Purpose: As new quality metrics and interventions for potentially preventable emergency department (ED) visits are implemented, we sought to compare methods for evaluating the prevalence and costs of potentially preventable ED visits that were related to cancer and chronic disease among a commercially insured oncology population in the year after treatment initiation. Methods: We linked SEER records in western Washington from 2011 to 2016 with claims from two commercial insurers. The study included patients who were diagnosed with a solid tumor and tracked ED utilization for 1 year after the start of chemotherapy or radiation. Cancer symptoms from the Centers for Medicare & Medicaid Services metric and a patient-reported outcome intervention were labeled potentially preventable (PpCancer). Prevention Quality Indicators of the Agency for Healthcare Research and Quality were labeled potentially preventable–chronic disease (PpChronic). We reported the primary diagnosis, all diagnosis field coding (1 to 10), and 2016 adjusted reimbursements. Results: Of 5,853 eligible patients, 27% had at least one ED visit, which yielded 2,400 total visits. Using primary diagnosis coding, 49.8% of ED visits had a PpCancer diagnosis, whereas 3.2% had a PpChronic diagnosis. Considering all diagnosis fields, 45.0%, 9.4%, and 18.5% included a PpCancer only, a PpChronic only, and both a PpCancer and a PpChronic diagnosis, respectively. The median reimbursement per visit was $735 (interquartile ratio, $194 to $1,549). Conclusion: The prevalence of potentially preventable ED visits was generally high, but varied depending on the diagnosis code fields and the group of codes considered. Future research is needed to understand the complex landscape of potentially preventable ED visits and measures to improve value in cancer care delivery.

Purpose of the Study: To explore individual, social, environmental, and program-related motivators, barriers, and impacts of sedentary behavior (SB) reduction among a group of overweight and obese older adults aged 60 and older.Design and Methods: Semistructured interviews were conducted with 24 participants following a SB reduction intervention. Transcripts from these interviews were iteratively coded by a team, and key themes were defined and refined guided by the social–ecological framework.Results: Motivators included the desire to improve health, newly acquired awareness of SB, the ease of incorporating SB reduction into current lifestyle, an adaptable environment, and the use of reminders. Barriers included existing health conditions, enjoyment of sedentary activities, unadaptable environments, fatigue, and difficulty understanding SB reduction as distinct from physical activity (PA). Participants reported impacts on physical and mental health and changes in awareness, exercise, and daily activity.Implications: Although in many ways motivators and barriers to reducing SB are similar to those of PA, SB interventions have special considerations and may ultimately be easier for some individuals to incorporate into their lifestyle.

Background: Few studies characterize older adult physical activity and sitting patterns using accurate accelerometer and concurrent posture measures. In this descriptive paper, we report accelerometer data collection protocols, consent rates, and physical behavior measures from a population-based cohort study (Adult Changes in Thought, ACT). Methods: The ACT study holds enrollment steady at approximately 2000 members of Kaiser Permanente Washington aged 65+ without dementia undergoing detailed biennial assessments. In 2016 the ACT-Activity Monitor (ACT-AM) sub-study was initiated to obtain data from wearing activPAL and ActiGraph devices for 7 days following regular biennial visits. We describe the methods protocol of ACT-AM and present characteristics of people who did and did not consent to wear devices. We compute inverse probability of response weights and incorporate these weights in linear regression models to estimate means and 95% confidence intervals (CI) of device-based pattern metrics, adjusted for wear time and demographic factors, and weighted to account for potential selection bias due to device-wear consent. Results: Among 1885 eligible ACT participants, 56% agreed to wear both devices (mean age 77 years, 56% female, 89% non-Hispanic white, 91% with post-secondary education). On average, those who agreed to wear devices were younger and healthier. Estimated mean (95% CI) activPAL-derived sitting, standing, and stepping times were 10.2 h/day (603–618 min/day), 3.9 h/day (226–239 min/day), and 1.4 h/day (79–84 min/day), respectively. Estimated mean ActiGraph derived sedentary (Vector Magnitude [VM] < =18 counts/15 s), light intensity (VM 19–518 counts/15 s), and moderate-to-vigorous intensity (VM > 518 counts/15 s) physical activity durations were 9.5 h/day (565–577 min/day), 4.5 h/day (267–276 min/day), and 1.0 h/day (59–64 min/day). Participants who were older, had chronic conditions, and were unable to walk a half-mile had higher sedentary time and less physical activity. Conclusions: Our recruitment rate demonstrates the feasibility of cohort participants to wear two devices that measure sedentary time and physical activity. Data indicate high levels of sitting time in older adults but also high levels of physical activity using cut-points developed for older adults. These data will help researchers test hypotheses related to physical behavior and health in older adults in the future.

Introduction: Older adults, who already have higher levels of social isolation, loneliness, and sedentary behavior, are particularly susceptible to negative impacts from social distancing mandates meant to control the spread of COVID-19. We sought to explore the physical, mental, and social health impacts of the pandemic on older adults and their coping techniques.Materials and Methods: We conducted 25 semi-structured interviews with a sub-sample of participants in an ongoing sedentary behavior reduction intervention. Interviews were recorded and transcribed, and iterative coding was used to extract key themes.Results: Most participants reported an increase in sedentary behavior due to limitations on leaving their home and increased free time to pursue seated hobbies (e.g., reading, knitting, tv). However, many participants also reported increased levels of intentional physical activity and exercise, particularly outdoors or online. Participants also reported high levels of stress and a large decrease in in-person social connection. Virtual connection with others through phone and video was commonly used to stay connected with friends and family, engage in community groups and activities, and cope with stress and social isolation. Maintenance of a positive attitude and perspective gained from past hardships was also an important coping strategy for many participants.Discussion: The COVID-19 pandemic and associated social distancing measures have impacted older adults' perceived levels of activity, stress, and social isolation, but many leveraged technology and prior life experiences to cope. These themes could inform future interventions for older adults dealing with chronic stress and isolation.

Physical activity is known to prevent falls; however, use of widely available exercise programs for older adults, including EnhanceFitness and Silver Sneakers, has not been examined in relation to effects on falls among program participants. We aimed to determine whether participation in EnhanceFitness or Silver Sneakers is associated with a reduced risk of falls resulting in medical care. A retrospective cohort study examined a demographically representative sample from a Washington State integrated health system. Health plan members aged 65 or older, including 2,095 EnhanceFitness users, 13,576 Silver Sneakers users, and 55,127 nonusers from 2005 through 2011, were classified as consistent users (used a program ≥2 times in all years they were enrolled in the health plan during the study period); intermittent users (used a program ≥2 times in 1 or more years enrolled but not all years), or nonusers of EnhanceFitness or Silver Sneakers. The main outcome was measured as time-to-first-fall requiring inpatient or out-of-hospital medical treatment based on the International Classification of Diseases, 9th Revision, Clinical Modification, Sixth Edition and E-codes. In fully adjusted Cox proportional hazards models, consistent (hazard ratio [HR], 0.74; 95% confidence interval [CI], 0.63-0.88) and intermittent (HR, 0.87; 95% CI, 0.8-0.94) EnhanceFitness participation were both associated with a reduced risk of falls resulting in medical care. Intermittent Silver Sneakers participation showed a reduced risk (HR, 0.93; 95% CI, 0.90-0.97). Participation in widely available community-based exercise programs geared toward older adults (but not specific to fall prevention) reduced the risk of medical falls. Structured programs that include balance and strength exercise, as EnhanceFitness does, may be effective in reducing fall risk.

Introduction: Sitting patterns predict several healthy aging outcomes. These patterns can potentially be measured using hip-worn accelerometers, but current methods are limited by an inability to detect postural transitions. To overcome these limitations, we developed the Convolutional Neural Network Hip Accelerometer Posture (CHAP) classification method. Methods: CHAP was developed on 709 older adults who wore an ActiGraph GT3X+ accelerometer on the hip, with ground-truth sit/stand labels derived from concurrently worn thigh-worn activPAL inclinometers for up to 7 d. The CHAP method was compared with traditional cut-point methods of sitting pattern classification as well as a previous machine-learned algorithm (two-level behavior classification). Results: For minute-level sitting versus nonsitting classification, CHAP performed better (93% agreement with activPAL) than did other methods (74%–83% agreement). CHAP also outperformed other methods in its sensitivity to detecting sit-to-stand transitions: cut-point (73%), TLBC (26%), and CHAP (83%). CHAP’s positive predictive value of capturing sit-to-stand transitions was also superior to other methods: cut-point (30%), TLBC (71%), and CHAP (83%). Day-level sitting pattern metrics, such as mean sitting bout duration, derived from CHAP did not differ significantly from activPAL, whereas other methods did: activPAL (15.4 min of mean sitting bout duration), CHAP (15.7 min), cut-point (9.4 min), and TLBC (49.4 min). Conclusion: CHAP was the most accurate method for classifying sit-to-stand transitions and sitting patterns from free-living hip-worn accelerometer data in older adults. This promotes enhanced analysis of older adult movement data, resulting in more accurate measures of sitting patterns and opening the door for large-scale cohort studies into the effects of sitting patterns on healthy aging outcomes.