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      Artificial Intelligence–Powered Digital Health Platform and Wearable Devices Improve Outcomes for Older Adults in Assisted Living Communities: Pilot Intervention Study

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          Abstract

          Background

          Wearables and artificial intelligence (AI)–powered digital health platforms that utilize machine learning algorithms can autonomously measure a senior’s change in activity and behavior and may be useful tools for proactive interventions that target modifiable risk factors.

          Objective

          The goal of this study was to analyze how a wearable device and AI-powered digital health platform could provide improved health outcomes for older adults in assisted living communities.

          Methods

          Data from 490 residents from six assisted living communities were analyzed retrospectively over 24 months. The intervention group (+CP) consisted of 3 communities that utilized CarePredict (n=256), and the control group (–CP) consisted of 3 communities (n=234) that did not utilize CarePredict. The following outcomes were measured and compared to baseline: hospitalization rate, fall rate, length of stay (LOS), and staff response time.

          Results

          The residents of the +CP and –CP communities exhibit no statistical difference in age ( P=.64), sex ( P=.63), and staff service hours per resident ( P=.94). The data show that the +CP communities exhibited a 39% lower hospitalization rate ( P=.02), a 69% lower fall rate ( P=.01), and a 67% greater length of stay ( P=.03) than the –CP communities. The staff alert acknowledgment and reach resident times also improved in the +CP communities by 37% ( P=.02) and 40% ( P=.02), respectively.

          Conclusions

          The AI-powered digital health platform provides the community staff with actionable information regarding each resident’s activities and behavior, which can be used to identify older adults that are at an increased risk for a health decline. Staff can use this data to intervene much earlier, protecting seniors from conditions that left untreated could result in hospitalization. In summary, the use of wearables and AI-powered digital health platform can contribute to improved health outcomes for seniors in assisted living communities. The accuracy of the system will be further validated in a larger trial.

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          Most cited references52

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          Lifespan and Healthspan: Past, Present, and Promise.

          The past century was a period of increasing life expectancy throughout the age range. This resulted in more people living to old age and to spending more years at the older ages. It is likely that increases in life expectancy at older ages will continue, but life expectancy at birth is unlikely to reach levels above 95 unless there is a fundamental change in our ability to delay the aging process. We have yet to experience much compression of morbidity as the age of onset of most health problems has not increased markedly. In recent decades, there have been some reductions in the prevalence of physical disability and dementia. At the same time, the prevalence of disease has increased markedly, in large part due to treatment which extends life for those with disease. Compressing morbidity or increasing the relative healthspan will require "delaying aging" or delaying the physiological change that results in disease and disability. While moving to life expectancies above age 95 and compressing morbidity substantially may require significant scientific breakthroughs; significant improvement in health and increases in life expectancy in the United States could be achieved with behavioral, life style, and policy changes that reduce socioeconomic disparities and allow us to reach the levels of health and life expectancy achieved in peer societies.
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            Interventions for preventing falls in older people in care facilities and hospitals

            Background Falls in care facilities and hospitals are common events that cause considerable morbidity and mortality for older people. This is an update of a review first published in 2010 and updated in 2012. Objectives To assess the effects of interventions designed to reduce the incidence of falls in older people in care facilities and hospitals. Search methods We searched the Cochrane Bone, Joint and Muscle Trauma Group Specialised Register (August 2017); Cochrane Central Register of Controlled Trials (2017, Issue 8); and MEDLINE, Embase, CINAHL and trial registers to August 2017. Selection criteria Randomised controlled trials of interventions for preventing falls in older people in residential or nursing care facilities, or hospitals. Data collection and analysis One review author screened abstracts; two review authors screened full-text articles for inclusion. Two review authors independently performed study selection, 'Risk of bias' assessment and data extraction. We calculated rate ratios (RaR) with 95% confidence intervals (CIs) for rate of falls and risk ratios (RRs) and 95% CIs for outcomes such as risk of falling (number of people falling). We pooled results where appropriate. We used GRADE to assess the quality of evidence. Main results Thirty-five new trials (77,869 participants) were included in this update. Overall, we included 95 trials (138,164 participants), 71 (40,374 participants; mean age 84 years; 75% women) in care facilities and 24 (97,790 participants; mean age 78 years; 52% women) in hospitals. The majority of trials were at high risk of bias in one or more domains, mostly relating to lack of blinding. With few exceptions, the quality of evidence for individual interventions in either setting was generally rated as low or very low. Risk of fracture and adverse events were generally poorly reported and, where reported, the evidence was very low-quality, which means that we are uncertain of the estimates. Only the falls outcomes for the main comparisons are reported here. Care facilities Seventeen trials compared exercise with control (typically usual care alone). We are uncertain of the effect of exercise on rate of falls (RaR 0.93, 95% CI 0.72 to 1.20; 2002 participants, 10 studies; I² = 76%; very low-quality evidence). Exercise may make little or no difference to the risk of falling (RR 1.02, 95% CI 0.88 to 1.18; 2090 participants, 10 studies; I² = 23%; low-quality evidence). There is low-quality evidence that general medication review (tested in 12 trials) may make little or no difference to the rate of falls (RaR 0.93, 95% CI 0.64 to 1.35; 2409 participants, 6 studies; I² = 93%) or the risk of falling (RR 0.93, 95% CI 0.80 to 1.09; 5139 participants, 6 studies; I² = 48%). There is moderate-quality evidence that vitamin D supplementation (4512 participants, 4 studies) probably reduces the rate of falls (RaR 0.72, 95% CI 0.55 to 0.95; I² = 62%), but probably makes little or no difference to the risk of falling (RR 0.92, 95% CI 0.76 to 1.12; I² = 42%). The population included in these studies had low vitamin D levels. Multifactorial interventions were tested in 13 trials. We are uncertain of the effect of multifactorial interventions on the rate of falls (RaR 0.88, 95% CI 0.66 to 1.18; 3439 participants, 10 studies; I² = 84%; very low-quality evidence). They may make little or no difference to the risk of falling (RR 0.92, 95% CI 0.81 to 1.05; 3153 participants, 9 studies; I² = 42%; low-quality evidence). Hospitals Three trials tested the effect of additional physiotherapy (supervised exercises) in rehabilitation wards (subacute setting). The very low-quality evidence means we are uncertain of the effect of additional physiotherapy on the rate of falls (RaR 0.59, 95% CI 0.26 to 1.34; 215 participants, 2 studies; I² = 0%), or whether it reduces the risk of falling (RR 0.36, 95% CI 0.14 to 0.93; 83 participants, 2 studies; I² = 0%). We are uncertain of the effects of bed and chair sensor alarms in hospitals, tested in two trials (28,649 participants) on rate of falls (RaR 0.60, 95% CI 0.27 to 1.34; I² = 0%; very low-quality evidence) or risk of falling (RR 0.93, 95% CI 0.38 to 2.24; I² = 0%; very low-quality evidence). Multifactorial interventions in hospitals may reduce rate of falls in hospitals (RaR 0.80, 95% CI 0.64 to 1.01; 44,664 participants, 5 studies; I² = 52%). A subgroup analysis by setting suggests the reduction may be more likely in a subacute setting (RaR 0.67, 95% CI 0.54 to 0.83; 3747 participants, 2 studies; I² = 0%; low-quality evidence). We are uncertain of the effect of multifactorial interventions on the risk of falling (RR 0.82, 95% CI 0.62 to 1.09; 39,889 participants; 3 studies; I² = 0%; very low-quality evidence). Authors' conclusions In care facilities: we are uncertain of the effect of exercise on rate of falls and it may make little or no difference to the risk of falling. General medication review may make little or no difference to the rate of falls or risk of falling. Vitamin D supplementation probably reduces the rate of falls but not risk of falling. We are uncertain of the effect of multifactorial interventions on the rate of falls; they may make little or no difference to the risk of falling. In hospitals: we are uncertain of the effect of additional physiotherapy on the rate of falls or whether it reduces the risk of falling. We are uncertain of the effect of providing bed sensor alarms on the rate of falls or risk of falling. Multifactorial interventions may reduce rate of falls, although subgroup analysis suggests this may apply mostly to a subacute setting; we are uncertain of the effect of these interventions on risk of falling. Interventions for preventing falls in older people in care facilities and hospitals Review question How effective are interventions designed to reduce falls in older people in care facilities and hospitals? Background Falls by older people in care facilities, such as nursing homes, and hospitals are common events that may cause loss of independence, injuries, and sometimes death as a result of injury. Effective interventions to prevent falls are therefore important. Many types of interventions are in use. These include exercise, medication interventions that include vitamin D supplementation and reviews of the drugs that people are taking, environment or assistive technologies including bed or chair alarms or the use of special (low/low) beds, social environment interventions that target staff members and changes in the organisational system, and knowledge interventions. A special type of intervention is the multifactorial intervention, where the selection of single interventions such as exercise and vitamin D supplementation is based on an assessment of a person's risk factors for falling. Falls are reported in two ways in our review. One outcome is rate of falls, which is the number of falls. The other outcome is risk of falling, which is the number of people who had one or more falls. Search date We searched the healthcare literature for reports of randomised controlled trials relevant to this review up to August 2017. Study characteristics This review included 95 randomised controlled trials involving 138,164 participants. Seventy-one trials (40,374 participants) were in care facilities, and 24 (97,790 participants) in hospitals. On average, participants were 84 years old in care facilities and 78 years old in hospitals. In care facilities, 75% were women and in hospitals, 52% were women. Quality of the evidence The majority of trials were at high risk of bias, mostly relating to lack of blinding. With few exceptions, the quality of evidence for individual interventions in either setting was generally rated as low or very low. Risk of fracture and adverse events were generally poorly reported and, where reported, the evidence was very low quality, which means that we are uncertain of the estimates. Key results There was evidence, often from single studies, for a wide range of interventions used for preventing falls in both settings. However, in the following we summarise only the falls outcomes for four key interventions in care facilities and three key interventions in hospitals. Care facilities We are uncertain of the effect of exercise on the rate of falls (very low-quality evidence) and it may make little or no difference to the risk of falling (low-quality evidence). General medication review may make little or no difference to the rate of falls (low-quality evidence) or the risk of falling (low-quality evidence). Prescription of vitamin D probably reduces the rate of falls (moderate-quality evidence) but probably makes little or no difference to the risk of falling (moderate-quality evidence). The population included in these studies appeared to have low vitamin D levels. We are uncertain of the effect of multifactorial interventions on the rate of falls (very low-quality evidence). They may make little or no difference to the risk of falling (low-quality evidence). Hospitals We are uncertain whether physiotherapy aimed specifically at reducing falls in addition to usual rehabilitation in the ward has an effect on the rate of falls or reduces the risk of falling (very low-quality evidence). We are uncertain of the effect of bed alarms on the rate of falls or risk of falling (very low-quality evidence). Multifactorial interventions may reduce the rate of falls, although this is more likely in a rehabilitation or geriatric ward setting (low-quality evidence). We are uncertain of the effect of these interventions on risk of falling.
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              Fear of falling and restriction of mobility in elderly fallers.

              To identify the characteristics of elderly persons who develop a fear of falling after experiencing a fall and to investigate the association of this fear with changes in health status over time. A prospective study of falls over a 2-year period (1991-92). Falls were ascertained using bimonthly postcards plus telephone interview with a standardized (World Health Organisation) questionnaire for circumstances, fear of falling and consequences of each reported fall. Each participant underwent a physical exam and subjective health assessment each year form 1990 to 1993. New-Mexico Aging Process Study, USA. 487 elderly subjects (> 60 years) living independently in the community. Fear of falling after experiencing a fall. 70 (32%) of 219 subjects who experienced a fall during the 2 year study period reported a fear of falling. Women were more likely than men to report fear of falling (74% vs 26%). Fallers who were afraid of falling again had significantly ore balance (31.9% vs 12.8%) and gait disorders (31.9% vs 7.4%) at entry in the study in 1990. Among sex, age, mental status, balance and gait abnormalities, economic resource and physical health, logistic regression analysis show gait abnormalities and poor self-perception of physical health, cognitive status and economic resources to be significantly associated with fear of falling. Subjects who reported a fear of falling experienced a greater increase in balance (P = 0.08), gait (P < 0.01) and cognitive disorders (P = 0.09) over time, resulting in a decrease in mobility level. The study indicated that about one-third of elderly people develop a fear of falling after an incident fall and this issue should be specifically addressed in any rehabilitation programme.
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                Author and article information

                Contributors
                Journal
                JMIR Aging
                JMIR Aging
                JA
                JMIR Aging
                JMIR Publications (Toronto, Canada )
                2561-7605
                Jul-Dec 2020
                10 September 2020
                : 3
                : 2
                : e19554
                Affiliations
                [1 ] CarePredict Plantation, FL United States
                [2 ] Lifewell Senior Living Corporation Houston, TX United States
                [3 ] Department of Geriatric Medicine and Palliative Care Icahn School of Medicine Mount Sinai New York, NY United States
                [4 ] Alzheimer’s Drug Discovery Foundation New York, NY United States
                Author notes
                Corresponding Author: Gerald Wilmink jerry.wilmink@ 123456gmail.com
                Author information
                https://orcid.org/0000-0003-0967-7707
                https://orcid.org/0000-0003-1696-3402
                https://orcid.org/0000-0003-2525-6363
                https://orcid.org/0000-0001-8639-7210
                https://orcid.org/0000-0002-1692-6655
                https://orcid.org/0000-0002-3310-0492
                https://orcid.org/0000-0002-2820-7770
                Article
                v3i2e19554
                10.2196/19554
                7516685
                32723711
                3509e39a-fcf4-4c9e-9286-5278309ae70e
                ©Gerald Wilmink, Katherine Dupey, Schon Alkire, Jeffrey Grote, Gregory Zobel, Howard M Fillit, Satish Movva. Originally published in JMIR Aging (http://aging.jmir.org), 10.09.2020.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Aging, is properly cited. The complete bibliographic information, a link to the original publication on http://aging.jmir.org, as well as this copyright and license information must be included.

                History
                : 24 April 2020
                : 20 May 2020
                : 2 July 2020
                : 28 July 2020
                Categories
                Original Paper
                Original Paper

                health technology,artificial intelligence,ai,preventive,senior technology,assisted living,long-term services,long-term care providers

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