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Suicidal Ideation in US Nursing Homes: Association With Individual and Facility Factors
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Suicidal Ideation in US Nursing Homes: Association with Individual and Facility Factors Helena Temkin-Greener PhD , Jessica Orth MS, MPH , Yeates Conwell MD , Yue Li PhD PII: DOI: Reference:
S1064-7481(19)30591-3 https://doi.org/10.1016/j.jagp.2019.12.011 AMGP 1391
To appear in:
The American Journal of Geriatric Psychiatry
Received date: Revised date: Accepted date:
7 November 2019 19 December 2019 19 December 2019
Please cite this article as: Helena Temkin-Greener PhD , Jessica Orth MS, MPH , Yeates Conwell MD , Yue Li PhD , Suicidal Ideation in US Nursing Homes: Association with Individual and Facility Factors, The American Journal of Geriatric Psychiatry (2020), doi: https://doi.org/10.1016/j.jagp.2019.12.011
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.
Suicidal Ideation in US Nursing Homes: Association with Individual and Facility Factors
Helena Temkin-Greener, PhD,1Jessica Orth, MS, MPH1, Yeates Conwell, MD2, Yue Li, PhD1,
1
Department of Public Health Sciences, University of Rochester School of Medicine and
Dentistry, Rochester, NY 2
Department of Psychiatry, University of Rochester School of Medicine and Dentistry,
Rochester, NY
Corresponding Author: Helena Temkin-Greener, PhD
Public Health Sciences 265 Crittenden Blvd. Rochester, NY 14642 Phone: 585-275-8713 Email: [email protected]
Key words: suicidal ideation, nursing homes, risk-factors
This study was supported by funding from the National Institute of Mental Health, grant 1RF1MH117528-01 Conflicts of Interest: none
1
Highlights 1. What is the frequency and timing of suicidal ideation (SI) in US nursing homes, and what is the association of SI with individual and facility level factors? 2. SI is highest at admission and declines with the duration of a nursing home stay. Several potentially modifiable individual and facility-level factors are associated with SI risk throughout the stay. 3. The frequency of SI in nursing homes may be under-reported, and the PHQ-9 item used to assess SI may not be well understood.
ABSTRACT Objectives: To assess prevalence of suicidal ideation (SI) among new post-acute and long-stay nursing home (NH) admissions and examine the associations with individual and NH-level factors. Setting/Participants: 1,864,102 post-acute and 304,106 long-stay admissions to just over 15,000 NHs between 7/1/2014 and 6/30/2015. Measurement: Using 100% of the national Minimum Data Set 3.0 we identified SI and key covariates. SI was based on responses to one item on the PHQ-9 scale. For post-acute residents SI was measured at admission and discharge. For long-stay residents, SI was assessed at admission and assessments closest to 90, 180, and 365 days thereafter. Patient socio-demographics, functional and cognitive status, co-morbid conditions and other covariates were included as independent variables, as were several NH-level factors. Logistic regression models were fit to estimate SI risk at admission and at subsequent time intervals. Results: Observed 2-week prevalence rates of SI were highest at admission (1.24% for postacute and 1.84% for long-stays) and declined thereafter at each subsequent time interval. The odds of SI were significantly increased for residents with severe depression at admission and all subsequent intervals. Residents in for-profits had significantly lower rates of SI, compared with those in not-for-profits. Conclusions: Our findings demonstrate that SI risk in NHs is highest at admission and subsequently declines. We found several potentially modifiable individual-level risk factors for SI. The identification of SI may be seriously underreported in for-profit-facilities. Future research may be needed to explore how the PHQ-9 item on SI is understood by residents and recorded by staff. Key words: suicidal ideation, nursing homes, risk-factors
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INTRODUCTION Death by suicide and suicidal ideation (SI) among older adults, including those in nursing homes (NHs), are of growing concern both in the US and abroad. 1–6 NH placement has long been known to be one of the most distressing healthcare transitions faced by older adults, often associated with an increase in depression and a possible precipitant of suicide.7 Every year over 1.6 million Medicare beneficiaries in the US are admitted to Skilled Nursing Facilities (SNF) and while most expect to be discharged back to the community, only 40% ever are. 8 Studies of completed suicide in NHs are relatively few, many are at least 2 decades old, and their findings are highly variable. While some have reported that suicide rates in NHs are substantially lower than in the community,9 others have shown the incidence of suicide among older adults to be comparable in NHs and in the community.10 Still others have suggested that suicides in this care setting remain considerably under recognized and underreported.11 A recent systematic review of the literature from 1990 through 2015 identified only 5 studies of suicides in US NHs, most based on small, convenience samples and differing methodologies.3 One national-level study using data from the National Violent Death Reporting System has shown that between 2003 and 2015, about 2.2% of suicides among adults age 55 and over were associated with transitions to or from NHs. 12 At the same time, prevalence of suicidal ideation (SI), a risk factor for suicidal behavior, has been reported as being substantially higher in NHs than in the general population.13 A recent systematic review, which identified only a handful of studies from the US and elsewhere, reported SI within the past month as ranging from 5% to 33% of NH residents.2 Prevalence of SI was reported to be the highest within the first seven months of entering a NH,14 and some have suggested this may reflect on the severity of distress associated with moving from one’s home in the community to a NH.7 As with completed suicides, these studies also relied on small, convenience samples and many are over 2 decades old. Prior to 2011, SI assessments in NHs were rarely conducted. With the implementation of the Minimum Data Set (MDS) 3.0 in late
3
2010, all US NHs (certified by Medicare and Medicaid) are required to routinely administer the Patient Health Questionnaire (PHQ-9) to all residents,15 which among others includes a question on presence of self-harm thoughts. The availability and the uniformity of data resulting from the MDS assessments provide an opportunity to examine SI in US NHs in detail. We used calendar year (CY)2014-2016 MDS 3.0 data to address two objectives. First, we measured the prevalence of SI at NH entry and at several intervals thereafter to identify periods of greatest risk. Second, we examined associations between SI and individual as well as NH-level characteristics to identify potential correlates that may be important in the early identification and management of suicide risk in NHs.
METHODS Data Sources and Sample Data came from several sources. We used 100% of the national Minimum Data Set (MDS 3.0) for CY2014-2016. The MDS data are available for all patients admitted to Medicaid and/or Medicare certified NHs in the US or approximately 15,600 facilities. These NHs are required to conduct and report detailed resident assessments at admission and thereafter quarterly, annually or when a significant change in health status occurs. Validity and reliability of the MDS assessments, and of the PHQ-9 items, have been documented in prior literature. 15–18 Item 9 on the PHQ-9 has been considered to be a predictor of SI with several studies demonstrating increased risk of suicide attempts or deaths among community outpatients and among users of services provided by the Veterans Health Administration, who responded affirmatively to this item.19,20 The MDS contains information on resident’s socio-demographics, functional and cognitive status, and diagnostics and therapeutics. Other sources of data are identified below. The study sample consisted of Medicare beneficiaries newly admitted to a US NHs between 7/1/2014 and 6/30/2015, with no NH stay in the prior 180 days (1/1/2014-6/30/2014). The follow-up period for any admissions during the study window was up to 395 days (7/1/2015-
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7/29/2016) in order to capture the MDS assessments performed closest to one year after admission. We created a new resident ID and nested episodes within resident, so a resident may appear more than once if they had multiple admissions during the year-window. Residents were further identified as post-acute (short-stay) and long-stay (custodial), based on the algorithm developed for CMS by RTI International.21 Residents who were comatose and those for whom the PHQ-9 SI items were missing were excluded (1.15% of sample). Our final analytical sample included 1,864,102 post-acute and 304,106 long-stay admissions to just over 15,000 NHs in a period of one year. The study protocol was reviewed and approved by the institutional review board of the University of Rochester School of Medicine and Dentistry.
Outcome Measure SI was measured by presence (1) or absence (0) of symptom on item 9 of the PHQ-9 scale, which queries if a resident “over the last 2 weeks, [has] been bothered by …thoughts that you would be better off dead, or hurting yourself in some way.” Presence or absence of SI was assessed by a patient self-report (D0200I) or was staff-reported (D0500I) if a resident was known to be “rarely/never understood”. Because SI may be more frequent at points of transition, we measured SI for post-acute residents at admission and discharge, and for long-stay residents at admission and at assessments closest to 90, 180, and 365 days after NH admission.
Independent Variables Both individual- and NH-level independent variables were included following a literature review and consultations with clinicians. These included residents’ socio-demographics such as age, gender, marital status, and race/ethnicity. Clinical and diagnostic covariates, based on the assessments closest to the time periods examined, included: functional status (level of
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impairments in activities of daily living, scale from 0 to 28); cognitive status (scale of 0-3 categorized as none/mild [0, 1] versus moderate/severe [2, 3] impairment);22 aggressive behavior (scale of 0-12 categorized as none/mild [0-2] versus moderate/severe [3-12]);23 depressive symptoms (defined as a score of 10 or higher on the PHQ-8 – self or staff reported);17,24 and a set of binary variables indicating presence/absence (1/0) of specific comorbid conditions (dementia, psychiatric disorders, delusions, hallucinations). We also included a count variable for the presence of other comorbidities (cancer, heart conditions, gastrointestinal, genitourinary, infections, metabolic, musculoskeletal, neurologic, nutritional, pulmonary, and vision impairment). Presence of pain negatively affecting sleep or activities was coded as a binary (1/0) variable, as was presence of pressure ulcers (stage 2 or higher). We also accounted for the use (binary 1/0) of behavioral health medications such as antipsychotic, antianxiety, antidepressant or hypnotic. Finally, we also included binary indicators as to whether a resident needed an interpreter to communicate with caregivers, and whether presence or absence of PHQ-9 symptoms was self- or staff-reported.
We also defined several NH-level variables, which have been hypothesized to be associated with depression and risk of suicide in long-term care, although empirical evidence on these associations has been very scant.4,10,25 These covariates were: bed-size; profit status (for profit or non-profit), chain membership, occupancy rate, % of Medicare and % of Medicaid residents, number of certified nurse aide (CNA) hours per resident per day; total number of licensed nursing hours per resident per day, overall facility 5-star rating, and facility rural versus urban location. Data on facility characteristics and on star ratings were obtained from 2015 CMS Nursing Home Compare (NHC) web site, the Area Health Resources File, and Brown University’s LTCfocus. A county-level variable measuring NH market bed competition was also included.
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Statistical Analyses
We first performed bivariate analyses to examine the observed rates of SI for post-acute and long-stay NH residents at admission and at specified assessment times following admission. For each group of residents, we examined both time invariant (e.g. sociodemographics) and time-varying (e.g. cognitive impairment, functional status, depressive symptoms) characteristics, as well as facility-level factors. We fit separate logistic regression models to estimate the risk of SI at post-acute admission and discharge, and at long-stay admission and assessments occurring at 90, 180, and 365 days after NH admission. All models included Huber-White robust standard error estimates clustering at the NH level. State dummies were included in all models to control for state-level variations that may influence the prevalence of SI and its reporting in the MDS. Predicted SI rates were calculated based on coefficient estimation for all covariates. We conducted sensitivity analyses to assess the impact of residents’ death. We compared the analyses in which residents who died during the follow-up periods were excluded to the analyses based on the total sample. Findings from these analyses were not measurably different and therefore we presented only the results based on the entire sample.
Analyses were performed using SAS version 9.4 (SAS Institute, Inc. Cary, NC).
RESULTS Among short-stay NH residents, the observed SI rate was 1.24% at admission declining to 0.50% at discharge; while among long-stay NH residents, the observed SI rate was 1.81% at admission, 1.21% at 90 days, 1.19% at 180 days, and 0.98% at 365 days after admission. The predicted rates remained largely unchanged (Figure 1).
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Table 1 shows that at NH admission, residents with SI were slightly older, more likely to be male, unmarried, and non-Hispanic White. They were less likely to need interpreter services and less likely to have staff-observed PHQ-9 symptoms. Residents with SI had a lower prevalence of moderate/severe cognitive impairment but higher prevalence of depressive symptoms and moderate/severe aggressive behavior compared to residents without SI. Regarding diagnostic characteristics, residents with SI had higher prevalence of psychiatric conditions, delusions, hallucinations, more comorbidities, higher frequency of pressure ulcers, higher use of BH medications, and more pain compared to those without SI. Residents with SI were more likely to reside in smaller, non-profit, and rural NHs in less competitive NH markets compared to residents without SI. There were no statistically significant differences between residents with and without SI regarding functional status, prevalence of dementia, and the 5-star NH quality. The differences between residents with and without SI were similar at discharge or during other follow-up periods, and thus are not shown for ease of presentation. Our multivariate analyses largely confirmed these unadjusted differences in SI (Table 2). After controlling for residents’ socio-demographics, health status, clinical conditions, as well as NH, market, and state covariates, the predicted probabilities of SI remained largely unchanged and showed similar downward trends (to observed rates) as residents were discharged (shortstay) or continued as long-stay residents. Compared to Whites, African-Americans had more than 40% lower odds of SI for both post-acute and for long-stay residents at admission, and declining thereafter. Odds ratios were also lower at admission for residents who were Hispanic, but over time, the decline was not as precipitous or statistically significant for long-stay residents in this population subgroup. For post-acute residents, presence of depressive symptoms (PHQ8=>10) increased the odds of SI at admission more than ten-fold and even more so at discharge. Depressive symptoms were also significantly associated with SI for long-stay residents at admission, and increasing more than 9-fold at 90, 180, and 365 days following.
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For post-acute and long-stay residents, respectively, we found 57% and 29% higher odds of moderate/severe aggressive behavior on admission, with increasing risk at subsequent assessments; as well as 25% and 29% higher odds of pain; 27% and 25% higher odds of behavioral health medication use; and 43% and 29% higher odds of psychiatric diagnoses. The odds of SI were 7.5% lower for residents with dementia and 11.6% lower for residents with moderate/severe cognitive impairment at admission, and at all subsequent assessments. Facility structural characteristics such as bed size, chain membership or occupancy rates were not consistently or significantly associated with SI. However, post-acute residents in for-profit facilities had 24.0% lower odds of SI at admission and 25.8% lower odds at discharge compared to residents in not-for-profits; for long-stay residents at admission, 90, 180, and 365 days from NH admission the odds were of SI were 28.6%, 36.2%, and 40.3% lower, respectively. Furthermore, residents in NHs with higher CNA staffing experienced higher odds of SI for post-acute and long-stay residents alike, at admission and at subsequent assessments. The association with licensed nursing hours/resident day for the most part was not statistically significant. Similarly, we found no significant association of SI with other facility characteristics such as 5-star rating or rural-urban location. The effect size of the association with % Medicare and % Medicaid residents, while statistically significant, was very small and thus clinically not meaningful. In highly competitive NH markets, the odds of SI were lower for post-acute residents at admission and at discharge, but were not consistently significant for long stay residents. After controlling for individual, facility, and market level factors there were significant variations in the predicted probability of SI across states. Figure 2 depicts these predicted probabilities for both post-acute and long-stay admissions. Residents in NHs located in the north and mid-west parts of the country, as well as those in Maine, Vermont, and New
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Hampshire, had consistently higher rates of SI compared to residents in facilities located in the southern and east coast states.
DISCUSSION To our knowledge, this is a first study of SI in US NHs based on recent national-level assessments provided through the Minimum Data Set 3.0. Our findings suggest that the MDSbased coding of SI among NH residents is less frequent than previously reported. We found that around the point of NH admission, the average rate of SI (in the past two weeks) was below 2% for post-acute and for long-stay residents. Consistent with prior studies4,14 we found SI to be higher at admission than at subsequent assessment periods. For post-acute residents, SI declined precipitously, by almost 60%, between admission and discharge, while for long-stay residents a significant decline occurred within 3 months of admission with a further decrease by the end one year of stay. These findings suggest that NH placement may itself be a significant risk for SI. While the risk of SI may attenuate over time, certain individual-level covariates appear to exacerbate that risk. Not unexpectedly, we found presence of moderate-to-severe depressive symptoms to sizably increase that risk throughout the NH stay. Consistent with prior studies, several other factors were positively associated with SI, for example aggressive behavior, psychiatric conditions, presence of pain that interferes with sleep or activities, and the use of such common medications as antidepressants, antianxiety, antipsychotics, and hypnotics. Our findings further showed that the effect size of these factors vis a vis SI increased with the duration of the NH stay. Also consistent with the literature, we found that residents with dementia and/or cognitive impairment had lower odds of SI, 26 although we were unable to determine if this is due to some “protective” factor or is a function of the inability to respond or have this item accurately recorded.
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With regard to organizational-level factors that may be associated with SI, our study was able to shed some light on what has been a significant gap in the literature. 2 We identified two NH-level covariates that were consistently associated with SI. A one hour (per resident/day) increase in CNA staffing increased the odds of SI by 10%-to-20%, depending on the assessment period. While somewhat counter-intuitive, this finding may suggest that identification of residents with severe depression, often associated with SI, may be better in facilities with more CNAs. Prior research has suggested that CNAs who are in close daily contact with the residents were best positioned to recognize changes in residents’ mood and behavior,27 and thus may be able to call attention to those most vulnerable for suicidal risk. We also found that residents in for-profit homes had consistently and very significantly lower risk-adjusted odds of SI, at admission and at subsequent assessment intervals, compared to residents in not-for-profits. For-profit status of NHs has been found to be associated with worse quality of care,28 and poorer resident outcomes,29 thus making this finding a bit counterintuitive if lower SI rate is believed to indicate better quality of care. However, for-profits have also been shown to have lower staffing levels and higher staff burdens.30 When staff are overburdened and may not be very adept in the administration of psychometric assessments it is possible that the presence of SI, not a common occurrence, is overlooked. Thus, underreporting of SI in for-profit NHs appears to be the most likely explanation for this finding. The inclusion of the item on self-harm and suicidal thoughts on the PHQ-9 of the MDS 3.0 assessment forms implies that NHs have in place processes and systems to appropriately treat or refer residents identified as being at risk for suicide. However, a recent national survey has reported that more than 25% of NHs have difficulty in assessing residents for emotional problems, 45% are unable to provide behavioral health crisis interventions, and a third cannot adequately coordinate with community providers for services they lack within. Furthermore, these shortcoming in services appear to be exacerbated by lack of psychiatrically trained nurses and high turnover among the CNAs. 31 Thus, although identifying residents at high risk for
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suicide may be critical to effective prevention and appropriate treatment, it remains somewhat uncertain if most NHs in the US have the resources and expertise needed to adequately care for such residents. The issue of accurately screening for suicidal/death ideation may be further confounded by the way the single item on SI is phrased, requiring a yes or no response to having had “thoughts that you would be better off dead, or hurting yourself in some way”. 32 The wording of this item combines two constructs, each of which has an ambiguous relationship to suicidal thoughts. Some have suggested that death ideation (be better off dead) is a normal part of approaching end-of-life and does not necessarily signify active planning or intent to end one’s life.32 The second part of this PHQ-9 item (hurting yourself in some way) does not distinguish injury with the intent to die from non-suicidal self-injury. However, prior studies have suggested that even death ideation, not just active suicidal thoughts, is likely associated with higher risk for suicide.19,20,33 Hence, a positive answer to this item should mark the need for further assessment. Several limitations should be noted. First, the data are largely cross sectional and our findings should not be interpreted as causal, only as associations. Second, while the analyses adjust for numerous individual and facility level factors, it is possible that unmeasured variables may confound our findings. Finally, although previous validation studies demonstrated relatively high validity of the MDS-3 items it is possible that SI was under-reported and under-identified in many NHs, especially, as we suggested, in for-profit NHs. Despite this potential limitation, our analyses confirmed important correlates for SI such as mood and psychiatric disorders, and identified important patterns of changes in reported rates at different points of NH care. Despite the growing awareness and the recent focus on suicides in NHs in the popular press,34,35 understanding of suicide risk and the identification of associated factors remain relatively meager. This study is the first to use the national MDS 3.0 assessments, which all Medicare and Medicaid certified NHs are required to complete for their residents, to identify and
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characterize SI. Our findings demonstrate that SI in NH is highest at admission, likely reflecting the stress of transitioning from home, and declines with the duration of stay. We identified several modifiable individual-level risk factors, largely consistent with prior literature. Our findings also suggest that identification of residents who are at risk of SI may be seriously underreported in for-profit facilities. Future research should explore how the item on SI in PHQ-9 is both understood by residents and recorded by staff.
13
ACKNOWLEDGMENTS This study was supported by funding from the National Institute of Mental Health, grant 1RF1MH117528-01
Conflicts of Interest: none
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Figure legends Figure 1: Observed and Predicted Suicide Ideation Risk at Admission and During the NH Stay: Post-Acute and Long-Stay Residents Figure 2A: Post-Acute Admissions: Predicted Nursing Home SI Rated by State Lowest Rate: 0.40 (FL) Highest Rate: 4.12 (ND)
Figure 2B: Long-Stay Admissions: Predicted Nursing Home SI Rates by State Lowest Rate: 0.43 (NM) Highest Rate: 4.61 (SD)
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Table 1: Descriptive Characteristics of Newly Admitted Post-Acute and Long-Stay Nursing Home Residents by Presence of Suicidal Ideation. Suicidal Ideation N: 28,548 1.24 1.81
No Suicidal Ideation N: 2,139,660 98.76 98.19
p-value (
or t-test)
Post-acute admission <0.001 Long-stay admission Resident Covariates Age <0.001 78.39 13.50 76.92 12.82 Female 59.01% 60.99% <0.001 Interpreter 1.43% 3.05% <0.001 Staff observed PHQ-9 4.81% 8.23% <0.001 Married 30.72% 33.08% <0.001 Race: <0.001 0: White 88.01% 78.36% 1: African American 4.42% 10.76% 2: Hispanic 2.33% 4.48% 3: Other 5.25% 6.39% Moderate/severe 17.85% 18.51% 0.001 cognitive impairment Functional status 0.848 17.02 4.73 17.01 4.70 PHQ-8: 10+ 41.36% 5.16% <0.001 Moderate/severe 5.11% 2.23% <0.001 aggressive behavior Dementia 20.85% 20.65% 0.409 Psychiatric 56.99% 40.87% <0.001 Delusions 4.40% 1.81% <0.001 Hallucinations 2.81% 0.97% <0.001 Number of diseases <0.001 3.60 1.54 3.45 1.49 Pressure ulcers 8.44% 7.97% 0.003 BH medications 65.99% 50.67% <0.001 Pain 31.41% 21.46% <0.001 NH Covariates Total number of beds <0.001 123.62 73.28 132.54 76.57 For-profit 60.19% 72.27% <0.001 Chain 56.04% 58.90% <0.001 Occupancy rate <0.001 83.22 17.78 83.93 16.02 Aide nursing <0.001 2.55 0.65 2.48 0.56 hours/resident day Total licensed nursing <0.001 1.77 0.67 1.81 0.68 hours/resident day Overall 5-star rating: 0.077 1 12.64% 12.38% 2-4 62.33% 62.15% 5 24.45% 25.01% Urban NH 74.67% 82.02% <0.001 % Medicare residents <0.001 17.83 16.11 21.21 17.29 % Medicaid residents <0.001 52.63 23.20 51.75 23.70 County covariates Market competition (1<0.001 0.82 0.22 0.86 0.19 HHI) Notes. PHQ: Patient Health Questionnaire; BH medications: behavioral health medications; NH: nursing home; HHI: Herfindahl-Hirschman Index
19
Table 2: Predicted Probability of Suicidal Ideation for Post-Acute and Long-Stay Nursing Home Residents: By Assessment Perioda Post-Acute: Admission N=1,642,394
Post-Acute: Discharge N=1,064,416
Long-stay: Admission N=267,721
Long-Stay: Admission+90 N=234,768
Long-stay: Admission+180 N=174,382
Long-stay: Admission+365 N=128,719
Suicide ideation Observed rate (per 100)
1.24%
0.50%
1.81%
1.21%
1.19%
0.98%
Average predicted probability rate (per 100) Resident Covariates
1.24%
0.51%
1.84%
1.24%
1.22%
0.99%
Odds Ratio (Wald 95%CI) 1.02 (1.01, 1.02) * 0.77 (0.74, 0.79) * 0.83 (0.68, 1.01) 0.40 (0.37, 0.44) * 0.83 (0.81, 0.86) *
Odds Ratio (Wald 95%CI) 1.02 (1.02, 1.03) * 0.72 (0.68, 0.77) * 0.93 (0.63, 1.39) 0.61 (0.49, 0.74) * 0.79 (0.74, 0.84) *
Odds Ratio (Wald 95%CI) 1.01 (1.01, 1.02) * 0.83 (0.77, 0.88) * 0.75 (0.57, 0.97) * 0.35 (0.30, 0.41) * 0.94 (0.88, 1.01)
Odds Ratio (Wald 95%CI) 1.01 (1.01, 1.02) * 0.86 (0.79, 0.94) * 0.85 (0.59, 1.22) 0.30 (0.25, 0.36) * 1.01 (0.92, 1.11)
Odds Ratio (Wald 95%CI) 1.01 (1.01, 1.02) * 0.84 (0.76, 0.92) * 0.93 (0.62, 1.40) 0.26 (0.21, 0.33) * 1.02 (0.91, 1.13)
Odds Ratio (Wald 95%CI) 1.02 (1.01, 1.02) * 0.83 (0.73, 0.95 * 0.85 (0.49, 1.49) 0.25 (0.19, 0.33) * 0.87 (0.75, 1.01)
Reference 0.59 (0.54, 0.64) * 0.85 (0.75, 0.96) * 0.84 (0.77, 0.92) * 0.93 (0.88, 0.98) *
Reference 0.57 (0.48, 0.68) * 0.76 (0.59, 0.98) * 0.87 (0.74, 1.02) 1.00 (0.91, 1.11)
Reference 0.51 (0.44, 0.60) * 0.83 (0.67, 1.04) 0.84 (0.72, 0.99) * 0.78 (0.72, 0.84) *
Reference 0.50 (0.41, 0.62) * 0.73 (0.54, 0.97) * 0.83 (0.67, 1.02) 0.79 (0.72, 0.88) *
Reference 0.51 (0.40, 0.64) * 0.72 (0.51, 1.02) 0.84 (0.65, 1.07) 0.86 (0.76, 0.96) *
Reference 0.44 (0.31, 0.60) * 0.75 (0.49, 1.16 0.64 (0.43, 0.95) * 0.69 (0.60, 0.80 *
1.01 (1.01, 1.02) * 11.72 (11.21, 12.25) * 1.58 (1.45, 1.71) *
1.02 (1.01, 1.03) * 18.53 (16.96, 20.24) * 1.93 (1.60, 2.32) *
1.01 (0.99, 1.01) 8.86 (8.23, 9.53) * 1.29 (1.12, 1.47) *
1.01 (1.01, 1.02) * 9.49 (8.59, 10.48) * 1.40 (1.20, 1.64) *
1.01 (1.00, 1.02) * 9.31 (8.28, 10.46) * 1.39 (1.15, 1.67) *
1.01 (1.00, 1.02) * 9.64 (8.31, 11.17) * 1.56 (1.24, 1.97) *
0.93 (0.88, 0.97) * 1.43 (1.37, 1.49) * 1.40 (1.26, 1.54) * 1.44 (1.26, 1.63) * 0.99 (0.98, 1.01) 1.10 (1.04, 1.16) * 1.27 (1.21, 1.32) * 1.25 (1.20, 1.30) *
0.92 (0.70, 1.21) 1.18 (1.10, 1.26) * 1.56 (1.26, 1.94) * 1.37 (0.93, 2.01) 1.08 (1.05, 1.11) * 0.96 (0.84, 1.09) 1.70 (1.58, 1.81) * 1.28 (1.18, 1.40) *
0.88 (0.82, 0.95) * 1.29 (1.19, 1.40) * 1.21 (1.05, 1.39) * 1.41 (1.18, 1.69) * 1.00 (0.98, 1.03) 1.02 (0.91, 1.13) 1.25 (1.14, 1.36) * 1.29 (1.20, 1.40) *
0.85 (0.77, 0.92) * 1.44 (1.30, 1.60) * 1.11 (0.92, 1.33) 1.30 (1.01, 1.68) * 1.01 (0.98, 1.05) 1.02 (0.86, 1.21) 1.33 (1.18, 1.49) * 1.42 (1.28, 1.58) *
0.78 (0.70, 0.86) * 1.22 (1.06, 1.39) * 1.06 (0.86, 1.30) 1.45 (1.09, 1.95) * 1.03 (0.99, 107) 0.98 (0.79, 1.23) 1.40 (1.21, 1.61) * 1.66 (1.46, 1.88) *
0.78 (0.68, 0.89) * 1.63 (1.36, 1.94) * 1.68 (1.34, 2.11) * 1.24 (0.89, 1.72) 1.03 (0.96, 1.07) 1.16 (0.86, 1.58) 1.28 (1.07, 1.54) * 1.43 (1.21, 1.69) *
1.00 (0.99, 0.99) * 0.76 (0.68, 0.84) * 0.90 (0.93, 0.98) * 0.99 (0.99, 0.99) *
1.00 (0.99, 0.99) * 0.74 (0.63, 0.88) * 0.86 (0.76, 0.98) * 0.99 (0.99, 1.00)
1.00 (0.99, 0.99) * 0.71 (0.65, 0.79) * 0.99 (0.90, 1.08) 0.99 (0.99, 1.00)
1.00 (0.99, 1.00) 0.64 (0.57, 0.72) * 0.96 (0.86, 1.06) 1.00 (0.99, 1.00)
1.00 (0.99, 99) * 0.63 (0.55, 0.71) * 0.95 (0.84, 1.07) 1.00 (0.99, 1.00)
1.00 (0.99, 1.00) 0.60 (0.51, 0.70) * 1.03 (0.89, 1.19) 1.00 (0.99, 1.00)
Age Female Interpreter Staff observed PHQ-9 Married Race/ethnicity: White African American Hispanic Other Moderate/severe cognitive impairment Functional Status PHQ-8: 10+ Moderate/severe aggressive behavior Dementia Psychiatric Delusions Hallucinations Number of diseases Pressure ulcers BH medications Pain NH Covariates Total number of beds For-profit Chain Occupancy rate
20
Aide nursing hours/resident day Total licensed nursing hours/resident day Overall 5-star rating: 1 2-4 5 Urban NH % Medicare residents % Medicaid residents County covariates Market competition (1HHI)
1.111 (1.02, 1.21) *
1.176 (1.02, 1.36) *
1.132 (1.04, 1.23) *
1.178 (1.07, 1.30) *
1.103 (0.99, 1.23)
1.211 (1.06, 1.38) *
1.031 (0.95, 1.12)
1.144 (1.02, 1.28) *
0.994 (0.89, 1.10)
0.998 (0.89, 1.12)
1.026 (0.88, 1.19)
1.063 (0.85, 1.32)
1.074 (0.96, 1.21) Reference 0.947 (0.87, 1.04) 1.017 (0.92, 1.12) 0.988 (0.98, 0.99) * 0.998 (0.99, 1.00)
1.121 (0.92, 1.36) Reference 0.923 (0.80, 1.06) 1.062 (0.91, 1.24) 0.989 (0.98, 0.99) * 0.999 (0.99, 1.00)
1.034 (0.92, 1.17) Reference 0.948 (0.85, 1.06) 0.967 (0.85, 1.09 0.986 (0.98, 0.99) * 0.997 (0.99, 0.99) *
0.978 (0.84, 1.14) Reference 0.925 (0.81, 1.05) 0.941 (0.81, 1.09) 0.983 (0.98, 0.99) * 0.996 (0.99, 0.99) *
0.876 (0.74, 1.04) Reference 0.946 (0.82, 1.09) 1.024 (0.88, 1.20) 0.989 (0.98, 0.99) * 0.995 (0.99, 0.99) *
1.028 (0.83, 1.28) Reference 1.019 (0.86, 1.21) 1.167 (0.96, 1.42) 0.988 (0.98, 0.99) * 0.995 (0.99, 0.99) *
0.701 (0.58, 0.85) *
0.692 (0.51, 0.94) *
0.827 (0.65, 1.05)
0.834 (0.64, 1.08)
0.608 (0.46, 0.80) *
0.623 (0.44, 0.88) *
Notes: Logistic regression models (Wald tests with 80 degrees of freedom) PHQ: Patient Health Questionnaire; BH medications: behavioral health medications; NH: nursing home; HHI: Herfindahl-Hirschman Index *P-value<0.05 a
State dummies are not reported in the table
21
Figure 1
22
Figure 2
23
Figure 3
24
Suicidal Ideation in US Nursing Homes: Association with Individual and Facility Factors Helena Temkin-Greener PhD , Jessica Orth MS, MPH , Yeates Conwell MD , Yue Li PhD PII: DOI: Reference:
S1064-7481(19)30591-3 https://doi.org/10.1016/j.jagp.2019.12.011 AMGP 1391
To appear in:
The American Journal of Geriatric Psychiatry
Received date: Revised date: Accepted date:
7 November 2019 19 December 2019 19 December 2019
Please cite this article as: Helena Temkin-Greener PhD , Jessica Orth MS, MPH , Yeates Conwell MD , Yue Li PhD , Suicidal Ideation in US Nursing Homes: Association with Individual and Facility Factors, The American Journal of Geriatric Psychiatry (2020), doi: https://doi.org/10.1016/j.jagp.2019.12.011
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.
Suicidal Ideation in US Nursing Homes: Association with Individual and Facility Factors
Helena Temkin-Greener, PhD,1Jessica Orth, MS, MPH1, Yeates Conwell, MD2, Yue Li, PhD1,
1
Department of Public Health Sciences, University of Rochester School of Medicine and
Dentistry, Rochester, NY 2
Department of Psychiatry, University of Rochester School of Medicine and Dentistry,
Rochester, NY
Corresponding Author: Helena Temkin-Greener, PhD
Public Health Sciences 265 Crittenden Blvd. Rochester, NY 14642 Phone: 585-275-8713 Email: [email protected]
Key words: suicidal ideation, nursing homes, risk-factors
This study was supported by funding from the National Institute of Mental Health, grant 1RF1MH117528-01 Conflicts of Interest: none
1
Highlights 1. What is the frequency and timing of suicidal ideation (SI) in US nursing homes, and what is the association of SI with individual and facility level factors? 2. SI is highest at admission and declines with the duration of a nursing home stay. Several potentially modifiable individual and facility-level factors are associated with SI risk throughout the stay. 3. The frequency of SI in nursing homes may be under-reported, and the PHQ-9 item used to assess SI may not be well understood.
ABSTRACT Objectives: To assess prevalence of suicidal ideation (SI) among new post-acute and long-stay nursing home (NH) admissions and examine the associations with individual and NH-level factors. Setting/Participants: 1,864,102 post-acute and 304,106 long-stay admissions to just over 15,000 NHs between 7/1/2014 and 6/30/2015. Measurement: Using 100% of the national Minimum Data Set 3.0 we identified SI and key covariates. SI was based on responses to one item on the PHQ-9 scale. For post-acute residents SI was measured at admission and discharge. For long-stay residents, SI was assessed at admission and assessments closest to 90, 180, and 365 days thereafter. Patient socio-demographics, functional and cognitive status, co-morbid conditions and other covariates were included as independent variables, as were several NH-level factors. Logistic regression models were fit to estimate SI risk at admission and at subsequent time intervals. Results: Observed 2-week prevalence rates of SI were highest at admission (1.24% for postacute and 1.84% for long-stays) and declined thereafter at each subsequent time interval. The odds of SI were significantly increased for residents with severe depression at admission and all subsequent intervals. Residents in for-profits had significantly lower rates of SI, compared with those in not-for-profits. Conclusions: Our findings demonstrate that SI risk in NHs is highest at admission and subsequently declines. We found several potentially modifiable individual-level risk factors for SI. The identification of SI may be seriously underreported in for-profit-facilities. Future research may be needed to explore how the PHQ-9 item on SI is understood by residents and recorded by staff. Key words: suicidal ideation, nursing homes, risk-factors
2
INTRODUCTION Death by suicide and suicidal ideation (SI) among older adults, including those in nursing homes (NHs), are of growing concern both in the US and abroad. 1–6 NH placement has long been known to be one of the most distressing healthcare transitions faced by older adults, often associated with an increase in depression and a possible precipitant of suicide.7 Every year over 1.6 million Medicare beneficiaries in the US are admitted to Skilled Nursing Facilities (SNF) and while most expect to be discharged back to the community, only 40% ever are. 8 Studies of completed suicide in NHs are relatively few, many are at least 2 decades old, and their findings are highly variable. While some have reported that suicide rates in NHs are substantially lower than in the community,9 others have shown the incidence of suicide among older adults to be comparable in NHs and in the community.10 Still others have suggested that suicides in this care setting remain considerably under recognized and underreported.11 A recent systematic review of the literature from 1990 through 2015 identified only 5 studies of suicides in US NHs, most based on small, convenience samples and differing methodologies.3 One national-level study using data from the National Violent Death Reporting System has shown that between 2003 and 2015, about 2.2% of suicides among adults age 55 and over were associated with transitions to or from NHs. 12 At the same time, prevalence of suicidal ideation (SI), a risk factor for suicidal behavior, has been reported as being substantially higher in NHs than in the general population.13 A recent systematic review, which identified only a handful of studies from the US and elsewhere, reported SI within the past month as ranging from 5% to 33% of NH residents.2 Prevalence of SI was reported to be the highest within the first seven months of entering a NH,14 and some have suggested this may reflect on the severity of distress associated with moving from one’s home in the community to a NH.7 As with completed suicides, these studies also relied on small, convenience samples and many are over 2 decades old. Prior to 2011, SI assessments in NHs were rarely conducted. With the implementation of the Minimum Data Set (MDS) 3.0 in late
3
2010, all US NHs (certified by Medicare and Medicaid) are required to routinely administer the Patient Health Questionnaire (PHQ-9) to all residents,15 which among others includes a question on presence of self-harm thoughts. The availability and the uniformity of data resulting from the MDS assessments provide an opportunity to examine SI in US NHs in detail. We used calendar year (CY)2014-2016 MDS 3.0 data to address two objectives. First, we measured the prevalence of SI at NH entry and at several intervals thereafter to identify periods of greatest risk. Second, we examined associations between SI and individual as well as NH-level characteristics to identify potential correlates that may be important in the early identification and management of suicide risk in NHs.
METHODS Data Sources and Sample Data came from several sources. We used 100% of the national Minimum Data Set (MDS 3.0) for CY2014-2016. The MDS data are available for all patients admitted to Medicaid and/or Medicare certified NHs in the US or approximately 15,600 facilities. These NHs are required to conduct and report detailed resident assessments at admission and thereafter quarterly, annually or when a significant change in health status occurs. Validity and reliability of the MDS assessments, and of the PHQ-9 items, have been documented in prior literature. 15–18 Item 9 on the PHQ-9 has been considered to be a predictor of SI with several studies demonstrating increased risk of suicide attempts or deaths among community outpatients and among users of services provided by the Veterans Health Administration, who responded affirmatively to this item.19,20 The MDS contains information on resident’s socio-demographics, functional and cognitive status, and diagnostics and therapeutics. Other sources of data are identified below. The study sample consisted of Medicare beneficiaries newly admitted to a US NHs between 7/1/2014 and 6/30/2015, with no NH stay in the prior 180 days (1/1/2014-6/30/2014). The follow-up period for any admissions during the study window was up to 395 days (7/1/2015-
4
7/29/2016) in order to capture the MDS assessments performed closest to one year after admission. We created a new resident ID and nested episodes within resident, so a resident may appear more than once if they had multiple admissions during the year-window. Residents were further identified as post-acute (short-stay) and long-stay (custodial), based on the algorithm developed for CMS by RTI International.21 Residents who were comatose and those for whom the PHQ-9 SI items were missing were excluded (1.15% of sample). Our final analytical sample included 1,864,102 post-acute and 304,106 long-stay admissions to just over 15,000 NHs in a period of one year. The study protocol was reviewed and approved by the institutional review board of the University of Rochester School of Medicine and Dentistry.
Outcome Measure SI was measured by presence (1) or absence (0) of symptom on item 9 of the PHQ-9 scale, which queries if a resident “over the last 2 weeks, [has] been bothered by …thoughts that you would be better off dead, or hurting yourself in some way.” Presence or absence of SI was assessed by a patient self-report (D0200I) or was staff-reported (D0500I) if a resident was known to be “rarely/never understood”. Because SI may be more frequent at points of transition, we measured SI for post-acute residents at admission and discharge, and for long-stay residents at admission and at assessments closest to 90, 180, and 365 days after NH admission.
Independent Variables Both individual- and NH-level independent variables were included following a literature review and consultations with clinicians. These included residents’ socio-demographics such as age, gender, marital status, and race/ethnicity. Clinical and diagnostic covariates, based on the assessments closest to the time periods examined, included: functional status (level of
5
impairments in activities of daily living, scale from 0 to 28); cognitive status (scale of 0-3 categorized as none/mild [0, 1] versus moderate/severe [2, 3] impairment);22 aggressive behavior (scale of 0-12 categorized as none/mild [0-2] versus moderate/severe [3-12]);23 depressive symptoms (defined as a score of 10 or higher on the PHQ-8 – self or staff reported);17,24 and a set of binary variables indicating presence/absence (1/0) of specific comorbid conditions (dementia, psychiatric disorders, delusions, hallucinations). We also included a count variable for the presence of other comorbidities (cancer, heart conditions, gastrointestinal, genitourinary, infections, metabolic, musculoskeletal, neurologic, nutritional, pulmonary, and vision impairment). Presence of pain negatively affecting sleep or activities was coded as a binary (1/0) variable, as was presence of pressure ulcers (stage 2 or higher). We also accounted for the use (binary 1/0) of behavioral health medications such as antipsychotic, antianxiety, antidepressant or hypnotic. Finally, we also included binary indicators as to whether a resident needed an interpreter to communicate with caregivers, and whether presence or absence of PHQ-9 symptoms was self- or staff-reported.
We also defined several NH-level variables, which have been hypothesized to be associated with depression and risk of suicide in long-term care, although empirical evidence on these associations has been very scant.4,10,25 These covariates were: bed-size; profit status (for profit or non-profit), chain membership, occupancy rate, % of Medicare and % of Medicaid residents, number of certified nurse aide (CNA) hours per resident per day; total number of licensed nursing hours per resident per day, overall facility 5-star rating, and facility rural versus urban location. Data on facility characteristics and on star ratings were obtained from 2015 CMS Nursing Home Compare (NHC) web site, the Area Health Resources File, and Brown University’s LTCfocus. A county-level variable measuring NH market bed competition was also included.
6
Statistical Analyses
We first performed bivariate analyses to examine the observed rates of SI for post-acute and long-stay NH residents at admission and at specified assessment times following admission. For each group of residents, we examined both time invariant (e.g. sociodemographics) and time-varying (e.g. cognitive impairment, functional status, depressive symptoms) characteristics, as well as facility-level factors. We fit separate logistic regression models to estimate the risk of SI at post-acute admission and discharge, and at long-stay admission and assessments occurring at 90, 180, and 365 days after NH admission. All models included Huber-White robust standard error estimates clustering at the NH level. State dummies were included in all models to control for state-level variations that may influence the prevalence of SI and its reporting in the MDS. Predicted SI rates were calculated based on coefficient estimation for all covariates. We conducted sensitivity analyses to assess the impact of residents’ death. We compared the analyses in which residents who died during the follow-up periods were excluded to the analyses based on the total sample. Findings from these analyses were not measurably different and therefore we presented only the results based on the entire sample.
Analyses were performed using SAS version 9.4 (SAS Institute, Inc. Cary, NC).
RESULTS Among short-stay NH residents, the observed SI rate was 1.24% at admission declining to 0.50% at discharge; while among long-stay NH residents, the observed SI rate was 1.81% at admission, 1.21% at 90 days, 1.19% at 180 days, and 0.98% at 365 days after admission. The predicted rates remained largely unchanged (Figure 1).
7
Table 1 shows that at NH admission, residents with SI were slightly older, more likely to be male, unmarried, and non-Hispanic White. They were less likely to need interpreter services and less likely to have staff-observed PHQ-9 symptoms. Residents with SI had a lower prevalence of moderate/severe cognitive impairment but higher prevalence of depressive symptoms and moderate/severe aggressive behavior compared to residents without SI. Regarding diagnostic characteristics, residents with SI had higher prevalence of psychiatric conditions, delusions, hallucinations, more comorbidities, higher frequency of pressure ulcers, higher use of BH medications, and more pain compared to those without SI. Residents with SI were more likely to reside in smaller, non-profit, and rural NHs in less competitive NH markets compared to residents without SI. There were no statistically significant differences between residents with and without SI regarding functional status, prevalence of dementia, and the 5-star NH quality. The differences between residents with and without SI were similar at discharge or during other follow-up periods, and thus are not shown for ease of presentation. Our multivariate analyses largely confirmed these unadjusted differences in SI (Table 2). After controlling for residents’ socio-demographics, health status, clinical conditions, as well as NH, market, and state covariates, the predicted probabilities of SI remained largely unchanged and showed similar downward trends (to observed rates) as residents were discharged (shortstay) or continued as long-stay residents. Compared to Whites, African-Americans had more than 40% lower odds of SI for both post-acute and for long-stay residents at admission, and declining thereafter. Odds ratios were also lower at admission for residents who were Hispanic, but over time, the decline was not as precipitous or statistically significant for long-stay residents in this population subgroup. For post-acute residents, presence of depressive symptoms (PHQ8=>10) increased the odds of SI at admission more than ten-fold and even more so at discharge. Depressive symptoms were also significantly associated with SI for long-stay residents at admission, and increasing more than 9-fold at 90, 180, and 365 days following.
8
For post-acute and long-stay residents, respectively, we found 57% and 29% higher odds of moderate/severe aggressive behavior on admission, with increasing risk at subsequent assessments; as well as 25% and 29% higher odds of pain; 27% and 25% higher odds of behavioral health medication use; and 43% and 29% higher odds of psychiatric diagnoses. The odds of SI were 7.5% lower for residents with dementia and 11.6% lower for residents with moderate/severe cognitive impairment at admission, and at all subsequent assessments. Facility structural characteristics such as bed size, chain membership or occupancy rates were not consistently or significantly associated with SI. However, post-acute residents in for-profit facilities had 24.0% lower odds of SI at admission and 25.8% lower odds at discharge compared to residents in not-for-profits; for long-stay residents at admission, 90, 180, and 365 days from NH admission the odds were of SI were 28.6%, 36.2%, and 40.3% lower, respectively. Furthermore, residents in NHs with higher CNA staffing experienced higher odds of SI for post-acute and long-stay residents alike, at admission and at subsequent assessments. The association with licensed nursing hours/resident day for the most part was not statistically significant. Similarly, we found no significant association of SI with other facility characteristics such as 5-star rating or rural-urban location. The effect size of the association with % Medicare and % Medicaid residents, while statistically significant, was very small and thus clinically not meaningful. In highly competitive NH markets, the odds of SI were lower for post-acute residents at admission and at discharge, but were not consistently significant for long stay residents. After controlling for individual, facility, and market level factors there were significant variations in the predicted probability of SI across states. Figure 2 depicts these predicted probabilities for both post-acute and long-stay admissions. Residents in NHs located in the north and mid-west parts of the country, as well as those in Maine, Vermont, and New
9
Hampshire, had consistently higher rates of SI compared to residents in facilities located in the southern and east coast states.
DISCUSSION To our knowledge, this is a first study of SI in US NHs based on recent national-level assessments provided through the Minimum Data Set 3.0. Our findings suggest that the MDSbased coding of SI among NH residents is less frequent than previously reported. We found that around the point of NH admission, the average rate of SI (in the past two weeks) was below 2% for post-acute and for long-stay residents. Consistent with prior studies4,14 we found SI to be higher at admission than at subsequent assessment periods. For post-acute residents, SI declined precipitously, by almost 60%, between admission and discharge, while for long-stay residents a significant decline occurred within 3 months of admission with a further decrease by the end one year of stay. These findings suggest that NH placement may itself be a significant risk for SI. While the risk of SI may attenuate over time, certain individual-level covariates appear to exacerbate that risk. Not unexpectedly, we found presence of moderate-to-severe depressive symptoms to sizably increase that risk throughout the NH stay. Consistent with prior studies, several other factors were positively associated with SI, for example aggressive behavior, psychiatric conditions, presence of pain that interferes with sleep or activities, and the use of such common medications as antidepressants, antianxiety, antipsychotics, and hypnotics. Our findings further showed that the effect size of these factors vis a vis SI increased with the duration of the NH stay. Also consistent with the literature, we found that residents with dementia and/or cognitive impairment had lower odds of SI, 26 although we were unable to determine if this is due to some “protective” factor or is a function of the inability to respond or have this item accurately recorded.
10
With regard to organizational-level factors that may be associated with SI, our study was able to shed some light on what has been a significant gap in the literature. 2 We identified two NH-level covariates that were consistently associated with SI. A one hour (per resident/day) increase in CNA staffing increased the odds of SI by 10%-to-20%, depending on the assessment period. While somewhat counter-intuitive, this finding may suggest that identification of residents with severe depression, often associated with SI, may be better in facilities with more CNAs. Prior research has suggested that CNAs who are in close daily contact with the residents were best positioned to recognize changes in residents’ mood and behavior,27 and thus may be able to call attention to those most vulnerable for suicidal risk. We also found that residents in for-profit homes had consistently and very significantly lower risk-adjusted odds of SI, at admission and at subsequent assessment intervals, compared to residents in not-for-profits. For-profit status of NHs has been found to be associated with worse quality of care,28 and poorer resident outcomes,29 thus making this finding a bit counterintuitive if lower SI rate is believed to indicate better quality of care. However, for-profits have also been shown to have lower staffing levels and higher staff burdens.30 When staff are overburdened and may not be very adept in the administration of psychometric assessments it is possible that the presence of SI, not a common occurrence, is overlooked. Thus, underreporting of SI in for-profit NHs appears to be the most likely explanation for this finding. The inclusion of the item on self-harm and suicidal thoughts on the PHQ-9 of the MDS 3.0 assessment forms implies that NHs have in place processes and systems to appropriately treat or refer residents identified as being at risk for suicide. However, a recent national survey has reported that more than 25% of NHs have difficulty in assessing residents for emotional problems, 45% are unable to provide behavioral health crisis interventions, and a third cannot adequately coordinate with community providers for services they lack within. Furthermore, these shortcoming in services appear to be exacerbated by lack of psychiatrically trained nurses and high turnover among the CNAs. 31 Thus, although identifying residents at high risk for
11
suicide may be critical to effective prevention and appropriate treatment, it remains somewhat uncertain if most NHs in the US have the resources and expertise needed to adequately care for such residents. The issue of accurately screening for suicidal/death ideation may be further confounded by the way the single item on SI is phrased, requiring a yes or no response to having had “thoughts that you would be better off dead, or hurting yourself in some way”. 32 The wording of this item combines two constructs, each of which has an ambiguous relationship to suicidal thoughts. Some have suggested that death ideation (be better off dead) is a normal part of approaching end-of-life and does not necessarily signify active planning or intent to end one’s life.32 The second part of this PHQ-9 item (hurting yourself in some way) does not distinguish injury with the intent to die from non-suicidal self-injury. However, prior studies have suggested that even death ideation, not just active suicidal thoughts, is likely associated with higher risk for suicide.19,20,33 Hence, a positive answer to this item should mark the need for further assessment. Several limitations should be noted. First, the data are largely cross sectional and our findings should not be interpreted as causal, only as associations. Second, while the analyses adjust for numerous individual and facility level factors, it is possible that unmeasured variables may confound our findings. Finally, although previous validation studies demonstrated relatively high validity of the MDS-3 items it is possible that SI was under-reported and under-identified in many NHs, especially, as we suggested, in for-profit NHs. Despite this potential limitation, our analyses confirmed important correlates for SI such as mood and psychiatric disorders, and identified important patterns of changes in reported rates at different points of NH care. Despite the growing awareness and the recent focus on suicides in NHs in the popular press,34,35 understanding of suicide risk and the identification of associated factors remain relatively meager. This study is the first to use the national MDS 3.0 assessments, which all Medicare and Medicaid certified NHs are required to complete for their residents, to identify and
12
characterize SI. Our findings demonstrate that SI in NH is highest at admission, likely reflecting the stress of transitioning from home, and declines with the duration of stay. We identified several modifiable individual-level risk factors, largely consistent with prior literature. Our findings also suggest that identification of residents who are at risk of SI may be seriously underreported in for-profit facilities. Future research should explore how the item on SI in PHQ-9 is both understood by residents and recorded by staff.
13
ACKNOWLEDGMENTS This study was supported by funding from the National Institute of Mental Health, grant 1RF1MH117528-01
Conflicts of Interest: none
14
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Figure legends Figure 1: Observed and Predicted Suicide Ideation Risk at Admission and During the NH Stay: Post-Acute and Long-Stay Residents Figure 2A: Post-Acute Admissions: Predicted Nursing Home SI Rated by State Lowest Rate: 0.40 (FL) Highest Rate: 4.12 (ND)
Figure 2B: Long-Stay Admissions: Predicted Nursing Home SI Rates by State Lowest Rate: 0.43 (NM) Highest Rate: 4.61 (SD)
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Table 1: Descriptive Characteristics of Newly Admitted Post-Acute and Long-Stay Nursing Home Residents by Presence of Suicidal Ideation. Suicidal Ideation N: 28,548 1.24 1.81
No Suicidal Ideation N: 2,139,660 98.76 98.19
p-value (
or t-test)
Post-acute admission <0.001 Long-stay admission Resident Covariates Age <0.001 78.39 13.50 76.92 12.82 Female 59.01% 60.99% <0.001 Interpreter 1.43% 3.05% <0.001 Staff observed PHQ-9 4.81% 8.23% <0.001 Married 30.72% 33.08% <0.001 Race: <0.001 0: White 88.01% 78.36% 1: African American 4.42% 10.76% 2: Hispanic 2.33% 4.48% 3: Other 5.25% 6.39% Moderate/severe 17.85% 18.51% 0.001 cognitive impairment Functional status 0.848 17.02 4.73 17.01 4.70 PHQ-8: 10+ 41.36% 5.16% <0.001 Moderate/severe 5.11% 2.23% <0.001 aggressive behavior Dementia 20.85% 20.65% 0.409 Psychiatric 56.99% 40.87% <0.001 Delusions 4.40% 1.81% <0.001 Hallucinations 2.81% 0.97% <0.001 Number of diseases <0.001 3.60 1.54 3.45 1.49 Pressure ulcers 8.44% 7.97% 0.003 BH medications 65.99% 50.67% <0.001 Pain 31.41% 21.46% <0.001 NH Covariates Total number of beds <0.001 123.62 73.28 132.54 76.57 For-profit 60.19% 72.27% <0.001 Chain 56.04% 58.90% <0.001 Occupancy rate <0.001 83.22 17.78 83.93 16.02 Aide nursing <0.001 2.55 0.65 2.48 0.56 hours/resident day Total licensed nursing <0.001 1.77 0.67 1.81 0.68 hours/resident day Overall 5-star rating: 0.077 1 12.64% 12.38% 2-4 62.33% 62.15% 5 24.45% 25.01% Urban NH 74.67% 82.02% <0.001 % Medicare residents <0.001 17.83 16.11 21.21 17.29 % Medicaid residents <0.001 52.63 23.20 51.75 23.70 County covariates Market competition (1<0.001 0.82 0.22 0.86 0.19 HHI) Notes. PHQ: Patient Health Questionnaire; BH medications: behavioral health medications; NH: nursing home; HHI: Herfindahl-Hirschman Index
19
Table 2: Predicted Probability of Suicidal Ideation for Post-Acute and Long-Stay Nursing Home Residents: By Assessment Perioda Post-Acute: Admission N=1,642,394
Post-Acute: Discharge N=1,064,416
Long-stay: Admission N=267,721
Long-Stay: Admission+90 N=234,768
Long-stay: Admission+180 N=174,382
Long-stay: Admission+365 N=128,719
Suicide ideation Observed rate (per 100)
1.24%
0.50%
1.81%
1.21%
1.19%
0.98%
Average predicted probability rate (per 100) Resident Covariates
1.24%
0.51%
1.84%
1.24%
1.22%
0.99%
Odds Ratio (Wald 95%CI) 1.02 (1.01, 1.02) * 0.77 (0.74, 0.79) * 0.83 (0.68, 1.01) 0.40 (0.37, 0.44) * 0.83 (0.81, 0.86) *
Odds Ratio (Wald 95%CI) 1.02 (1.02, 1.03) * 0.72 (0.68, 0.77) * 0.93 (0.63, 1.39) 0.61 (0.49, 0.74) * 0.79 (0.74, 0.84) *
Odds Ratio (Wald 95%CI) 1.01 (1.01, 1.02) * 0.83 (0.77, 0.88) * 0.75 (0.57, 0.97) * 0.35 (0.30, 0.41) * 0.94 (0.88, 1.01)
Odds Ratio (Wald 95%CI) 1.01 (1.01, 1.02) * 0.86 (0.79, 0.94) * 0.85 (0.59, 1.22) 0.30 (0.25, 0.36) * 1.01 (0.92, 1.11)
Odds Ratio (Wald 95%CI) 1.01 (1.01, 1.02) * 0.84 (0.76, 0.92) * 0.93 (0.62, 1.40) 0.26 (0.21, 0.33) * 1.02 (0.91, 1.13)
Odds Ratio (Wald 95%CI) 1.02 (1.01, 1.02) * 0.83 (0.73, 0.95 * 0.85 (0.49, 1.49) 0.25 (0.19, 0.33) * 0.87 (0.75, 1.01)
Reference 0.59 (0.54, 0.64) * 0.85 (0.75, 0.96) * 0.84 (0.77, 0.92) * 0.93 (0.88, 0.98) *
Reference 0.57 (0.48, 0.68) * 0.76 (0.59, 0.98) * 0.87 (0.74, 1.02) 1.00 (0.91, 1.11)
Reference 0.51 (0.44, 0.60) * 0.83 (0.67, 1.04) 0.84 (0.72, 0.99) * 0.78 (0.72, 0.84) *
Reference 0.50 (0.41, 0.62) * 0.73 (0.54, 0.97) * 0.83 (0.67, 1.02) 0.79 (0.72, 0.88) *
Reference 0.51 (0.40, 0.64) * 0.72 (0.51, 1.02) 0.84 (0.65, 1.07) 0.86 (0.76, 0.96) *
Reference 0.44 (0.31, 0.60) * 0.75 (0.49, 1.16 0.64 (0.43, 0.95) * 0.69 (0.60, 0.80 *
1.01 (1.01, 1.02) * 11.72 (11.21, 12.25) * 1.58 (1.45, 1.71) *
1.02 (1.01, 1.03) * 18.53 (16.96, 20.24) * 1.93 (1.60, 2.32) *
1.01 (0.99, 1.01) 8.86 (8.23, 9.53) * 1.29 (1.12, 1.47) *
1.01 (1.01, 1.02) * 9.49 (8.59, 10.48) * 1.40 (1.20, 1.64) *
1.01 (1.00, 1.02) * 9.31 (8.28, 10.46) * 1.39 (1.15, 1.67) *
1.01 (1.00, 1.02) * 9.64 (8.31, 11.17) * 1.56 (1.24, 1.97) *
0.93 (0.88, 0.97) * 1.43 (1.37, 1.49) * 1.40 (1.26, 1.54) * 1.44 (1.26, 1.63) * 0.99 (0.98, 1.01) 1.10 (1.04, 1.16) * 1.27 (1.21, 1.32) * 1.25 (1.20, 1.30) *
0.92 (0.70, 1.21) 1.18 (1.10, 1.26) * 1.56 (1.26, 1.94) * 1.37 (0.93, 2.01) 1.08 (1.05, 1.11) * 0.96 (0.84, 1.09) 1.70 (1.58, 1.81) * 1.28 (1.18, 1.40) *
0.88 (0.82, 0.95) * 1.29 (1.19, 1.40) * 1.21 (1.05, 1.39) * 1.41 (1.18, 1.69) * 1.00 (0.98, 1.03) 1.02 (0.91, 1.13) 1.25 (1.14, 1.36) * 1.29 (1.20, 1.40) *
0.85 (0.77, 0.92) * 1.44 (1.30, 1.60) * 1.11 (0.92, 1.33) 1.30 (1.01, 1.68) * 1.01 (0.98, 1.05) 1.02 (0.86, 1.21) 1.33 (1.18, 1.49) * 1.42 (1.28, 1.58) *
0.78 (0.70, 0.86) * 1.22 (1.06, 1.39) * 1.06 (0.86, 1.30) 1.45 (1.09, 1.95) * 1.03 (0.99, 107) 0.98 (0.79, 1.23) 1.40 (1.21, 1.61) * 1.66 (1.46, 1.88) *
0.78 (0.68, 0.89) * 1.63 (1.36, 1.94) * 1.68 (1.34, 2.11) * 1.24 (0.89, 1.72) 1.03 (0.96, 1.07) 1.16 (0.86, 1.58) 1.28 (1.07, 1.54) * 1.43 (1.21, 1.69) *
1.00 (0.99, 0.99) * 0.76 (0.68, 0.84) * 0.90 (0.93, 0.98) * 0.99 (0.99, 0.99) *
1.00 (0.99, 0.99) * 0.74 (0.63, 0.88) * 0.86 (0.76, 0.98) * 0.99 (0.99, 1.00)
1.00 (0.99, 0.99) * 0.71 (0.65, 0.79) * 0.99 (0.90, 1.08) 0.99 (0.99, 1.00)
1.00 (0.99, 1.00) 0.64 (0.57, 0.72) * 0.96 (0.86, 1.06) 1.00 (0.99, 1.00)
1.00 (0.99, 99) * 0.63 (0.55, 0.71) * 0.95 (0.84, 1.07) 1.00 (0.99, 1.00)
1.00 (0.99, 1.00) 0.60 (0.51, 0.70) * 1.03 (0.89, 1.19) 1.00 (0.99, 1.00)
Age Female Interpreter Staff observed PHQ-9 Married Race/ethnicity: White African American Hispanic Other Moderate/severe cognitive impairment Functional Status PHQ-8: 10+ Moderate/severe aggressive behavior Dementia Psychiatric Delusions Hallucinations Number of diseases Pressure ulcers BH medications Pain NH Covariates Total number of beds For-profit Chain Occupancy rate
20
Aide nursing hours/resident day Total licensed nursing hours/resident day Overall 5-star rating: 1 2-4 5 Urban NH % Medicare residents % Medicaid residents County covariates Market competition (1HHI)
1.111 (1.02, 1.21) *
1.176 (1.02, 1.36) *
1.132 (1.04, 1.23) *
1.178 (1.07, 1.30) *
1.103 (0.99, 1.23)
1.211 (1.06, 1.38) *
1.031 (0.95, 1.12)
1.144 (1.02, 1.28) *
0.994 (0.89, 1.10)
0.998 (0.89, 1.12)
1.026 (0.88, 1.19)
1.063 (0.85, 1.32)
1.074 (0.96, 1.21) Reference 0.947 (0.87, 1.04) 1.017 (0.92, 1.12) 0.988 (0.98, 0.99) * 0.998 (0.99, 1.00)
1.121 (0.92, 1.36) Reference 0.923 (0.80, 1.06) 1.062 (0.91, 1.24) 0.989 (0.98, 0.99) * 0.999 (0.99, 1.00)
1.034 (0.92, 1.17) Reference 0.948 (0.85, 1.06) 0.967 (0.85, 1.09 0.986 (0.98, 0.99) * 0.997 (0.99, 0.99) *
0.978 (0.84, 1.14) Reference 0.925 (0.81, 1.05) 0.941 (0.81, 1.09) 0.983 (0.98, 0.99) * 0.996 (0.99, 0.99) *
0.876 (0.74, 1.04) Reference 0.946 (0.82, 1.09) 1.024 (0.88, 1.20) 0.989 (0.98, 0.99) * 0.995 (0.99, 0.99) *
1.028 (0.83, 1.28) Reference 1.019 (0.86, 1.21) 1.167 (0.96, 1.42) 0.988 (0.98, 0.99) * 0.995 (0.99, 0.99) *
0.701 (0.58, 0.85) *
0.692 (0.51, 0.94) *
0.827 (0.65, 1.05)
0.834 (0.64, 1.08)
0.608 (0.46, 0.80) *
0.623 (0.44, 0.88) *
Notes: Logistic regression models (Wald tests with 80 degrees of freedom) PHQ: Patient Health Questionnaire; BH medications: behavioral health medications; NH: nursing home; HHI: Herfindahl-Hirschman Index *P-value<0.05 a
State dummies are not reported in the table
21
Figure 1
22
Figure 2
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Figure 3
24