Social Isolation and Loneliness in Older Adults Opportunities for the Health Care System (2020) / Chapter Skim
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7 Role of the Health Care System
7 Role of the Health Care System
Pages 123-146
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From page 123... ...
increased the risk of developing coronary heart disease and stroke, independently of traditional cardiovascular disease risk factors (Valtorta et al., 2016a)
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Social support: the actual or perceived availability of resources (e.g., informa tional, tangible, emotional) from others, typically one's social network.
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As noted previously in this report, the existing evidence base shows that a variety of indicators are used to evaluate social isolation and loneliness, including the strength of an individual's relationships and social networks, a person's living arrangements, and a person's psychosocial functioning. Similarly, health care utilization is often determined differently in different studies, with readmission rates, length of hospital stay, number of hospitalizations, the use of outpatient services, and primary care visits being examined in various studies.
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Evidence of No Impact on Utilization Some studies have found that having fewer social supports has limited to no impact on health care utilization by older adults. In one study, older patients with weaker social relationships did not place greater demands on ambulatory care (as defined by physician visits and community- or home-based services)
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. Comprehensive and advanced primary care settings serving older adults are well suited to the task of caring for individuals living with social isolation and loneliness and could ultimately help link these individuals to effective interventions.
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9) Another Canadian study of residents of assisted living facilities showed that those with poor social relationships had a significantly increased risk for placement in a nursing home (Maxwell et al., 2013)
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SOCIAL DETERMINANTS OF HEALTH AND THE HEALTH CARE SYSTEM Targeting the major social and behavioral risk factors for health offers a way to improve population health and even reduce health disparities. Healthy People,1 a program of the U.S.
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However, the authors found that MMCOs are "not yet systematically engaged in comprehensive [social determinants of health] strategies to improve health or change health care utilization patterns" (Gottlieb et al., 2016, p.
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. However, the study also notes that collecting data on social determinants of health in the health care setting "may be affected by unconscious or implicit biases held by program leaders and practitioners" (NASEM, 2019, p.
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Researchers are considering how informatics might be used to make social determinants of health data collected in the EHR accessible, the use of implementation science to address program development and deployment, and natural language processing to identify information related to the social determinants of health, such as an individual patient experiencing social isolation, in clinical notes (Bazemore et al., 2018; Hripcsak et al., 2015; Zhu et al., 2019)
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Screening Versus Assessment for Social Isolation and Loneliness Loneliness and social isolation have high prevalence rates in adults over age 60 (see Chapter 1) and have been linked to significant health consequences and increased mortality risk (see Chapters 2 and 3)
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Yet, because of the high prevalence rates and broad-reaching health effects, the committee concludes that the health care system is well poised to develop methods and processes for identifying social isolation and loneliness in health care settings, even if the methods do not rely on a formal screening protocol. As such, the committee concludes that it is more appropriate to talk about the identification of loneliness and isolation as risk factors for health consequences rather than about how to screen for social isolation and loneliness.
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. As the health care delivery system mobilizes to incorporate assessments and, as the research develops, to integrate interventions for the social determinants of health, some researchers are cautioning that not all patients may view primary care interventions of this type as positive.
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Using this framework and working with the available evidence, the committee concluded that the existing tools likely to have the greatest success in clinical settings are the Berkman–Syme Social Network Index (for measuring social isolation) and the three-item UCLA Loneliness Scale (for measuring loneliness)
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Data for predictive analytics can be gathered from a variety of sources, including various types of information captured in the EHR, such as visit patterns, medications, and patient portal messages; retail activity such as prescriptions filled or over-the-counter medications purchased; social media and internet usage, including search history data;3 and physical activity monitors such as wearable sensors and other consumer health devices. Other sources of data that may be of use for predictive analytics are information captured in files maintained in social service agencies and, in the future, outcomes data from the widespread implementation of assessment tools for social isolation and loneliness and for potentially precipitating life events (Weissman et al., 2020)
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The domain "social connections and social isolation" was described as an item not routinely collected in clinical settings but nonetheless a crucial domain for inclusion, with the evidence supporting its inclusion equivalent to the evidence supporting the inclusion of race, education, physical activity, tobacco use, and neighborhood characteristics. The measures recommended in the Phase 2 report (IOM, 2014)
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The report had a pragmatic emphasis on choices that enable action in clinical settings, but it stopped short of making recommendations related to the communication and coordination infrastructure (e.g., between medical and community-based service providers) that would be needed to implement interventions to address issues related to social determinants for individual patients or groups.
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. This report identified four key barriers to the widespread use of social determinants of health data for improving health: 1.
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. In a parallel process, OCHIN, Inc., a nonprofit health care innovation center in Oregon, reported on the process that was used and the lessons that were learned through the implementation of a social determinants of health screening tool across a network of more than 400 federally qualified health centers in the KPNW region, taking advantage of the KPNW tool's social isolation domain and questions (Gold et al., 2017)
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• It is more appropriate to consider and plan for the identification of lone liness and social isolation as risk factors for health consequences than to consider how to screen for social isolation and loneliness. • The current identification tools most likely to be successfully imple mented in clinical settings are the Berkman–Syme (for measuring social isolation)
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RECOMMENDATION 7-1: Health care providers and practices should periodically perform an assessment using one or more validated tools to identify older adults experiencing social isolation and loneliness and to initiate potential preventive interventions after having identified individu als at elevated risk due to life events (e.g., loss of someone significant, geographic move, relevant health conditions)
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Furthermore, the committee notes that the thresholds for identifying socially isolated or lonely older adults and their risk of health impacts will vary with the tool used and the health profile of the person being assessed. While there are limitations to current tools, the committee asserts that the use of existing validated tools is necessary in order to address social isolation and loneliness more fully in clinical settings.
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Therefore, in order to improve the evidence around the use of specific tools in clinical settings, the committee makes the following recommendation: RECOMMENDATION 7-2: Health care systems should create opportuni ties for clinicians to partner with researchers to evaluate the application of currently available evidence-based tools for assessing social isolation and loneliness in clinical settings, including testing and applications for specific populations. Finally, the committee concludes that assessment data should be included in clear locations in the EHR.
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how to best integrate information from patients' assessments into their health record in order to make determinations about future care and the identification of risk (see Recommendation 9-4 in Chapter 9 for the need for more research on interventions in clinical settings)
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