Lower odds of successful community discharge after medical hospitalization for Veterans with schizophrenia: A retrospective cohort study of national data.

Medical comorbidity, particularly cardiovascular diseases, contributes to high rates of hospital admission and early mortality in people with schizophrenia. The 30 days following hospital discharge represents a critical period for mitigating adverse outcomes. This study examined the odds of successful community discharge among Veterans with schizophrenia compared to those with major affective disorders and those without serious mental illness (SMI) after a heart failure hospital admission. Data for Veterans hospitalized for heart failure were obtained from the Veterans Health Administration (VHA) and Centers for Medicare & Medicaid Services between 2011 and 2019. Psychiatric diagnoses and medical comorbidities were assessed in the year prior to hospitalization. Successful community discharge was defined as remaining in the community without hospital readmission, death, or hospice for 30 days after hospital discharge. Logistic regression analyses adjusting for relevant factors were used to examine whether individuals with a schizophrenia diagnosis showed lower odds of successful community discharge versus both comparison groups. Out of 309,750 total Veterans in the sample, 7377 (2.4%) had schizophrenia or schizoaffective disorder and 32,472 (10.5%) had major affective disorders (bipolar disorder or recurrent major depressive disorder). Results from adjusted logistic regression analyses demonstrated significantly lower odds of successful community discharge for Veterans with schizophrenia compared to the non-SMI (Odds Ratio [OR]: 0.63; 95% Confidence Interval [CI]: 0.60, 0.66) and major affective disorders (OR: 0.65, 95%; CI: 0.62, 0.69) groups. Intervention efforts should target the transition from hospital to home in the subgroup of Veterans with schizophrenia.

Serious mental illness is associated with elevated risk of hospital readmission in veterans with heart failure.

OBJECTIVE: Adults with serious mental illness (SMI) have high rates of cardiovascular disease, particularly heart failure, which contribute to premature mortality. The aims were to examine 90- and 365-day all-cause medical or surgical hospital readmission in Veterans with SMI discharged from a heart failure hospitalization. The exploratory aim was to evaluate 180-day post-discharge engagement in cardiac rehabilitation, an effective intervention for heart failure. METHODS: This study used administrative data from the Veterans Health Administration (VHA) and Centers for Medicare & Medicaid Services between 2011 and 2019. SMI status and medical comorbidity were assessed in the year prior to hospitalization. Cox proportional hazards models (competing risk of death) were used to evaluate the relationship between SMI status and outcomes. Models were adjusted for VHA hospital site, demographics, and medical characteristics. RESULTS: The sample comprised 189,767 Veterans of which 23,671 (12.5%) had SMI. Compared to those without SMI, Veterans with SMI had significantly higher readmission rates at 90 (16.1% vs. 13.9%) and 365 (42.6% vs. 37.1%) days. After adjustment, risk of readmission remained significant (90 days: HR: 1.07, 95% CI: 1.03, 1.11; 365 days: HR: 1.10, 95% CI: 1.07, 1.12). SMI status was not significantly associated with 180-day cardiac rehabilitation engagement (HR: 0.98, 95% CI: 0.91, 1.07). CONCLUSIONS: Veterans with SMI and heart failure have higher 90- and 365-day hospital readmission rates even after adjustment. There were no differences in cardiac rehabilitation engagement based on SMI status. Future work should consider a broader range of post-discharge interventions to understand contributors to readmission.

Changes in the burden of medications that may impair driving among older adults before and after a motor vehicle crash.

BACKGROUND: Medications are one of the most easily modifiable risk factors for motor vehicle crashes (MVCs) among older adults, yet limited information exists on how the use of potentially driver-impairing (PDI) medications changes following an MVC. Therefore, we examined the number and types of PDI medication classes dispensed before and after an MVC. METHODS: This observational study included Medicare fee-for-service beneficiaries aged ≥67 years who were involved in a police-reported MVC in New Jersey as a driver between 2008 and 2017. Analyses were conducted at the "person-crash" level because participants could be involved in more than one MVC. We examined the use of 36 PDI medication classes in the 120 days before and 120 days after MVC. We described the number and prevalence of PDI medication classes in the pre-MVC and post-MVC periods as well as the most common PDI medication classes started and stopped following the MVC. RESULTS: Among 124,954 person-crashes, the mean (SD) age was 76.0 (6.5) years, 51.3% were female, and 83.9% were non-Hispanic White. The median (Q1 , Q3 ) number of PDI medication classes was 2 (1, 4) in both the pre-MVC and post-MVC periods. Overall, 20.3% had a net increase, 15.9% had a net decrease, and 63.8% had no net change in the number of PDI medication classes after MVC. Opioids, antihistamines, and thiazide diuretics were the top PDI medication classes stopped following MVC, at incidences of 6.2%, 2.1%, and 1.7%, respectively. The top medication classes started were opioids (8.3%), skeletal muscle relaxants (2.2%), and benzodiazepines (2.1%). CONCLUSIONS: A majority of crash-involved older adults were exposed to multiple PDI medications before and after MVC. A greater proportion of person-crashes were associated with an increased rather than decreased number of PDI medications. The reasons why clinicians refrain from stopping PDI medications following an MVC remain to be elucidated.

Distribution of Adult Day Health Centers and Persons Living with Dementia Among Hospital Service Areas in Rhode Island.

INTRODUCTION: Adult day health centers (ADHCs) provide an important service to community-dwelling adults with functional dependency. This includes persons living with dementia (PLWD) and their caregivers, but we don't know how well ADHC capacity matches the distribution of PLWD. METHODS: For this cross-sectional study, we identified community-dwelling PLWD using Medicare claims, and ADHC capacity using licensure data. We aggregated both features by Hospital Service Area. By linear regression, we determined the association between ADHC capacity and community-dwelling PLWD. RESULTS: We identified 3836 community-dwelling Medicare beneficiaries living with dementia. We included 28 ADHCs, with licensed capacity for 2127 clients. The linear regression coefficient (95% Confidence Interval) for number of community-dwelling beneficiaries with dementia was 1.07 (0.6-1.53). DISCUSSION: Rhode Island's ADHC capacity distribution roughly approximates the distribution of persons with dementia. Plans for the future of dementia care in Rhode Island should consider these findings.

Class II/III Obesity Prevalence in Residents of US Nursing Homes: Cross-sectional Study and Forecasting 2030 with COVID-19 Perspective.

OBJECTIVES: This study aimed to better understand Class II/III obesity prevalence trends among older adults residing in nursing homes (NH) nationwide. METHODS: Our retrospective cross-sectional study evaluated Class II/III obesity (BMI ≥35 kg/m²) prevalence among NH residents in two independent national NH cohorts. We used databases from Veterans Administration NHs called Community Living Centers (CLCs) covering 7 years to 2022, and Rhode Island Medicare data covering 20 years ending in 2020. We also performed forecasting regression analysis of obesity trends. RESULTS: While VA CLC resident obesity prevalence was less overall and dipped during the COVID-19 pandemic, obesity prevalence increased in NH residents in both cohorts over the last decade and is predicted to do so through 2030. CONCLUSION: Obesity prevalence in NHs is on the rise. It will be important to understand clinical, functional, and financial implications for NHs, particularly if predictions on increases materialize.