Poor mental health is common among older adults with pain, resulting in high economic burden and impaired quality of life. This retrospective, cross-sectional database study aimed to identify characteristics associated with good mental health status among United States (US) adults aged ≥50 years with self-reported pain in the last four weeks using a weighted sample of 2017 Medical Expenditure Panel Survey data. Hierarchical multivariable logistic regression models were used to identify statistically significant predictors of good (versus poor) perceived mental health status. From a weighted population of 57,074,842 individuals, 85.5% (95% confidence interval (CI) = 84.4%, 86.7%) had good perceived mental health. Good mental health was associated most strongly with physical health status (adjusted odds ratio (AOR) = 9.216, 95% CI = 7.044, 12.058). Employed individuals were 1.7 times more likely to report good mental health versus unemployed (AOR = 1.715, 95% CI = 1.199, 2.452). Individuals who had completed less than high school education (AOR = 0.750, 95% CI = 0.569, 0.987) or who reported having a limitation (AOR = 0.513, 95% CI = 0.384, 0.684) were less likely to report good mental health. These key characteristics can be utilized to predict mental health status, which may be investigated to better manage concurrent pain and poor mental health.

This cross-sectional study included a nationally representative sample of U.S. adults aged ≥50 years with self-reported pain in the past 4 weeks from the 2018 Medical Expenditure Panel Survey. Adjusted linear regression analyses accounted for the complex survey design and assessed differences in several types of annual health care expenditures between individuals who reported frequent exercise (≥30 min of moderate–vigorous intensity physical activity ≥5 times per week) and those who did not. Approximately 23,940,144 of 56,979,267 older U.S. adults with pain reported frequent exercise. In adjusted analyses, individuals who reported frequent exercise had 15% lower annual prescription medication expenditures compared with those who did not report frequent exercise (p = .007). There were no statistical differences between frequent exercise status for other health care expenditure types (p > .05). In conclusion, adjusted annual prescription medication expenditures were 15% lower among older U.S. adults with pain who reported frequent exercise versus those who did not.

ObjectivesThis study aimed to determine if differences exist in healthcare expenditures of older United States (US) adults with pain based on self-reported mental health status, which is important to know given the prevalence of pain and poor mental health in the USA.DesignThis was a cross-sectional study.SettingUS Medical Expenditure Panel Survey (MEPS) interviews.ParticipantsUS adults aged ≥50 years, with self-reported pain in the past 4 weeks and positive healthcare expenditure in the 2018 Medical Expenditure Panel Survey (MEPS). The independent variable was poor versus good mental health status.Primary and secondary outcome measuresDescriptive statistics compared demographic characteristics (using chi-square tests) and mean healthcare expenditures (using t-tests) between groups. Adjusted linear regression models with logarithmically-transformed expenditures compared differences in: total; inpatient; outpatient; emergency room; office-based; prescription medications and other expenditures. Analyses accounted for the complex MEPS design and were weighted to produce nationally-representative results. The a priori alpha level was 0.05.ResultsThe weighted population included 57 134 711 older US adults with self-reported pain (14.4% poor mental health, 85.6% good mental health). Compared with individuals with good mental health, individuals with poor mental health had higher unadjusted total expenditures (US$20 231 vs US$13 379, p<0.0001), higher prescription medication expenditures (US$5924 vs US$3610, p<0.0001) and higher other expenditures (US$4833 vs US$2285, p<0.0001). In adjusted multivariable linear regression models, there were no differences in expenditures between those with poor mental health and those with good mental health status.ConclusionsThere were no statistically significant differences in adjusted annual (2018) positive healthcare expenditures among older US adults with pain and poor versus good mental health status.

Introduction Antipsychotics are commonly used to treat psychotic symptoms and severe mental illnesses. Treatment guidelines recommend antipsychotics be titrated quickly to therapeutic effect in the acute setting but acknowledge that determining the optimal dose is complicated by a delay between treatment initiation and therapeutic response. The purpose of this study was to evaluate antipsychotic titration patterns in an inpatient psychiatric hospital. Methods This study is a retrospective chart review of adult patients admitted to a teaching hospital and initiated on an antipsychotic for treatment of psychosis between January and December 2018. Patients were excluded if they had substance-induced psychosis, delirium, were prescribed &gt;1 antipsychotic, or had no antipsychotic dose changes. The primary outcome was the average titration rate of the newly initiated antipsychotic. Secondary outcomes included differences in titration rate between involuntary and voluntary admissions and other antipsychotic characteristics. Results Of 149 patients included, the majority had a primary diagnosis of schizophrenia. Antipsychotics were titrated on average every 2 days regardless of admission type. Eighteen percent of patients were titrated to guideline-recommended maximum doses, and it took, on average, 3 days for patients to reach their final dose during hospitalization. Average length of stay was 9 days, and 43.6% of patients were readmitted within 1 year. Discussion Antipsychotics are titrated rapidly in the inpatient setting despite a lack of evidence regarding the impact of titration rate on clinical outcomes. Further studies comparing slow versus rapid titration strategies are needed to elucidate the impact of this on patient outcomes.

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