Comparing two durations of medically tailored meals posthospitalization: A randomized clinical trial.

BACKGROUND: Medically tailored meals (MTM) may be beneficial to patients after hospital discharge. OBJECTIVE: To determine if 2 versus 4 weeks of MTM posthospitalization will improve patient outcomes. DESIGN: Randomized unblinded trial. SETTINGS AND PARTICIPANTS: Six hundred and fifty patients pending hospital discharge with at least one chronic condition. INTERVENTION: One MTM a day for 2 versus 4 weeks. MAIN OUTCOME AND MEASURES: The primary outcome was a change from baseline to 60 days in the Hospital Anxiety Depression Scale (HADS). Secondary outcomes measured change in the Katz activities of daily living (ADLs), DETERMINE nutritional risk, and all-cause emergency department (ED) visits and rehospitalizations. RESULTS: From baseline to 60 days the HADS anxiety subscale changed 5.4-4.9 in the 2-week group (p = .03) and 5.4-5.3 in the 4-week group (p = .49); the difference in change between groups 0.4 (p = .25). HADS changed 5.4-4.8 in the 2-week group (p = .005) and 5.3-5.1 in the 4-week group (p = .34); the difference in change between groups 0.4 (p = .18). ADL score changed from 5.3 to 5.6 in the 2-week group (p ≤ .0001) and 5.2-5.5 in the 4-week group (p ≤ .0001); the difference in change between groups -0.01 (p = .90). The DETERMINE changed in the 2-week group from 7.2 to 6.4 (p = .0006) and from 7 to 6.7 in the 4-week group (p = .19); the difference in change between groups 0.5 (p = .13). There was no difference in ED visits and rehospitalizations between groups or time to rehospitalization. CONCLUSIONS: Different durations of short-term MTM did not affect patient-centered or utilization outcomes.

Demographic, Clinical, and Behavioral Factors Associated With Electronic Nicotine Delivery Systems Use in a Large Cohort in the United States.

Introduction: Our primary purpose is to understand comorbidities and health outcomes associated with electronic nicotine delivery systems (ENDS) use. Methods: Study participants were Kaiser Permanente (KP) members from eight US regions who joined the Kaiser Permanente Research Bank (KPRB) from September 2015 through December 2019 and completed a questionnaire assessing demographic and behavioral factors, including ENDS and traditional cigarette use. Medical history and health outcomes were obtained from electronic health records. We used multinomial logistic regression to estimate odd ratios (ORs) and 95% confidence intervals (CIs) of current and former ENDS use according to member characteristics, behavioral factors, and clinical history. We used Cox regression to estimate hazard ratios (HRs) and 95% CIs comparing risk of health outcomes according to ENDS use. Results: Of 119 593 participants, 1594 (1%) reported current ENDS use and 5603 (5%) reported past ENDS use. ENDS users were more likely to be younger, male, gay or lesbian, and American Indian / Alaskan Native or Asian. After adjustment for confounding, current ENDS use was associated with current traditional cigarette use (OR = 39.55; CI:33.44-46.77), current marijuana use (OR = 6.72; CI:5.61-8.05), history of lung cancer (OR = 2.64; CI:1.42-4.92), non-stroke cerebral vascular disease (OR = 1.55; CI:1.21-1.99), and chronic obstructive pulmonary disease (OR = 2.16; CI:1.77-2.63). Current ENDS use was also associated with increased risk of emergency room (ER) visits (HR = 1.17; CI: 1.05-1.30) and death (HR = 1.84; CI:1.02-3.32). Conclusions: Concurrent traditional cigarette use, marijuana use, and comorbidities were prevalent among those who used ENDS, and current ENDS use was associated with an increased risk of ER visits and death. Additional research focused on health risks associated with concurrent ENDS and traditional cigarette use in those with underlying comorbidities is needed.

Characteristics of Patients and Proxy Caregivers Using Patient Portals in the Setting of Serious Illness and End of Life.

Background: There are few studies examining the usage and utility of patient portals among seriously ill and end-of-life populations and their caregivers. Objective: The aim of this study was to describe portal user characteristics among patients and their caregivers (proxy login) at two time points: (1) the 12 months following an electronic medical record flag for serious illness and (2) during the last 12 months of life. Methods: A retrospective cohort analysis of Kaiser Permanente Colorado (KPCO) patients with serious illness, as defined by Kaiser Permanente's prognostic algorithm, and their proxy caregivers was performed for the two time periods. Use was characterized as (1) the discrete number of days the portal was used and (2) the number of days that portal features were accessed. Differences in use by user characteristics were assessed. Results: Patients flagged for serious illness (N = 6129) were 70.4 ± 14.2 years of age, and used the portal on average 50.4 days. Patients (N = 6517) in the last year of life were 76.7 ± 13.7 years of age and used the portal on average 43 days. Caregiver proxy use of the portal was low in both cohorts. Patients who were older, female, non-White, and healthier were less likely to use the portal. Conclusions: In comparison with overall KPCO portal use and recent patient portal studies examining use patterns, patient portal use was high among patients flagged with serious illness and nearing the end of life. However, because use was associated with age, gender, and race, addressing barriers to portal adoption among underserved populations and caregiver proxies is key to better leveraging patient portal systems for palliative and end-of-life care.

Using Self-Reported Data to Segment Older Adult Populations with Complex Care Needs.

BACKGROUND: Tailored care management requires effectively segmenting heterogeneous populations into actionable subgroups. Using patient reported data may help identify groups with care needs not revealed in traditional clinical data. METHODS: We conducted retrospective segmentation analyses of 9,617 Kaiser Permanente Colorado members age 65 or older at risk for high utilization due to advanced illness and geriatric issues who had completed a Medicare Health Risk Assessment (HRA) between 2014 and 2017. We separately applied clustering methods and latent class analyses (LCA) to HRA variables to identify groups of individuals with actionable profiles that may inform care management. HRA variables reflected self-reported quality of life, mood, activities of daily living (ADL), urinary incontinence, falls, living situation, isolation, financial constraints, and advance directives. We described groups by demographic, utilization, and clinical characteristics. RESULTS: Cluster analyses produced a 14-cluster solution and LCA produced an 8-class solution reflecting groups with identifiable care needs. Example groups included: frail individuals with memory impairment less likely to live independently, those with poor physical and mental well-being and ADL limitations, those with ADL limitations but good mental and physical well-being, and those with few health or other limitations differentiated by age, presence or absence of a documented advance directive, and tobacco use. CONCLUSIONS: Segmenting populations with complex care needs into meaningful subgroups can inform tailored care management. We found groups produced through cluster methods to be more intuitive, but both methods produced actionable information. Applying these methods to patient-reported data may make care more efficient and patient-centered.