no effect on prevalent opioid use. Compared with unexposed patients, those subject to query mandates-alone or with registration mandates-experienced 12 fewer opioid days supplied and a lower mean cumulative MED (-662 mg and -702 mg, respectively), P < 0.01. Registration-only mandates were associated with 21 days more (P < 0.01) total days supplied and lower daily MED (1.1 mg; P < 0.05) but had no statistically significant effect on cumulative MED (-46 mg, P > 0.05). CONCLUSION: Query mandates are a stronger PDMP tool than registration mandates in reducing opioid days supplied and cumulative MED. Initiatives should target PDMP mandates toward intended patient groups to reduce high-risk opioid use without compromising adequate pain treatment.

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OBJECTIVES: During the last quarter of 2020-despite improved distribution of personal protective equipment (PPE) and knowledge of COVID-19 management-nursing homes experienced the greatest increases in cases and deaths since the pandemic's beginning. We sought to update COVID-19 estimates of cases, hospitalization, and mortality and to evaluate the association of potentially modifiable facility-level infection control factors on odds and magnitude of COVID-19 cases, hospitalizations, and deaths in nursing homes during the third surge of the pandemic. DESIGN: Cross-sectional analysis. SETTING AND PARTICIPANTS: Facility-level data from 13,156 US nursing home facilities. METHODS: Two series of multivariable logistic regression and generalized linear models to examine the association of infection control factors (personal protective equipment and staffing) on incidence and magnitude, respectively, of confirmed COVID-19 cases, hospitalizations, and deaths in nursing home residents reported in the last quarter of 2020. RESULTS: Nursing homes experienced steep increases in COVID-19 cases, hospitalizations, and deaths during the final quarter of 2020. Four-fifths (80.51%; n = 10,592) of facilities reported at least 1 COVID-19 case, 49.44% (n = 6504) reported at least 1 hospitalization, and 49.76% (n = 6546) reported at least 1 death during this third surge. N95 mask shortages were associated with increased odds of at least 1 COVID-19 case [odds ratio (OR) 1.21, 95% confidence interval (CI) 1.05-1.40] and hospitalization (1.26, 95% CI 1.13-1.40), as well as larger numbers of hospitalizations (1.11, 95% CI 1.02-1.20). Nursing aide shortages were associated with lower odds of at least 1 COVID-19 death (1.23, 95% CI 1.12-1.34) and higher hospitalizations (1.09, 95% CI 1.01-1.17). The number of nursing hours per resident per day was largely insignificant across all outcomes. Of note, smaller (<50-bed) and midsized (50- to 150-bed) facilities had lower odds yet higher magnitude of all COVID outcomes. Bed occupancy rates >75% increased odds of experiencing a COVID-19 case (1.48, 95% CI 1.35-1.62) or death (1.25, 95% CI 1.17-1.34). CONCLUSIONS AND IMPLICATIONS: Adequate staffing and PPE-along with reduced occupancy and smaller facilities-mitigate incidence and magnitude of COVID-19 cases and sequelae. Addressing shortcomings in these factors is critical to the prevention of infections and adverse health consequences of a next surge among vulnerable nursing home residents.

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Few studies have quantified the multimorbidity burden in older adults with chronic obstructive pulmonary disease (COPD) using large and generalizable data. Such evidence is essential to inform evidence-based research, clinical care, and resource allocation. This retrospective cohort study used a nationally representative sample of Medicare beneficiaries aged 65 years or older with COPD and 1:1 matched (on age, sex, and race) non-COPD beneficiaries to: (1) quantify the prevalence of multimorbidity at COPD onset and one-year later; (2) quantify the rates [per 100 person-years (PY)] of newly diagnosed multimorbidity during in the year prior to and in the year following COPD onset; and (3) compare multimorbidity prevalence in beneficiaries with and without COPD. Among 739,118 eligible beneficiaries with and without COPD, the average number of multimorbidity was 10.0 (SD = 4.7) and 1.0 (SD = 3.3), respectively. The most prevalent multimorbidity at COPD onset and at one-year after, respectively, were hypertension (70.8% and 80.2%), hyperlipidemia (52.2% and 64.8%), anemia (42.1% and 52.0%), arthritis (39.8% and 47.7%), and congestive heart failure (CHF) (31.3% and 38.8%). Conditions with the highest newly diagnosed rates before and following COPD onset, respectively, included hypertension (39.8 and 32.3 per 100 PY), hyperlipidemia (22.8 and 27.6), anemia (17.8 and 20.3), CHF (16.2 and 13.2), and arthritis (12.9 and 13.2). COPD was significantly associated with increased odds of all measured conditions relative to non-COPD controls. This study updates existing literature with more current, generalizable findings of the substantial multimorbidity burden in medically complex older adults with COPD-necessary to inform patient-centered, multidimensional care.Supplemental data for this article is available online at https://doi.org/10.1080/15412555.2021.1968815 .

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OBJECTIVE: The objective of this study was to estimate the risk of traumatic brain injury (TBI) associated with opioid use among older adult Medicare beneficiaries. SETTING: Five percent sample of Medicare administrative claims obtained for years 2011-2015. PARTICIPANTS: A total of 50 873 community-dwelling beneficiaries 65 years and older who sustained TBI. DESIGN: Case-crossover study comparing opioid use in the 7 days prior to TBI with the control periods of 3, 6, and 9 months prior to TBI. MAIN MEASURES: TBI cases were identified using ICD-9 (International Classification of Diseases, Ninth Revision) and ICD-10 (International Classification of Diseases, Tenth Revision) codes. Prescription opioid exposure and concomitant nonopioid fall risk-increasing drug (FRID) use were determined by examining the prescription drug event file. RESULTS: The 8257 opioid users (16.2%) were significantly younger (mean age 79.0 vs 80.8 years, P < .001). Relative to nonusers, opioid users were more likely to be women (77.0% vs 70.0%, P < .001) with a Charlson Comorbidity Index of 2 or more (43.7% vs 30.9%, P < .001) and higher concomitant FRID use (94.0% vs 82.7%, P < .001). Prescription opioid use independently increased the risk of TBI compared with nonusers (OR = 1.34; 95% CI, 1.28-1.40). In direct comparisons, we did not observe evidence of a significant difference in adjusted TBI risk between high- (≥90 morphine milligram equivalents) and standard-dose opioid prescriptions (OR = 1.01; 95% CI, 0.90-1.14) or between acute and chronic (≥90 days) opioid prescriptions (OR = 0.93; 95% CI, 0.84-1.02). CONCLUSIONS: Among older adult Medicare beneficiaries, prescription opioid use independently increased risk for TBI compared with nonusers after adjusting for concomitant FRID use. We found no significant difference in adjusted TBI risk between high-dose and standard-dose opioid use, nor did we find a significant difference in adjusted TBI risk between acute and chronic opioid use. This analysis can inform prescribing of opioids to community-dwelling older adults for pain management.

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OBJECTIVES: Although older adult prescription drug misuse (PDM) is associated with concerning consequences, stimulant PDM and poly- PDM involving multiple medication classes each remain understudied. Our objectives were to examine PDM and poly-PDM prevalence by medication class in US older adults and to identify the mental health, SUD, and health-related quality-of-life correlates of poly-PDM. METHOD: Data were from adults 50 and older completing the National Epidemiologic Survey on Alcohol and Related Conditions-III, (N = 14,667). Prevalence of PDM and poly-PDM by medication class was estimated. Logistic regression established odds of four SUD diagnoses, five psychopathology diagnoses and lifetime suicide attempts; linear regression evaluated health-related quality-of-life by PDM/poly-PDM status. RESULTS: Past-year PDM abstinence increased with age (50-54 years: 80.5%; 80 and older: 96.0%), while poly-PDM declined; past-year stimulant PDM was rare (≤0.6%), except when combined with opioid and tranquilizer/sedative PDM. Compared to no past-year PDM, both past-year opioid-only PDM and opioid-involved poly-PDM were associated with poorer health-related quality-of-life and greater odds of psychopathology and SUD, with the highest odds in poly-PDM. CONCLUSION: The presence of any opioid-involved PDM in older adults highlights screening for SUD, psychopathology, and other medical conditions, with the most significant intervention needs likely in those with opioid-involved poly-PDM.

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