Predicting Homelessness Among Transitioning U.S. Army Soldiers.

INTRODUCTION: This study develops a practical method to triage Army transitioning service members (TSMs) at highest risk of homelessness to target a preventive intervention. METHODS: The sample included 4,790 soldiers from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in 1 of 3 Army STARRS 2011-2014 baseline surveys followed by the third wave of the STARRS-LS online panel surveys (2020-2022). Two machine learning models were trained: a Stage-1 model that used administrative predictors and geospatial data available for all TSMs at discharge to identify high-risk TSMs for initial outreach; and a Stage-2 model estimated in the high-risk subsample that used self-reported survey data to help determine highest risk based on additional information collected from high-risk TSMs once they are contacted. The outcome in both models was homelessness within 12 months after leaving active service. RESULTS: Twelve-month prevalence of post-transition homelessness was 5.0% (SE=0.5). The Stage-1 model identified 30% of high-risk TSMs who accounted for 52% of homelessness. The Stage-2 model identified 10% of all TSMs (i.e., 33% of high-risk TSMs) who accounted for 35% of all homelessness (i.e., 63% of the homeless among high-risk TSMs). CONCLUSIONS: Machine learning can help target outreach and assessment of TSMs for homeless prevention interventions.

Benzodiazepine Prescriptions for Homeless Veterans Affairs Service Users With Mental Illness.

OBJECTIVE: Despite elevated risk for substance use disorder and overdose death in the homeless population, benzodiazepine prescribing for this population has not been examined. In this study, the authors used data from the U.S. Department of Veterans Affairs (VA) health care system to examine benzodiazepine prescribing and risky and potentially inappropriate benzodiazepine prescribing practices for homeless VA service users. METHODS: Using national VA administrative data (2018-2019), the authors conducted logistic regression to compare likelihood of benzodiazepine prescribing and t tests to compare indicators of risky and potentially inappropriate benzodiazepine prescribing patterns for homeless service users with mental illness (N=244,113) and their housed peers (N=2,763,513). RESULTS: Unadjusted analyses showed that benzodiazepines were prescribed for 7.5% of homeless VA service users with mental illness, versus 9.4% of their housed peers (p<0.001). Analyses adjusted for sociodemographic and clinical characteristics and health care utilization showed that homeless service users were less likely than their housed peers to receive a benzodiazepine prescription (AOR=0.70, 99% CI=0.68-0.72). However, compared with their housed peers, homeless service users received higher rates of risky and potentially inappropriate benzodiazepine prescriptions, including multiple concurrent benzodiazepine prescriptions (9.4% vs. 7.0%, p<0.001) and concurrent prescriptions for benzodiazepines and opioids (36.9% vs. 31.2%, p<0.001) or sedatives (61.9% vs. 45.9%, p<0.001). CONCLUSIONS: Although homeless VA service users with mental illness were less likely than their housed peers to receive a benzodiazepine prescription, benzodiazepine prescriptions for these service users had more characteristics of risky and potentially inappropriate prescribing.

Firearm Injuries In Children And Adolescents: Health And Economic Consequences Among Survivors And Family Members.

More US children and adolescents today die from firearms than any other cause, and many more sustain firearm injuries and survive. The clinical and economic impact of these firearm injuries on survivors and family members remains poorly understood. Using 2007-21 commercial health insurance claims data, we studied 2,052 child and adolescent survivors compared to 9,983 matched controls who did not incur firearm injuries, along with 6,209 family members of survivors compared to 29,877 matched controls, and 265 family members of decedents compared to 1,263 matched controls. Through one year after firearm injury, child and adolescent survivors experienced a 117 percent increase in pain disorders, a 68 percent increase in psychiatric disorders, and a 144 percent increase in substance use disorders relative to the controls. Survivors' health care spending increased by an average of $34,884-a 17.1-fold increase-with 95 percent paid by insurers or employers. Parents of survivors experienced a 30-31 percent increase in psychiatric disorders, with 75 percent more mental health visits by mothers, and 5-14 percent reductions in mothers' and siblings' routine medical care. Family members of decedents experienced substantially larger 2.3- to 5.3-fold increases in psychiatric disorders, with at least 15.3-fold more mental health visits among parents. Firearm injuries in youth have notable health implications for the whole family, along with large effects on societal spending.

Reimagining Institutionalization and a Continuum of Care for People Experiencing Homelessness and Mental Illness.

This Viewpoint discusses the continuum of preventive, community, and institutional services necessary for improving care for people with mental illness experiencing homelessness.

Stressful Life Events and Risk of Homelessness After Active Duty: An Assessment of Risk and Resilience Among Servicemembers.

OBJECTIVES: The transition from military to civilian life may present increased exposure to various stressful life events (SLEs) that can increase the risk of homelessness (eg, loss of employment, dissolution of romantic relationships). We assessed the extent to which exposure to SLEs occurring proximal to US Army soldier transitions out of active duty was associated with risk of homelessness. METHODS: A total of 16 589 respondents who were no longer on active duty but participated while on active duty during 2011-2014 baseline surveys completed follow-up surveys during 2016-2018 and 2018-2019. The follow-up surveys assessed SLEs and homelessness occurring in the past 12 months. We used modified Poisson regression models to evaluate how much differential SLE exposure and effects explained the aggregate association of a risk index with homelessness among a sample of 6837 respondents, weighted to represent the full sample. RESULTS: More than half (n = 3510, 52.8%) of respondents reported experiencing any SLEs in the past 12 months. Most (60.5%) of the difference in prevalence of homelessness among respondents defined as being at high risk of homelessness (vs lower risk) was explained by differential exposure to, and/or effects of, these SLEs. Personal betrayal by a loved one and economic problems played the largest roles in adjusted risk differences (0.045 and 0.074, respectively). CONCLUSIONS: Homelessness might be reduced by gearing interventions toward soldiers at high risk of homelessness who are transitioning out of active duty to reduce exposure to and effects of modifiable SLEs on experiencing homelessness.

Establishing Academic Homes for Homelessness: A Call to Action.

Although homelessness ranks as one of society's most pressing and visible health equity challenges, the academic community has not actively addressed its health impacts, root causes, and potential solutions. Few schools and programs of public health even offer a basic course for students. In the COVID-19 pandemic era, academia must demonstrate urgency to address homelessness and educate learners, motivate fledgling researchers, inform policy makers, offer community-engaged and evidence-based studies, and join in the growing national debate about best approaches. At a minimum, every public health student should understand the interdisciplinary challenges of homelessness, its implications for health equity, and opportunities to address the crisis. We call for academia, particularly schools and programs of public health, to engage more fully in national partnerships to care for members of society who are most marginalized, in terms of health and behavioral health outcomes, quality of life, and connectedness.

Prospective Associations of Military Discharge Characterization with Post-active Duty Suicide Attempts and Homelessness: Results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS).

INTRODUCTION: Active duty service members transitioning to civilian life can experience significant readjustment stressors. Over the past two decades of the United States' longest sustained conflict, reducing transitioning veterans' suicidal behavior and homelessness became national priorities. However, it remains a significant challenge to identify which service members are at greatest risk of these post-active duty outcomes. Discharge characterization, which indicates the quality of an individual's military service and affects eligibility for benefits and services at the Department of Veterans Affairs, is a potentially important indicator of risk. MATERIALS AND METHODS: This study used data from two self-report panel surveys of the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) (LS1: 2016-2018, n = 14,508; and LS2: 2018-2019, n = 12,156), which were administered to respondents who previously participated while on active duty in one of the three Army STARRS baseline self-report surveys (2011-2014): the New Soldier Study (NSS), a survey of soldiers entering basic training; All Army Study, a survey of active duty soldiers around the world; and the Pre-Post Deployment Study, a survey of soldiers before and after combat deployment. Human Subjects Committees of the participating institutions approved all recruitment, informed consent, and data collection protocols. We used modified Poisson regression models to prospectively examine the association of discharge characterization (honorable, general, "bad paper" [other than honorable, bad conduct, dishonorable], and uncharacterized [due to separation within the first 180 days of service]) with suicide attempt (subsample of n = 4334 observations) and homelessness (subsample of n = 6837 observations) among those no longer on active duty (i.e., separated or deactivated). Analyses controlled for other suicide attempt and homelessness risk factors using standardized risk indices that were previously developed using the LS survey data. RESULTS: Twelve-month prevalence rates of self-reported suicide attempts and homelessness in the total pooled LS sample were 1.0% and 2.9%, respectively. While not associated with suicide attempt risk, discharge characterization was associated with homelessness after controlling for other risk factors. Compared to soldiers with an honorable discharge, those with a bad paper discharge had an increased risk of homelessness in the total sample (relative risk [RR] = 4.4 [95% CI = 2.3-8.4]), as well as within subsamples defined by which baseline survey respondents completed (NSS vs. All Army Study/Pre-Post Deployment Study), whether respondents had been separated (vs. deactivated), and how much time had elapsed since respondents were last on active duty. CONCLUSIONS: There is a robust association between receiving a bad paper discharge and post-separation/deactivation homelessness. Policies that enhance transition assistance and access to mental healthcare for high-risk soldiers may aid in reducing post-separation/deactivation homelessness among those who do not receive an honorable discharge.

Predicting Homelessness Among U.S. Army Soldiers No Longer on Active Duty.

INTRODUCTION: The ability to predict and prevent homelessness has been an elusive goal. The purpose of this study was to develop a prediction model that identified U.S. Army soldiers at high risk of becoming homeless after transitioning to civilian life based on information available before the time of this transition. METHODS: The prospective cohort study consisted of observations from 16,589 soldiers who were separated or deactivated from service and who had previously participated in 1 of 3 baseline surveys of the Army Study to Assess Risk and Resilience in Servicemembers in 2011-2014. A machine learning model was developed in a 70% training sample and evaluated in the remaining 30% test sample to predict self-reported homelessness in 1 of 2 Longitudinal Study surveys administered in 2016-2018 and 2018-2019. Predictors included survey, administrative, and geospatial variables available before separation/deactivation. Analysis was conducted in November 2020-May 2021. RESULTS: The 12-month prevalence of homelessness was 2.9% (SE=0.2%) in the total Longitudinal Study sample. The area under the receiver operating characteristic curve in the test sample was 0.78 (SE=0.02) for homelessness. The 4 highest ventiles (top 20%) of predicted risk included 61% of respondents with homelessness. Self-reported lifetime histories of depression, trauma of having a loved one murdered, and post-traumatic stress disorder were the 3 strongest predictors of homelessness. CONCLUSIONS: A prediction model for homelessness can accurately target soldiers for preventive intervention before transition to civilian life.

Changes in Health Care Spending, Use, and Clinical Outcomes After Nonfatal Firearm Injuries Among Survivors and Family Members : A Cohort Study.

BACKGROUND: Despite increasing awareness of firearm-related deaths, evidence on the clinical and economic implications of nonfatal firearm injuries is limited. OBJECTIVE: To measure changes in clinical and economic outcomes after nonfatal firearm injuries among survivors and their family members. DESIGN: Cohort study. SETTING: MarketScan Medicare and commercial claims data, 2008 to 2018. PARTICIPANTS: 6498 survivors of firearm injuries matched to 32 490 control participants and 12 489 family members of survivors matched to 62 445 control participants. INTERVENTION: Exposure to nonfatal firearm injury as a survivor or family member of a survivor. MEASUREMENTS: Changes in health care spending, use, and morbidity from preinjury through 1 year postinjury relative to control participants, on average and by type and severity of firearm injury. RESULTS: After nonfatal firearm injury, medical spending increased $2495 per person per month (402%) and cost sharing increased $102 per person per month (176%) among survivors relative to control participants (P < 0.001) in the first year after injury, driven by an increase in the first month of $25 554 (4122%) in spending and $1112 (1917%) in cost sharing per survivor (P < 0.001). All categories of health care use increased relative to the control group. Survivors had a 40% increase in pain diagnoses, a 51% increase in psychiatric disorders, and an 85% increase in substance use disorders after firearm injury relative to control participants (P < 0.001), accompanied by increased pain and psychiatric medications. Family members had a 12% increase in psychiatric disorders relative to their control participants (P = 0.003). These overall clinical and economic changes were driven by intentional firearm injuries and more severe firearm injuries. LIMITATION: Precision of diagnostic codes and generalizability to other patient populations, including Medicaid and uninsured patients. CONCLUSION: In survivors, nonfatal firearm injuries led to increases in psychiatric disorders, substance use disorders, and pain diagnoses, alongside substantial increases in health care spending and use. In addition, mental health worsened among family members. PRIMARY FUNDING SOURCE: National Institutes of Health.

Health system-based housing navigation for patients experiencing homelessness: A new care coordination framework.

Patients experiencing homelessness are among the most disadvantaged in our society, suffering from poor health outcomes and exhibiting disproportionately high hospital utilization and spending. However, to date, hospitals have only scantily devoted time or resources to the housing coordination aspect of homelessness. Implementing better systems to coordinate housing for patients experiencing homelessness may improve health outcomes and reduce health care utilization for this population. This objective is now more important than ever as the economic impact of COVID-19 is expected to exacerbate the homelessness crisis. Ensuring that patients are properly connected to temporary or permanent housing is valuable to patient health, health care system metrics such as excess spending and utilization, and provider performance under Accountable Care Organizations or other risk-bearing payment models. Here, we propose a health systems-based housing coordination framework that may improve care delivery for patients experiencing homelessness. This framework relies on the coordination between dedicated hospital-based housing navigators who can identity patients experiencing homelessness and outpatient housing navigators equipped to coordinate short- and long-term housing specifically for patients experiencing homelessness who frequently interact with the health care system.

Health Care Spending And Use Among People Experiencing Unstable Housing In The Era Of Accountable Care Organizations.

Provider organizations are increasingly held accountable for health care spending in vulnerable populations. Longitudinal data on health care spending and use among people experiencing episodes of homelessness could inform the design of alternative payment models. We used Medicaid claims data to analyze spending and use among 402 people who were continuously enrolled in the Boston Health Care for the Homeless Program (BHCHP) from 2013 through 2015, compared to spending and use among 18,638 people who were continuously enrolled in Massachusetts Medicaid with no evidence of experiencing homelessness. The BHCHP population averaged $18,764 per person per year in spending-2.5 times more than spending among the comparison Medicaid population ($7,561). In unadjusted analyses this difference was explained by greater spending in the BHCHP population on outpatient care, including emergency department care, as well as on inpatient care and prescription drugs. After adjustment for covariates and multiple hypothesis testing, the difference was largely driven by outpatient spending. Differences were sensitive to adjustments for risk score, which suggests that housing instability and health risk are meaningfully correlated. This longitudinal analysis improves understanding of health care use and resource needs among people who are homeless or have unstable housing, and it could inform the design of alternative payment models for vulnerable populations.