Associations of Mortality Outcomes With Employment Status at Discharge From VA Vocational Rehabilitation Service Programs.

OBJECTIVE: The authors evaluated associations between employment at discharge from Veterans Health Administration Vocational Rehabilitation Service (VR) programs and suicide and other causes of death. METHODS: For veterans receiving VR between October 1, 2005, and September 30, 2014 (N=78,293), proportional hazards analyses were used to test associations of employment with suicide, drug overdose, and external and natural cause mortality rates over 1 and 5 years postdischarge and through December 31, 2019. The analyses were adjusted for clinical and sociodemographic characteristics and propensity for employment. RESULTS: Of the veterans, 94.1% had a psychiatric diagnosis, and 35.5% were employed at VR discharge. In proportional hazards analyses, employment was associated with lower mortality rates through 1 year (suicide, hazard ratio [HR]=0.54; overdose, HR=0.70; external causes, HR=0.62; and natural causes, HR=0.51) and 5 years postdischarge (overdose, HR=0.72; external causes, HR=0.81; and natural causes, HR=0.72). Through December 31, 2019, employment was associated with lower risks for overdose (HR=0.80) and death by external (HR=0.81) and natural (HR=0.80) causes. CONCLUSIONS: Employment at VR discharge was associated with lower mortality risk among veterans with psychiatric diagnoses.

Midlife diseases of despair and cardiometabolic risk: testing shared origins in adolescent psychopathology.

BACKGROUND: Rising midlife mortality in the United States is largely attributable to 'deaths of despair' (deaths from suicide, drug poisonings, and alcohol-related diseases) and deaths from cardiometabolic conditions. Although despair- and cardiometabolic-related mortality are increasing concurrently, it is unclear whether they share common developmental origins. We tested adolescent psychopathology as a potential common origin of midlife diseases of despair and cardiometabolic risk. METHODS: Participants (N = 4578) were from the National Longitudinal Study of Adolescent to Adult Health, a nationally representative cohort followed from adolescence to early midlife. Adolescent psychopathology included depression, anxiety, eating disorders, PTSD, conduct disorder, and ADHD at ages 11-18. Diseases of despair (suicidality, substance misuse, pain, and sleep problems) and cardiometabolic risk (hypertension, hyperlipidemia, high-risk waist circumference, diabetes, and cardiovascular conditions) were multi-modally measured at ages 33-43. RESULTS: At midlife, adolescents who experienced psychopathology exhibited more indicators of despair-related diseases and cardiometabolic risk (IRRs = 1.67 [1.46-1.87] and 1.13 [1.04-1.21], respectively), even after accounting for demographics, adolescent SES, and adolescent cognitive ability. Associations were evident for internalizing and externalizing conditions, and in a dose-response fashion. In mediation analyses, low education explained little of these associations, but early-adult substance use explained 21.5% of psychopathology's association with despair-related diseases. Midlife despair-related diseases and cardiometabolic risk co-occurred within individuals (IRR = 1.12 [1.08-1.16]). Adolescent psychopathology accounted for 8.3% of this co-occurrence, and 16.7% together with adolescent SES and cognitive ability. CONCLUSIONS: Adolescent psychopathology precedes both diseases of despair and cardiometabolic risk. Prevention and treatment of psychopathology may mitigate multiple causes of poor midlife health, reducing premature mortality.

Leveraging Natural Language Processing to Improve Electronic Health Record Suicide Risk Prediction for Veterans Health Administration Users.

Background: Suicide risk prediction models frequently rely on structured electronic health record (EHR) data, including patient demographics and health care usage variables. Unstructured EHR data, such as clinical notes, may improve predictive accuracy by allowing access to detailed information that does not exist in structured data fields. To assess comparative benefits of including unstructured data, we developed a large case-control dataset matched on a state-of-the-art structured EHR suicide risk algorithm, utilized natural language processing (NLP) to derive a clinical note predictive model, and evaluated to what extent this model provided predictive accuracy over and above existing predictive thresholds.Methods: We developed a matched case-control sample of Veterans Health Administration (VHA) patients in 2017 and 2018. Each case (all patients that died by suicide in that interval, n = 4,584) was matched with 5 controls (patients who remained alive during treatment year) who shared the same suicide risk percentile. All sample EHR notes were selected and abstracted using NLP methods. We applied machine-learning classification algorithms to NLP output to develop predictive models. We calculated area under the curve (AUC) and suicide risk concentration to evaluate predictive accuracy overall and for high-risk patients.Results: The best performing NLP-derived models provided 19% overall additional predictive accuracy (AUC = 0.69; 95% CI, 0.67, 0.72) and 6-fold additional risk concentration for patients at the highest risk tier (top 0.1%), relative to the structured EHR model.Conclusions: The NLP-supplemented predictive models provided considerable benefit when compared to conventional structured EHR models. Results support future structured and unstructured EHR risk model integrations.

Common infectious morbidity and white blood cell count in middle childhood predict behavior problems in adolescence.

We examined the associations of middle childhood infectious morbidity and inflammatory biomarkers with adolescent internalizing and externalizing behavior problems. We recruited 1018 Colombian schoolchildren aged 5-12 years into a cohort. We quantified white blood cell (WBC) counts and C-reactive protein at enrollment and prospectively recorded incidence of gastrointestinal, respiratory, and fever-associated morbidity during the first follow-up year. After a median 6 years, we assessed adolescent internalizing and externalizing behavior problems using child behavior checklist (CBCL) and youth self-report (YSR) questionnaires. Behavior problem scores were compared over biomarker and morbidity categories using mean differences and 95% confidence intervals (CI) from multivariable linear regression. Compared with children without symptoms, CBCL internalizing problem scores were an adjusted 2.5 (95% CI: 0.1, 4.9; p = .04) and 3.1 (95% CI: 1.1, 5.2; p = .003) units higher among children with moderate diarrhea with vomiting and high cough with fever rates, respectively. High cough with fever and high fever rates were associated with increased CBCL somatic complaints and anxious/depressed scores, respectively. WBC >10,000/mm3 was associated with both internalizing problem and YSR withdrawn/depressed scores. There were no associations with externalizing behavior problems. Whether or not decreasing the burden of common infections results in improved neurobehavioral outcomes warrants further investigation.

Suicide risk following a new cancer diagnosis among Veterans in Veterans Health Administration care.

BACKGROUND: Cancer diagnoses are associated with an increased risk for suicide. The aim of this study was to evaluate this association among Veterans receiving Veterans Health Administration (VHA) care, a population that has an especially high suicide risk. METHODS: Among 4,926,373 Veterans with VHA use in 2011 and in 2012 or 2013, and without VHA cancer diagnoses in 2011, we assessed suicide risk following incident cancer diagnoses. Risk time was from initial VHA use in 2012-2013 to 12/31/2018 or death, whichever came first. Cox proportional hazards regression models evaluated associations between new cancer diagnoses and suicide risk, adjusting for age, sex, VHA regional network, and mental health comorbidities. Suicide rates were calculated among Veterans with new cancer diagnoses through 84 months following diagnosis. RESULTS: A new cancer diagnosis corresponded to a 47% higher suicide risk (Adjusted Hazard Ratio [aHR] = 1.47, 95% CI: 1.33-1.63). The cancer subtype associated with the highest suicide risk was esophageal cancer (aHR = 6.01, 95% CI: 3.73-9.68), and other significant subtypes included head and neck (aHR = 3.55, 95% CI: 2.74-4.62) and lung cancer (aHR = 2.35, 95% CI: 1.85-3.00). Cancer stages 3 (aHR = 2.36, 95% CI: 1.80-3.11) and 4 (aHR = 3.53, 95% CI: 2.81-4.43) at diagnosis were positively associated with suicide risk. Suicide rates were highest within 3 months following diagnosis and remained elevated in the 3-6- and 6-12-month periods following diagnosis. CONCLUSION: Among Veteran VHA users, suicide risk was elevated following new cancer diagnoses. Risk was particularly high in the first 3 months. Additional screening and suicide prevention efforts may be warranted for VHA Veterans newly diagnosed with cancer.

Evaluation of the Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment Suicide Risk Modeling Clinical Program in the Veterans Health Administration.

Importance: The Veterans Health Administration (VHA) implemented a national clinical program using a suicide risk prediction algorithm, Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment (REACH VET), in which clinicians facilitate care enhancements for individuals identified in local top 0.1% suicide risk tiers. Evaluation studies are needed. Objective: To determine associations with treatment engagement, health care utilization, suicide attempts, safety plan documentation, and 6-month mortality. Design, Setting, and Participants: This cohort study used triple differences analyses comparing 6-month changes in outcomes after vs before program entry for individuals entering the REACH VET program (March 2017-December 2018) vs a similarly identified top 0.1% suicide risk tier cohort from prior to program initiation (March 2014-December 2015), adjusting for trends across subthreshold cohorts. Subcohort analyses (including individuals from March 2017-June 2018) evaluated difference-in-differences for cause-specific mortality using death certificate data. The subthreshold cohorts included individuals in the top 0.3% to 0.1% suicide risk tier, below the threshold for REACH VET eligibility, from the concurrent REACH VET period and from the pre-REACH VET period. Data were analyzed from December 2019 through September 2021. Exposures: REACH VET-designated clinicians treatment reevaluation and outreach for care enhancements, including safety planning, increased monitoring, and interventions to enhance coping. Main Outcomes and Measures: Process outcomes included VHA scheduled, completed, and missed appointments; mental health visits; and safety plan documentation and documentation within 6 months for individuals without plans within the prior 2 years. Clinical outcomes included mental health admissions, emergency department visits, nonfatal suicide attempts, and all-cause, suicide, and nonsuicide external-cause mortality. Results: A total of 173 313 individuals (mean [SD] age, 51.0 [14.7] years; 161 264 [93.1%] men and 12 049 [7.0%] women) were included in analyses, including 40 816 individuals eligible for REACH VET care and 36 604 individuals from the pre-REACH VET period in the top 0.1% of suicide risk. The REACH VET intervention was associated with significant increases in completed outpatient appointments (adjusted triple difference [ATD], 0.31; 95% CI, 0.06 to 0.55) and proportion of individuals with new safety plans (ATD, 0.08; 95% CI, 0.06 to 0.10) and reductions in mental health admissions (ATD, -0.08; 95% CI, -0.10 to -0.05), emergency department visits (ADT, -0.03; 95% CI, -0.06 to -0.01), and suicide attempts (ADT, -0.05; 95% CI, -0.06 to -0.03). Subcohort analyses did not identify differences in suicide or all-cause mortality (eg, age-and-sex-adjusted difference-in-difference for suicide mortality, 0.0007; 95% CI, -0.0006 to 0.0019). Conclusions and Relevance: These findings suggest that REACH VET implementation was associated with greater treatment engagement and new safety plan documentation and fewer mental health admissions, emergency department visits, and suicide attempts. Clinical programs using risk modeling may be effective tools to support care enhancements and risk reduction.

Hypertension Treatment Modality and Suicide Risk Among Veterans in Veterans Health Administration Care From 2015 to 2017.

Importance: The Veterans Health Administration (VHA) serves a population of veterans with a high prevalence of comorbid health conditions and increased risk for suicide. Objective: To replicate the findings of a previous study and assess whether exposure to angiotensin receptor blockers (ARBs) is associated with differential suicide risk compared with angiotensin-converting enzyme inhibitors (ACEIs) among veterans receiving VHA care. Design, Setting, and Participants: This nested case-control design included all suicide decedents from 2015 to 2017 with a VHA inpatient or outpatient encounter in the prior year and with either an active ACEI or ARB prescription in the 100 days prior to death. Using a 4:1 ratio, controls were matched to cases by age, sex, and hypertension and diabetes diagnoses. Controls were alive at the time of the death of the matched case, had a VHA encounter within the previous year, and had either an active ACEI or ARB medication fill within 100 days before the death of the matched case. Exposures: An active ACEI or ARB prescription within 100 days before the death of the case. Main Outcomes and Measures: Cases were suicide decedents from 2015 to 2017 per National Death Index search results included in the Veteran Affairs/Department of Defense Mortality Data Repository. Results: Among 1309 cases, the median (interquartile range [IQR]) age was 68 (60-76) years and among 5217 controls, the median (IQR) age was 67 (60-76) years, and 1.9% of veterans in both groups were female. ARBs were received by 20.2% of controls and 19.6% of cases; ACEIs were received by 79.8% of controls and 80.4% of cases. The crude suicide odds ratio for ARBs vs ACEIs was 0.966 (95% CI, 0.828-1.127). Controlling for covariates, the adjusted odds ratio for ARBs was 0.985 (95% CI, 0.834-1.164). Sensitivity analyses using only those covariates that differed significantly between groups, restricting to veterans ages 65 and older, dropping matching criteria, and adjusting for the quantity and temporal proximity of ACEI and ARB exposure in the 100 days prior to the index date, had consistent findings. Conclusions and Relevance: This case-control study did not identify differences in suicide risk by receipt of ARBs vs ACEIs in analyses specific to veterans receiving VHA care in contrast with findings from the referent study.

Can "deaths of despair" serve as a focus for planning and evaluating clinical and preventive services for Veterans?

Deaths of despair, a composite outcome including suicide and drug- and alcohol-related deaths, have been increasing, especially in subpopulations and geographic areas sensitive to economic and social hardships. The Veterans Health Administration (VHA) has begun evaluating the utility of this concept to guide planning and evaluations of clinical and preventive services for Veterans. In this study, mortality rates for middle-aged American men for 2013 to 2017 were from CDC WONDER, and rates for all Veterans, those using VHA healthcare services (VHA-utilizers), and other (non-VHA) Veterans were derived from National Death Index data. Findings demonstrated that rates for the composite were higher in VHA-utilizers and lower in non-VHA Veterans than middle-aged American men, consistent with use of VHA services by Veterans with the greatest needs. State rates in Veteran men were significantly and positively correlated with state rates for American men, and both were correlated with other characteristics of the social environment. The lack of correlation between rates for suicide and drug-related deaths indicates that deaths of despair cannot be modeled by assuming parallel paths from reactions to community-based stressors to the component outcomes; models should allow for an impact of community characteristics on partitioning between outcomes.