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Background: Central nervous system (CNS) medication use is common among older adults, yet the impact of hospitalizations on use remains unclear. This study details CNS medication use, discontinuations, and user profiles during hospitalization periods. Methods: Retrospective cohort study using electronic health records on patients ≥65 years, from three hospitals (2018–2020), and prescribed a CNS medication around hospitalization (90 days prior to 90 days after). Latent class transitions analysis (LCTA) examined profiles of CNS medication class users across four time points (90 days prior, admission, discharge, 90 days after hospitalization). Results: Among 4666 patients (mean age 74.3 ± 9.3 years; 63% female; 70% White; mean length of stay 4.6 ± 5.6 days (median 3.0 [2.0, 6.0]), the most commonly prescribed CNS medications were antidepressants (56%) and opioids (49%). Overall, 74% (n = 3446) of patients were persistent users of a CNS medication across all four time points; 7% (n = 388) had discontinuations during hospitalization, but of these, 64% (216/388) had new starts or restarts within 90 days after hospitalization. LCTA identified three profile groups: (1) low CNS medication users, 54%–60% of patients; (2) mental health medication users, 30%–36%; and (3) acute/chronic pain medication users, 9%–10%. Probability of staying in same group across the four time points was high (0.88–1.00). Transitioning to the low CNS medication use group was highest from admission to discharge (probability of 9% for pain medication users, 5% for mental health medication users). Female gender increased (OR 2.4, 95% CI 1.3–4.3), while chronic kidney disease lowered (OR 0.5, 0.2–0.9) the odds of transitioning to the low CNS medication use profile between admission and discharge. Conclusions: CNS medication use stays consistent around hospitalization, with discontinuation more likely between admission and discharge, especially among pain medication users. Further research on patient outcomes is needed to understand the benefits and harms of hospital deprescribing, particularly for medications requiring gradual tapering. [ABSTRACT FROM AUTHOR]

BACKGROUND: Hospital‐acquired disability (HAD) is common and often related to low physical activity while in the hospital. OBJECTIVE: To examine whether wearable hospital activity trackers can be used to predict HAD. DESIGN: A prospective observational study between January 2016 and March 2017. SETTING: An academic medical center. PARTICIPANTS: Community‐dwelling older adults, aged 60 years or older, enrolled within 24 hours of admission to general medicine (n = 46). MAIN MEASURES: Primary outcome was HAD, defined as having one or more new activity of daily living deficits, decline of four or greater on the Late‐Life Function and Disability Instrument (calculated between baseline and discharge), or discharge to a skilled nursing facility. Hospital activity (mean active time, mean sedentary time, and mean step counts per day) was measured using ankle‐mounted accelerometers. The association of the literature‐based threshold of 900 steps/day with HAD was also evaluated. RESULTS: Mean age was 73.2 years (SD = 9.5 years), 48% were male, and 76% were white. Median length of stay was 4 days (interquartile range [IQR] = 2.0‐6.0 days); 61% (n = 28) reported being able to walk without assistance of another person or walking aid at baseline. Median daily activity time and step counts were 1.1 h/d (IQR = 0.7‐1.7 h/d) and 1455.7 steps/day (IQR = 908.5‐2643 steps/day), respectively. Those with HAD (41%; n = 19) had lower activity time (0.8 vs 1.4 h/d; P =.04) and fewer step counts (1186 vs 1808 steps/day; P =.04), but no difference in sedentary time, compared to those without HAD. The 900 steps/day threshold had poor sensitivity (40%) and high specificity (85%) for detecting HAD. CONCLUSIONS: Low hospital physical activity, as measured by wearable accelerometers, is associated with HAD. Clinicians can utilize wearable technology data to refer patients to physical/occupational therapy services or other mobility interventions, like walking programs. J Am Geriatr Soc 68:261–265, 2020 [ABSTRACT FROM AUTHOR]