Abstract
Almost 25% of Medicare beneficiaries live in residential long-term care (LTC) (eg, independent or assisted living facility or nursing home). There are few reliable statistics on completed suicide in LTC, in part because of data limitations. To estimate the number of suicides associated with residential LTC (ie, among persons in a facility, transitioning into or out of a facility, or otherwise associated with LTC) among adults 55 and older and, secondarily, to identify whether machine learning tools could improve the quality of suicide surveillance data. Cross-sectional epidemiologic study (conducted in 2018) of restricted-access data from the National Violent Death Reporting System (NVDRS) (2003-2015) using restricted-access case narratives from suicides and undetermined deaths among adults 55 years and older in 27 states. Participants were all suicides and undetermined deaths (N = 47 759) among persons 55 years and older. Long-term care cited in the coroner/medical examiner case narrative, whether as a reason for self-harm or the injury location, identified using machine learning natural language processing (NLP) algorithms plus manual review of texts. Number and characteristics (eg, demographics, health history, and means of injury) of suicides associated with LTC. The κ statistic was used to estimate the reliability of the existing NVDRS injury location codes relative to cases identified by the algorithm. Among 47 759 persons 55 years and older (median age, 64 years; 77.6% male; 90.0% non-Hispanic white), this study identified 1037 suicide deaths associated with LTC, including 428 among older adults living in LTC, 449 among older adults transitioning to LTC, and 160 otherwise associated with LTC. In contrast, there were only 263 cases coded with the existing NVDRS location code "supervised residential facility," which had poor agreement with cases that the algorithm identified as occurring in LTC (κ statistic, 0.30; 95% CI, 0.26-0.35). Over a 13-year period, approximately 2.2% of suicides among adults 55 years and older were associated with LTC in some manner. Clinicians, administrators, and policy makers should consider ways to promote the mental health and well-being of older adults experiencing functioning limitations and their families. Natural language processing may be a useful way to improve abstraction of variables in the NVDRS.
Highlights
Forty million US adults are 65 years and older, and 5.5 million are 85 years and older; by 2050, 1 in 5 will be 65 or older.[1]
Among 47 759 persons 55 years and older, this study identified 1037 suicide deaths associated with long-term care (LTC), including 428 among older adults living in LTC, 449 among older adults transitioning to LTC, and 160 otherwise associated with LTC
There were only 263 cases coded with the existing National Violent Death Reporting System (NVDRS) location code “supervised residential facility,” which had poor agreement with cases that the algorithm identified as occurring in LTC (κ statistic, 0.30; 95% CI, 0.26-0.35)
Summary
Forty million US adults are 65 years and older, and 5.5 million are 85 years and older; by 2050, 1 in 5 will be 65 or older.[1]. A recent editorial noted that “...lack of progress in suicide prevention is in large part owing to our limited understanding of this problem...[W]e lack a firm understanding of the fundamental properties of [suicidal thoughts and behaviors], and when, why, and among whom they unfold.”3(p11). Understanding the location of suicidal behavior can help identify potential “points of engagement” for reducing suicide risk, including before acute crisis.[4] One location relevant to suicide prevention among older adults is residential long-term care (LTC) (eg, nursing homes, assisted living facilities, and continuing care retirement communities).[5] While 90% of US adults want to remain living in their own home as they age,[6] this desire to live independently often does not match the reality of “aging in place.”. While 90% of US adults want to remain living in their own home as they age,[6] this desire to live independently often does not match the reality of “aging in place.” Only 40% who are 70 years and older report that it is “very easy” to live independently, and 20% say that they cannot do so without occasional assistance.[6,7]
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