A Smartwatch Step-Counting App for Older Adults: Development and Evaluation Study.

BACKGROUND: Older adults who engage in physical activity can reduce their risk of mobility impairment and disability. Short amounts of walking can improve quality of life, physical function, and cardiovascular health. Various programs have been implemented to encourage older adults to engage in physical activity, but sustaining their motivation continues to be a challenge. Ubiquitous devices, such as mobile phones and smartwatches, coupled with machine-learning algorithms, can potentially encourage older adults to be more physically active. Current algorithms that are deployed in consumer devices (eg, Fitbit) are proprietary, often are not tailored to the movements of older adults, and have been shown to be inaccurate in clinical settings. Step-counting algorithms have been developed for smartwatches, but only using data from younger adults and, often, were only validated in controlled laboratory settings. OBJECTIVE: We sought to develop and validate a smartwatch step-counting app for older adults and evaluate the algorithm in free-living settings over a long period of time. METHODS: We developed and evaluated a step-counting app for older adults on an open-source wrist-worn device (Amulet). The app includes algorithms to infer the level of physical activity and to count steps. We validated the step-counting algorithm in the lab (counting steps from a video recording, n=20) and in free-living conditions-one 2-day field study (n=6) and two 12-week field studies (using the Fitbit as ground truth, n=16). During app system development, we evaluated 4 walking patterns: normal, fast, up and down a staircase, and intermittent speed. For the field studies, we evaluated 5 different cut-off values for the algorithm, using correlation and error rate as the evaluation metrics. RESULTS: The step-counting algorithm performed well. In the lab study, for normal walking (R2=0.5), there was a stronger correlation between the Amulet steps and the video-validated steps; for all activities, the Amulet's count was on average 3.2 (2.1%) steps lower (SD 25.9) than the video-validated count. For the 2-day field study, the best parameter settings led to an association between Amulet and Fitbit (R2=0.989) and 3.1% (SD 25.1) steps lower than Fitbit, respectively. For the 12-week field study, the best parameter setting led to an R2 value of 0.669. CONCLUSIONS: Our findings demonstrate the importance of an iterative process in algorithm development before field-based deployment. This work highlights various challenges and insights involved in developing and validating monitoring systems in real-world settings. Nonetheless, our step-counting app for older adults had good performance relative to the ground truth (a commercial Fitbit step counter). Our app could potentially be used to help improve physical activity among older adults.

"Patient Lost to Follow-up": Opportunities and Challenges in Delivering Primary Care in Academic Medical Centers.

BACKGROUND: Academic health centers (AHCs) face unique challenges in providing continuity to a medically and socially complex patient population. Little is known about what drives patient loss in these settings. OBJECTIVE: Determine physician- and patient-based factors associated with patient loss in AHCs. DESIGN: Retrospective cohort study, embedded qualitative analysis. SETTING: Academic health center. PARTICIPANTS: All visits from 7/1/2014 to 6/30/2019; 89 physicians (51%) participated in a qualitative analysis. MEASURES: Physician-based factors (gender, years of service, hours of practice per week, trainee status, and departure during the study period) and patient-based factors (age, gender, race, limited English proficiency, public health insurance, chronic illness burden, and severe psychiatric illness burden) and their association with patient loss to follow-up, defined as a lapse in provider visit greater than 3 years. RESULTS: We identified 402,415 visits for 41,876 distinct patients. A total of 9332 (22.3%) patients were lost to follow-up. Patient factors associated with loss to follow-up included patient age < 40 (HR 3.12 (2.94-3.33)), identification as non-white (HR 1.07 (1.10-1.13)), limited English proficiency (HR 1.18 (1.04-1.33)), and use of public insurance (HR 1.12 (1.04-1.21)). Provider factors associated with patient loss included trainee status (HR 3.74 (2.43-5.75)) and having recently departed from the practice (HR 1.98, 1.66-2.35). Structured interviews with clinical providers revealed unfavorable relationships with providers and staff (35%), inconvenience accessing primary care (23%), unreliable health insurance (18%), difficulty accessing one's primary care provider (14%), and patient/provider transitions (10%) as reasons for patient loss. CONCLUSIONS: Younger patient age, markers of social vulnerability, and physician transiency are associated with patient loss at AHCs, providing targets to improve continuity of care within these settings.

Effectiveness of Ambulatory Telemedicine Care in Older Adults: A Systematic Review.

BACKGROUND: Disparities in healthcare access and delivery, caused by transportation and health workforce difficulties, negatively impact individuals living in rural areas. These challenges are especially prominent in older adults. DESIGN: We systematically evaluated the feasibility, acceptability, and effectiveness in providing telemedicine (TMed), searching the English-language literature for studies (January 2012 to July 2018) in the following databases: Medline (PubMed); Cochrane Library (Wiley); Web of Science; CINAHL; EMBASE (Ovid); and PsycINFO (EBSCO). PARTICIPANTS: Older adults (mean age = 65 years or older, and none were younger than 60 years). INTERVENTIONS: Interventions consisted of live, synchronous, two-way videoconferencing communication in nonhospital settings. All medical interventions were included. MEASUREMENTS: Quality assessment, using the Cochrane Collaboration's Risk-of-Bias Tool, was applied on all included articles, including a qualitative summary of all articles. RESULTS: Of 6616 citations, we reviewed the full text of 1173 articles, excluding 1047 that did not meet criteria. Of the 17 randomized controlled trials, the United States was the country with the most trials (6 [35%]), with cohort sizes ranging from 3 to 844 (median = 35) participants. Risk of bias among included studies varied from low to high. Our qualitative analysis suggests that TMed can improve health outcomes in older adults and that it could be used in this population. CONCLUSIONS: TMed is feasible and acceptable in delivering care to older adults. Research should focus on well-designed randomized trials to overcome the high degree of bias observed in our synthesis. Clinicians should consider using TMed in routine practice to overcome barriers of distance and access to care. J Am Geriatr Soc 67:1737-1749, 2019.

Association of Hospital Admission Risk Profile Score with Mortality in Hospitalized Older Adults.

OBJECTIVES: To evaluate the association of the Hospital Admission Risk Profile (HARP) score with mortality after discharge in a population of hospitalized older adults. DESIGN: Retrospective cohort study. PARTICIPANTS: Hospitalized patients aged 70 years or older. MEASUREMENTS: Patient age at the time of admission, modified Folstein Mini-Mental Status Exam score, and self-reported instrumental activities of daily living 2 weeks prior to admission were used to calculate a HARP score. The primary outcome assessed was overall mortality up to 365 days after hospital discharge. Cox proportional hazard analyses evaluated the association between HARP score and mortality adjusting for age, sex, and comorbidities associated with increased mortality. RESULTS: Of the 474 patients, 165 (34.8%) had a low HARP score, 177 (37.4%) had an intermediate, and 132 (27.8%) had a high score. HARP score was not associated with differences in 30-day readmission rates. High HARP score patients had higher mortality when compared to patients with low HARP scores at all time frames (30 days: 12.9% vs 1.8%, p < .05; 90 days: 19.7% vs 4.8%, p < .05; 365 days: 34.8% vs 16.9%, p < .05). In fully adjusted Cox proportional models, patients with high HARP scores had a 3.5 times higher odds of mortality when compared to low HARP score patients. CONCLUSION: The HARP score is a simple and easy to use instrument that identifies patients at increased risk for mortality after hospital discharge. Early identification of patients at increased risk for mortality has the potential to help guide treatment decisions following hospital discharge and provides additional information to providers and patients for shared decision making and may help in clarifying and achieving patient and family goals of care.

Weight Loss Interventions in Older Adults with Obesity: A Systematic Review of Randomized Controlled Trials Since 2005.

OBJECTIVES: To identify geriatric obesity interventions that can guide clinical recommendations. DESIGN: Systematic review using Medline (PubMed), Cochrane Central Register of Controlled Trials, Web of Science, CINAHL, EMBASE (Ovid), and PsycINFO (Proquest) from January 1, 2005, to October 12, 2015, to identify English-language randomized controlled trials. PARTICIPANTS: Individuals aged 60 and older (mean age ≥65) and classified as having obesity (body mass index ≥30 kg/m2 ). INTERVENTIONS: Behavioral weight loss interventions not involving pharmacological or procedural therapies lasting 6 months or longer. MEASUREMENTS: Two investigators performed the systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria and achieved a high concordance rate (97.3%) in summarizing the primary outcomes. The three primary outcomes were weight loss, physical performance, and quality of life. RESULTS: Of 5,741 citations, 19 were included. (Six studies were unique, and the remaining 13 were based on the same study population.) Duration ranged from 6 to 18 months (n = 405 participants, age range 66.7-71.1). Weight loss in the intervention groups ranged from 0.5 to 10.7 kg (0.1-9.3%). Five studies had a resistance exercise program accompanying a dietary component. Greater weight loss was observed in groups with a dietary component than those with exercise alone. Exercise alone led to better physical function but no significant weight loss. Combined dietary and exercise components led to the greatest improvement in physical performance measures and quality of life and mitigated reductions in muscle and bone mass observed in diet-only study arms. Heterogeneous outcomes were observed, which limited the ability to synthesize the data quantitatively. CONCLUSIONS: The evidence supporting geriatric obesity interventions to improve physical function and quality of life is of low to moderate quality. Well-designed trials are needed in this population.

Association Between Hospital Admission Risk Profile Score and Skilled Nursing or Acute Rehabilitation Facility Discharges in Hospitalized Older Adults.

OBJECTIVES: To evaluate whether the Hospital Admission Risk Profile (HARP) score is associated with skilled nursing or acute rehabilitation facility discharge after an acute hospitalization. DESIGN: Retrospective cohort study. SETTING: Inpatient unit of a rural academic medical center. PARTICIPANTS: Hospitalized individuals aged 70 and older from October 1, 2013 to June 1, 2014. MEASUREMENTS: Participant age at the time of admission, modified Folstein Mini-Mental State Examination score, and self-reported instrumental activities of daily living 2 weeks before admission were used to calculate HARP score. The primary predictor was HARP score, and the primary outcome was discharge disposition (home, facility, deceased). Multivariate analysis was used to evaluate the association between HARP score and discharge disposition, adjusting for age, sex, comorbidities, and length of stay. RESULTS: Four hundred twenty-eight individuals admitted from home were screened and their HARP scores were categorized as low (n = 162, 37.8%), intermediate (n = 157, 36.7%), or high (n = 109, 25.5%). Participants with high HARP scores were significantly more likely to be discharged to a facility (55%) than those with low HARP scores (20%) (P < .001). After adjustment, participants with high HARP scores were more than four times as likely as those with low scores to be discharged to a facility (odds ratio = 4.58, 95% confidence interval = 2.42-8.66). CONCLUSION: In a population of older hospitalized adults, HARP score (using readily available admission information) identifies individuals at greater risk of skilled nursing or acute rehabilitation facility discharge. Early identification for potential facility discharges may allow for targeted interventions to prevent functional decline, improve informed shared decision-making about post-acute care needs, and expedite discharge planning.

Use of a Wearable Activity Device in Rural Older Obese Adults: A Pilot Study.

Objective: Assess the feasibility and acceptability of Fitbit for supporting behavioral change in rural, older adults with obesity. Method: Eight adults aged ≥65 with a body mass index (BMI) ≥30kg/m2 were recruited from a rural practice and provided a Fitbit Zip device for 30 days. Participants completed validated questionnaires/interviews. Results: Mean age was 73.4 ± 4.0 years (50% female) with a mean BMI of 34.5 ± 4.5kg/m2. We observed reductions in exercise confidence (sticking to it: 34.5 ± 3.3 to 30.9 ± 4.3, p = .04; making time: 18.9 ± 1.3 to 17.0 ± 2.6, p = .03) but no changes in patient activation (45.4 ± 4.3 vs. 45.0 ± 3.9). All reported high satisfaction, seven (87.5%) found Fitbit easy to use, and five (62.5%) found the feedback useful. The majority (n = 6 [75.0%]) were mostly/very satisfied with the intervention. Consistent themes emerged regarding the benefit of self-monitoring and participant motivation. Common concerns included finding time to exercise and lack of a peer group. Conclusion: Use of Fitbit is feasible/acceptable for use among older rural obese adults but may lead to reduced confidence.