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Flores MW, Lê Cook B, Mullin B, Halperin-Goldstein G, Nathan A, Tenso K, Schuman-Olivier Z. Associations between neighborhood-level factors and opioid-related mortality: A multi-level analysis using death certificate data. Addiction 2020; 115:1878-1889. [PMID: 32061139 PMCID: PMC7734613 DOI: 10.1111/add.15009] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Revised: 08/02/2019] [Accepted: 02/11/2020] [Indexed: 01/08/2023]
Abstract
AIM To identify associations between opioid-related mortality and neighborhood-level risk factors. DESIGN Cross-sectional study. SETTING Massachusetts, USA. PARTICIPANTS Using 2011-14 Massachusetts death certificate data, we identified opioid-related (n = 3089) and non-opioid-related premature deaths (n = 8729). MEASUREMENTS The independent variables consisted of four sets of neighborhood-level factors: (1) psychosocial, (2) economic, (3) built environment and (4) health-related. At the individual level we included the following compositional factors: age at death, sex, race/ethnicity, marital status, education, veteran status and nativity. The primary outcome of interest was opioid-related mortality. FINDINGS Multi-level models identified number of social associations per 10 000 [odds ratio (OR) = 0.84, P = 0.002, 95% confidence interval (CI) = 0.75-0.94] and number of hospital beds per 10 000 (OR = 0.78, P < 0.001, 95% CI = 0.68-0.88) to be inversely associated with opioid-related mortality, whereas the percentage living in poverty (OR = 1.01, P = 0.008, 95% CI = 1.00-1.01), food insecurity rate (OR = 1.21, P = 0.002, 95% CI = 1.07-1.37), number of federally qualified health centers (OR = 1.02, P = 0.028, 95% CI = 1.02-1.08) and per-capita morphine milligram equivalents of hydromorphone (OR = 1.05, P = 0.003, 95% CI = 1.01-1.08) were positively associated with opioid-related mortality. CONCLUSIONS Opioid-related deaths between 2011 and 2014 in the state of Massachusetts appear to be positively associated with the percentage living in poverty, food insecurity rate, number of federally qualified health centers and per-capita morphine milligram equivalents of hydromorphone, but inversely associated with number of social associations per 10 000 and number of hospital beds per 10 000.
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Feyman Y, Auty SG, Tenso K, Strombotne KL, Legler A, Griffith KN. County-Level Impact of the COVID-19 Pandemic on Excess Mortality Among U.S. Veterans: A Population-Based Study. LANCET REGIONAL HEALTH. AMERICAS 2021; 5:100093. [PMID: 34778864 PMCID: PMC8577544 DOI: 10.1016/j.lana.2021.100093] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 09/16/2021] [Accepted: 09/17/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND As the novel coronavirus (COVID-19) continues to impact the world at large, Veterans of the US Armed Forces are experiencing increases in both COVID-19 and non-COVID-19 mortality. Veterans may be more susceptible to the pandemic than the general population due to their higher comorbidity burdens and older age, but no research has examined if trends in excess mortality differ between these groups. Additionally, individual-level data on demographics, comorbidities, and deaths are provided in near-real time for all enrolees of the Veterans Health Administration (VHA). These data provide a unique opportunity to identify excess mortality throughout 2020 at a subnational level, and to validate these estimates against local COVID-19 burden. METHODS We queried VHA administrative data on demographics and comorbidities for 11.4 million enrolees during 2016-2020. Pre-pandemic data was used to develop and cross-validate eight mortality prediction models at the county-level including Poisson, Poisson quasi-likelihood, negative binomial, and generalized estimating equations. We then estimated county-level excess Veteran mortality during 2020 and correlated these estimates with local rates of COVID-19 confirmed cases and deaths. FINDINGS All models demonstrated excellent agreement between observed and predicted mortality during 2016-2019; a Poisson quasi-likelihood with county fixed effects minimized median squared error with a calibration slope of 1.00. Veterans of the U.S. Armed Forces faced an excess mortality rate of 13% in 2020, which corresponds to 50,299 excess deaths. County-level estimates of excess mortality were correlated with both COVID-19 cases (R2=0.77) and deaths per 1,000 population (R2=0.59). INTERPRETATION We developed sub-national estimates of excess mortality associated with the pandemic and shared our data as a resource for researchers and data journalists. Despite Veterans' greater likelihood of risk factors associated with severe COVID-19 illness, their excess mortality rate was slightly lower than the general population. Consistent access to health care and the rapid expansion of VHA telemedicine during the pandemic may explain this divergence. FUNDING This work was supported by grants from the Department of Veterans Affairs Quality Enhancement Research Initiative [PEC 16-001]. Dr. Griffith's effort was supported in part by the Agency for Healthcare Research & Quality [K12 HS026395].
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Minegishi T, Garrido MM, Lewis ET, Oliva EM, Pizer SD, Strombotne KL, Trafton JA, Tenso K, Sohoni PS, Frakt AB. Randomized Policy Evaluation of the Veterans Health Administration Stratification Tool for Opioid Risk Mitigation (STORM). J Gen Intern Med 2022; 37:3746-3750. [PMID: 35715661 PMCID: PMC9585134 DOI: 10.1007/s11606-022-07622-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 04/13/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND The Veterans Health Administration (VHA) developed a dashboard Stratification Tool for Opioid Risk Mitigation (STROM) to guide clinical practice interventions. VHA released a policy mandating that high-risk patients of an adverse event based on the STORM dashboard are to be reviewed by an interdisciplinary team of clinicians. AIM Randomized program evaluation to evaluate if patients in the oversight arm had a lower risk of opioid-related serious adverse events (SAEs) or death compared to those in the non-oversight arm. SETTING AND PARTICIPANTS One-hundred and forty VHA facilities (aka medical centers) were randomly assigned to two groups: oversight and non-oversight arms. VHA patients who were prescribed opioids between April 18, 2018, and November 8, 2019, were included in the cohort. PROGRAM DESCRIPTION We hypothesized that patients cared for by VHA facilities that received the policy with the oversight accountability language would achieve lower opioid-related SAEs or death. PROGRAM EVALUATION We did not observe a relationship between the oversight arm and opioid-related SAEs or death. Patients in the non-oversight arm had a significantly higher chance of receiving a case review compared to those in the oversight arm. DISCUSSION Even though our findings were unexpected, the STORM policy overall was likely successful in focusing the provider's attention on very high-risk patients.
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Li Y, Legler A, Tenso K, Garrido M, Pizer S. Impact of Medical Training Programs on Time-to-Fill Physician Vacancies at the Veterans Health Administration. Med Care 2024; 62:182-188. [PMID: 38180002 DOI: 10.1097/mlr.0000000000001970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Abstract
BACKGROUND The Department of Veterans Affairs (VA) provides the largest Graduate Medical Education (GME) training platform for health professionals in the United States. Studies on the impact of VA GME programs on physician recruitment were lacking. OBJECTIVES To examine the impact of the size of residency training programs at a VA facility on the facility's time-to-fill physician vacancies, and whether the impact differs by the socioeconomic deprivation and public school quality of the geographic area. PROJECT DESIGN We constructed an instrumental variable for training program size by interacting the facility clinicians share with the total training allocation nationally. SUBJECTS Our evaluation used national data on filled physician vacancies in the VA that were posted between 2020 and 2021. MEASURES The outcome evaluated was time-to-fill physician vacancies. Our explanatory variable was the facility-year level number of physician residency slots. RESULTS For positions posted in 2020, an increase of one training slot was significantly associated with a decrease of 1.33 days to fill physician vacancies (95% CI, 0.38-2.28) in facilities in less deprived areas, a decrease of 1.50 days (95% CI, 0.75-2.25) in facilities with better public schools, a decrease of 3.30 days (95% CI, 0.85-5.76) in facilities in both less deprived areas and better public schools. We found similar results for positions posted in 2020 and 2021 when limiting time-to-fill to <500 days. CONCLUSIONS We found that increasing the size of the residency program at a VA facility could decrease the facility's time-to-fill vacant physician positions in places with less socioeconomic deprivation or better public schools.
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Tenso K, Strombotne KL, Feyman Y, Auty SG, Legler A, Griffith KN. Excess Mortality at Veterans Health Administration Facilities During the COVID-19 Pandemic. Med Care 2023; 61:456-461. [PMID: 37219062 PMCID: PMC10353262 DOI: 10.1097/mlr.0000000000001866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
IMPORTANCE The COVID-19 pandemic resulted in excess mortality among the general US population and at Veterans Health Administration (VHA) facilities. It is critical to understand the characteristics of facilities that experienced the highest and lowest pandemic-related mortality to inform future mitigation efforts. OBJECTIVE To identify facility-level excess mortality during the pandemic and to correlate these estimates with facility characteristics and community-wide rates of COVID-19 burden. DESIGN We used pre-pandemic data to estimate mortality risk prediction models using 5-fold cross-validation and Poisson quasi-likelihood regression. We then estimated excess mortality and observed versus expected (O/E) mortality ratios by the VHA facility from March to December 2020. We examined facility-level characteristics by excess mortality quartile. PARTICIPANTS Overall, there were 11.4 million VHA enrollees during 2016 and 2020. MAIN MEASURES Facility-level O/E mortality ratios and excess all-cause mortality. RESULT VHA-enrolled veterans experienced 52,038 excess deaths from March to December 2020, equating to 16.8% excess mortality. Facility-specific rates ranged from -5.5% to +63.7%. Facilities in the lowest quartile for excess mortality experienced fewer COVID-19 deaths (0.7-1.51, P <0.001) and cases (52.0-63.0, P =0.002) per 1,000 population compared with the highest quartile. The highest quartile facilities had more hospital beds (276.7-187.6, P =0.024) and a higher percent change in the share of visits conducted via telehealth from 2019 to 2020 (183%-133%, P <0.008). CONCLUSIONS There was a large variation in mortality across VHA facilities during the pandemic, which was only partially explained by the local COVID-19 burden. Our work provides a framework for large health care systems to identify changes in facility-level mortality during a public health emergency.
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Tenso K, Strombotne K, Garrido MM, Lum J, Pizer S. Virtual Mental Health Care and Suicide-Related Events. JAMA Netw Open 2024; 7:e2443054. [PMID: 39499516 PMCID: PMC11539012 DOI: 10.1001/jamanetworkopen.2024.43054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Accepted: 09/12/2024] [Indexed: 11/07/2024] Open
Abstract
Importance The rising suicide rates in the US emphasize the need for effective prevention. While telehealth has transformed access to mental health care, the impact of telehealth on suicide outcomes is unknown. Objective To evaluate the association of virtual mental health services with individual-level suicide-related events (SREs). Design, Setting, and Participants This retrospective cohort study using broadband access as an instrumental variable assessed a national sample of Veterans Health Administration patients who received mental health care between March 1, 2020, and December 31, 2021. Participants were recently separated (ie, discharged or released from active duty) veterans who completed their active duty service between March 1, 2019, and December 31, 2020, and who received at least 2 outpatient or inpatient diagnoses related to major depressive disorder, substance use disorder, or posttraumatic stress disorder within the year before their most recent separation date. Data were analyzed May 1 to October 31, 2023. Exposure Percentage of a patient's total mental health visits that were conducted virtually by psychiatrists, psychologists, or social workers within a calendar month. Main Outcomes and Measures Binary measure indicating whether the patient had experienced an SRE (defined as a nonfatal suicide attempt, intentional self-harm, or suicide death) in a specific month and year as evaluated an instrumental variable probit model. Results The sample included 66 387 data points from 16 236 unique recently separated veterans. Among these entries, 44 766 were for male veterans (67.4%), the mean (SD) age across the sample was 32.9 (8.9) years, and the sample was representative of the US veteran population. There were 929 SREs (1.4%). Virtual mental health visits comprised a mean (SD) of 44.6% (46.1%) of all mental health visits. In instrumental variable probit analyses accounting for factors simultaneously associated with use of virtual mental health care and SRE risk, a 1% increase in the probability of virtual mental health visits was associated with a 2.5% decrease in SREs. Conclusions and Relevance Findings from this cohort study using a retrospective quasi-experimental design found that an increase in virtual mental health visits relative to total visits was associated with a statistically significant decrease in SREs, suggesting that providing virtual mental health services may reduce suicide-related outcomes.
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Tenso K, Pizer S, Palani S. Delivery system emergency department capacity and its effect on nonsystem service utilization. Acad Emerg Med 2023; 30:359-367. [PMID: 36797812 DOI: 10.1111/acem.14694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 01/24/2023] [Accepted: 02/03/2023] [Indexed: 02/18/2023]
Abstract
BACKGROUND Emergency department (ED) use is often seen as a source of excess health care spending, prompting managers to limit ED capacity in their health systems. However, if limited ED capacity in a delivery system leads patients to seek emergency care elsewhere, then health care quality and efficient management may be compromised within the system. OBJECTIVE The objective of this study was to explore the effect of the Veterans Health Administration (VHA) in-house ED clinician capacity on VHA community care (CC) ED claims. METHODS We used administrative data from the VHA to identify CC ED claims and Department of Veterans Affairs emergency physician (EP) capacity for 2014-2019. We used quasi-experimental instrumental variables approach with two different instruments: percent weekday federal holidays and VHA EP full-time equivalents (FTEs). We controlled for VHA ED variables such as ED wait times (door to triage, door to doctor, and door to admission) and demand variables such as alternative insurance coverage, driving time to VHA care, and demographic variables (employment, age, household income, race, gender, and VHA priority status). RESULTS After instrumenting for capacity with percent weekday federal holidays, we found that one clinic-day capacity (one 8-h ED shift) per 10,000 enrollees increase at the VHA ED will result in a reduction of 61 CC ED claims per 10,000 enrollees. After instrumenting for capacity with EP FTE, we found that one clinic-day capacity (one 8-h ED shift) per 10,000 enrollees increase at the VHA ED will result in a reduction of 48 CC ED claims per 10,000 enrollees. Both of these results are statistically significant at p < 0.001. CONCLUSIONS Our findings imply that offering more in-house ED care, in the form of clinician capacity, can substantially reduce out-of-system ED use. The results may be of interest to integrated health care system managers who prefer their patients to stay within network.
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Tenso K, Li Y, Legler A, Sadej I, Kabdiyeva A, Garrido MM, Pizer SD. Medical training program size and clinical staff productivity and turnover. Health Serv Res 2025; 60:e14364. [PMID: 39045876 PMCID: PMC11782085 DOI: 10.1111/1475-6773.14364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2024] Open
Abstract
OBJECTIVE The objective of this analysis was to evaluate the effect of resident program training size on clinician productivity and turnover in the Veterans Health Administration (VHA), the largest education and training platform for medical professionals in the United States. DATA SOURCES We retrieved administrative data on training programs and training facilities from the VA Office of Academic Affiliations and the VHA Corporate Data Warehouse. Data on primary care physician shortage areas were retrieved from the Health Resources and Services Administration. STUDY DESIGN We used a quasi-experimental instrumental variables 2SLS design and constructed an exogenous predicted training allocation treatment variable as a function of the total national training program allocation. The outcome was clinical staff productivity and turnover. Secondary analyses stratified results using Health Professional Shortage Areas data (HPSA). DATA COLLECTION/EXTRACTION METHODS Data were obtained for a national dataset of 141 VHA medical facilities and 26 specialties that hosted training programs across 11 years from 2011 to 2021 (N = 132,177). PRINCIPAL FINDINGS Instrumental variables results showed that on average, an increase of one training slot in a specialty leads to a decrease of 0.039 visits per standardized clinic day (p < 0.001) and a 0.02 percentage point increase in turnover (p < 0.001). The direction of this association varied by specialty: while psychiatry and psychology specialties saw a decline in productivity, fields such as primary care and cardiology experienced an increase in productivity. HPSA stratified results indicate that negative effects on productivity and turnover are driven by areas with little to no primary care physician shortage, whereas shortage areas experienced a small increase in productivity and no effect on turnover. CONCLUSIONS This quasi-experimental evaluation indicates that resident training program size is associated with reduced productivity and increased turnover in specialties such as psychiatry and in facilities with high baseline productivity. However, in specialties like primary care and cardiology, as well as areas with shortages of primary care, larger training programs are associated with increased productivity.
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Tenso K, Avila CJD, Garrido M, Lauver M, Reger MA, Legler A, Strombotne K. The use of crisis line services during the COVID-19 pandemic: Evidence from the veterans health administration. Gen Hosp Psychiatry 2023; 82:101-102. [PMID: 36858847 PMCID: PMC9916126 DOI: 10.1016/j.genhosppsych.2023.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 02/08/2023] [Indexed: 02/12/2023]
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Tenso K. Public Health Students to Fight COVID-19 Worldwide, Not Just at Home. Am J Public Health 2022; 112:595-597. [PMID: 35319929 PMCID: PMC8961858 DOI: 10.2105/ajph.2021.306681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/15/2021] [Indexed: 11/04/2022]
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Palani S, Garrido MM, Tenso K, Pizer SD. Community care emergency room use and specialty care leakage from Veterans Health Administration hospitals. Acad Emerg Med 2023; 30:379-387. [PMID: 36660799 DOI: 10.1111/acem.14667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 01/09/2023] [Accepted: 01/13/2023] [Indexed: 01/21/2023]
Abstract
BACKGROUND Care leakage from health systems can affect quality and cost of health care delivery. Identifying modifiable predictors of care leakage may help health systems avoid adverse consequences. Out-of-system emergency department (ED) use may be one modifiable cause of care leakage. Our objective was to investigate the relationship between out-of-system ED use and subsequent specialty care leakage. METHODS We used the Veterans Health Administration's (VA) Corporate Data Warehouse data from January 2021 to July 2021. A total of 330,547 patients who had at least one ED visit (in-house or community care [CC]) in the index period (January 2021-March 2021) were included. Outcomes were the proportions of specialty care visits in the community within 30, 60, 90, and 120 days from the index ED visit. Instrumental-variables regressions, using VA ED physician capacity as an instrument for Veterans' CC ED use, were utilized to estimate the proportions of subsequent specialty care visits in the community. Estimates were adjusted for patient and facility characteristics. RESULTS A CC ED visit was associated with increases in the proportions of specialty care visits in the community within 30, 60, 90, and 120 days from index visit. Within 30 days from index visit, CC ED patients were estimated to have a 45-percentage-point (pp; 95% confidence interval [CI], 43-47 pp) higher proportion of CC specialty care visits than patients with an in-house ED visit (p < 0.001). We observed similar, though slightly attenuated, results over long time periods since the index visit. CONCLUSIONS Veterans who have a CC ED visit have a greater proportion of subsequent specialty care visits in CC hospitals and clinics than Veterans with a VA ED visit. This relationship persists when we examine Veterans whose decision to go to a CC ED is influenced by VA ED physician capacity rather than general preferences for CC.
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Reger MA, Legler A, Lauver M, Tenso K, Manchester C, Griffin C, Strombotne KL, Landes SJ, Porter S, Bourgeois JE, Garrido MM. Caring Letters Sent by a Clinician or Peer to At-Risk Veterans: A Randomized Clinical Trial. JAMA Netw Open 2024; 7:e248064. [PMID: 38683611 PMCID: PMC11059042 DOI: 10.1001/jamanetworkopen.2024.8064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 02/25/2024] [Indexed: 05/01/2024] Open
Abstract
Importance Caring letters is an evidence-based suicide prevention intervention in acute care settings, but its outcomes among individuals who contact a national crisis line have not previously been evaluated. Objective To examine the outcomes of the Veterans Crisis Line (VCL) caring letters intervention and determine whether there are differences in outcomes by signatory. Design, Setting, and Participants This parallel randomized clinical trial compared signatories of caring letters and used an observational design to compare no receipt of caring letters with any caring letters receipt. Participants included veterans who contacted the VCL. Enrollment occurred between June 11, 2020, and June 10, 2021, with 1 year of follow-up. Analyses were completed between July 2022 and August 2023. Intervention Veterans were randomized to receive 9 caring letters for 1 year from either a clinician or peer veteran signatory. Main Outcomes and Measures The primary outcome measure was suicide attempt incidence in the 12 months following the index VCL contact. Incidence of Veterans Health Administration (VHA) inpatient, outpatient, and emergency health care use were secondary outcomes. All-cause mortality was an exploratory outcome. Wilcoxon rank-sum tests and χ2 tests were used to assess the differences in outcomes among the treatment and comparison groups. Results A total of 102 709 veterans (86 942 males [84.65%]; 15 737 females [15.32%]; mean [SD] age, 53.82 [17.35] years) contacted the VCL and were randomized. No association was found among signatory and suicide attempts, secondary outcomes, or all-cause mortality. In the analysis of any receipt of caring letters, there was no evidence of an association between caring letters receipt and suicide attempt incidence. Caring letters receipt was associated with increased VHA health care use (any outpatient: hazard ratio [HR], 1.10; 95% CI, 1.08-1.13; outpatient mental health: HR, 1.19; 95% CI, 1.17-1.22; any inpatient: HR, 1.13; 95% CI, 1.08-1.18; inpatient mental health: HR, 1.14; 95% CI, 1.07-1.21). Caring letters receipt was not associated with all-cause mortality. Conclusions and Relevance Among VHA patients who contacted the VCL, caring letters were not associated with suicide attempts, but were associated with a higher probability of health care use. No differences in outcomes were identified by signatory. Trial Registration isrctn.org Identifier: ISRCTN27551361.
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