Impact of Implementation Facilitation on the REACH VET Clinical Program for Veterans at Risk for Suicide.

OBJECTIVE: In 2017, the Veterans Health Administration (VHA) implemented a national suicide prevention program, called Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment (REACH VET), that uses a predictive algorithm to identify, attempt to reach, assess, and care for patients at the highest risk for suicide. The authors aimed to evaluate whether facilitation enhanced implementation of REACH VET at VHA facilities not meeting target completion rates. METHODS: In this hybrid effectiveness-implementation type 2 program evaluation, a quasi-experimental pre-post design was used to assess changes in implementation outcome measures evaluated 6 months before and 6 months after onset of facilitation of REACH VET implementation at 23 VHA facilities. Measures included percentages of patients with documented coordinator and provider acknowledgment of receipt, care evaluation, and outreach attempt. Generalized estimating equations were used to compare differences in REACH VET outcome measures before and after facilitation. Qualitative interviews were conducted with personnel and were explored via template analysis. RESULTS: Time had a significant effect in all outcomes models (p<0.001). An effect of facilitation was significant only for the outcome of attempted outreach. Patients identified by REACH VET had significantly higher odds of having a documented outreach attempt after facilitation of REACH VET implementation, compared with before facilitation. Site personnel felt supported and reported that the external facilitators were helpful and responsive. CONCLUSIONS: Facilitation of REACH VET implementation was associated with an improvement in outreach attempts to veterans identified as being at increased risk for suicide. Outreach is critical for engaging veterans in care.

Deploying a national clinical text processing infrastructure.

OBJECTIVES: Clinical text processing offers a promising avenue for improving multiple aspects of healthcare, though operational deployment remains a substantial challenge. This case report details the implementation of a national clinical text processing infrastructure within the Department of Veterans Affairs (VA). METHODS: Two foundational use cases, cancer case management and suicide and overdose prevention, illustrate how text processing can be practically implemented at scale for diverse clinical applications using shared services. RESULTS: Insights from these use cases underline both commonalities and differences, providing a replicable model for future text processing applications. CONCLUSIONS: This project enables more efficient initiation, testing, and future deployment of text processing models, streamlining the integration of these use cases into healthcare operations. This project implementation is in a large integrated health delivery system in the United States, but we expect the lessons learned to be relevant to any health system, including smaller local and regional health systems in the United States.

Impact of Mandated Case Review Policy on Opioid Discontinuation and Mortality Among High-Risk Long-Term Opioid Therapy Patients: The STORM Stepped-Wedge Cluster Randomized Controlled Trial.

BACKGROUND: Although long-term opioid therapy (LTOT) has its own risks, opioid discontinuation could pose harm for high-risk Veterans Health Administration (VHA) patients receiving LTOT. There is limited information on the impact of a mandate requiring providers to perform case reviews on high-risk patients with an active opioid prescription (ie, mandated case review policy) on opioid discontinuation and mortality. METHODS: Our study is a secondary data analysis of a 23-month stepped-wedge cluster randomized controlled trial between April 2018 and March 2020. The study included 10 685 LTOT patients with a predicted risk of a serious adverse event between the top 1% to 5% nationally who entered the risk range between 4/18/2018 and 11/9/2019. We examined whether the mandated case review policy had an impact on opioid discontinuation and mortality for the patients. RESULTS: Among 10 685 LTOT patients (88.2% male; mean [SD] age, 61.1 [11.7] years), 29.1% experienced discontinuation and the mortality rate was 9.5%. Patients under mandated case review had a decreased risk of opioid discontinuation (average marginal effect [AME], -11.16 [95% CI, -15.30 to -7.01] percentage points) and all-cause mortality (AME, -3.31 [95% CI, -5.63 to -1.00] percentage points), relative to patients who were not under the mandate. CONCLUSIONS: The VHA mandated case review policy was associated with lower probability of discontinuation and all-cause mortality for high-risk patients receiving LTOT. Interventions that maintain care engagement while optimizing pain management for high-risk patients may be beneficial for minimizing mortality and other risks associated with discontinuation.

Identification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans.

Importance: Suicide is a leading cause of death; however, the molecular genetic basis of suicidal thoughts and behaviors (SITB) remains unknown. Objective: To identify novel, replicable genomic risk loci for SITB. Design, Setting, and Participants: This genome-wide association study included 633 778 US military veterans with and without SITB, as identified through electronic health records. GWAS was performed separately by ancestry, controlling for sex, age, and genetic substructure. Cross-ancestry risk loci were identified through meta-analysis. Study enrollment began in 2011 and is ongoing. Data were analyzed from November 2021 to August 2022. Main Outcome and Measures: SITB. Results: A total of 633 778 US military veterans were included in the analysis (57 152 [9%] female; 121 118 [19.1%] African ancestry, 8285 [1.3%] Asian ancestry, 452 767 [71.4%] European ancestry, and 51 608 [8.1%] Hispanic ancestry), including 121 211 individuals with SITB (19.1%). Meta-analysis identified more than 200 GWS (P < 5 × 10-8) cross-ancestry risk single-nucleotide variants for SITB concentrated in 7 regions on chromosomes 2, 6, 9, 11, 14, 16, and 18. Top single-nucleotide variants were largely intronic in nature; 5 were independently replicated in ISGC, including rs6557168 in ESR1, rs12808482 in DRD2, rs77641763 in EXD3, rs10671545 in DCC, and rs36006172 in TRAF3. Associations for FBXL19 and AC018880.2 were not replicated. Gene-based analyses implicated 24 additional GWS cross-ancestry risk genes, including FURIN, TSNARE1, and the NCAM1-TTC12-ANKK1-DRD2 gene cluster. Cross-ancestry enrichment analyses revealed significant enrichment for expression in brain and pituitary tissue, synapse and ubiquitination processes, amphetamine addiction, parathyroid hormone synthesis, axon guidance, and dopaminergic pathways. Seven other unique European ancestry-specific GWS loci were identified, 2 of which (POM121L2 and METTL15/LINC02758) were replicated. Two additional GWS ancestry-specific loci were identified within the African ancestry (PET112/GATB) and Hispanic ancestry (intergenic locus on chromosome 4) subsets, both of which were replicated. No GWS loci were identified within the Asian ancestry subset; however, significant enrichment was observed for axon guidance, cyclic adenosine monophosphate signaling, focal adhesion, glutamatergic synapse, and oxytocin signaling pathways across all ancestries. Within the European ancestry subset, genetic correlations (r > 0.75) were observed between the SITB phenotype and a suicide attempt-only phenotype, depression, and posttraumatic stress disorder. Additionally, polygenic risk score analyses revealed that the Million Veteran Program polygenic risk score had nominally significant main effects in 2 independent samples of veterans of European and African ancestry. Conclusions and Relevance: The findings of this analysis may advance understanding of the molecular genetic basis of SITB and provide evidence for ESR1, DRD2, TRAF3, and DCC as cross-ancestry candidate risk genes. More work is needed to replicate these findings and to determine if and how these genes might impact clinical care.

Outpatient provider staffing ratios: Binary recursive models associated with quality, access, and satisfaction.

Veterans Health Administration (VHA) continues to expand the mental health (MH) workforce to meet increasing demand for services. In the present study, longitudinal unbiased recursive partitioning models (conditional inference trees) were created to identify optimal cutoffs for outpatient staffing ratios associated with success on VHA's measures of quality, access, and satisfaction. Quarterly Staff-to-Patient Ratios (SPRs), defined as the number of full-time equivalent providers per 1,000 veterans receiving outpatient mental health care, were calculated for 12 quarters from fiscal years 2016-2018. Associations between VHA metrics associated with quality, access, and satisfaction were evaluated in relation to the overall outpatient SPR. The root node identified an overall outpatient SPR of 7.39 as the split for optimal MH performance. Root nodes associated with metrics addressing population coverage, continuity of care, and experience of care identified SPRs of 7.87, 6.81, and 7.42, respectively. In all analyses, the lowest SPRs were associated with the lowest performance on VHA MH metrics, while the highest SPRs were associated with the highest performance. Analyses support VHA's current recommended minimum outpatient SPR of 7.72 as a reasonable target to provide high-quality care, access, and satisfaction. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Effect of a Predictive Analytics-Targeted Program in Patients on Opioids: a Stepped-Wedge Cluster Randomized Controlled Trial.

BACKGROUND: Risk of overdose, suicide, and other adverse outcomes are elevated among sub-populations prescribed opioid analgesics. To address this, the Veterans Health Administration (VHA) developed the Stratification Tool for Opioid Risk Mitigation (STORM)-a provider-facing dashboard that utilizes predictive analytics to stratify patients prescribed opioids based on risk for overdose/suicide. OBJECTIVE: To evaluate the impact of the case review mandate on serious adverse events (SAEs) and all-cause mortality among high-risk Veterans. DESIGN: A 23-month stepped-wedge cluster randomized controlled trial in all 140 VHA medical centers between 2018 and 2020. PARTICIPANTS: A total of 44,042 patients actively prescribed opioid analgesics with high STORM risk scores (i.e., percentiles 1% to 5%) for an overdose or suicide-related event. INTERVENTION: A mandate requiring providers to perform case reviews on opioid analgesic-prescribed patients at high risk of overdose/suicide. MAIN MEASURES: Nine serious adverse events (SAEs), case review completion, number of risk mitigation strategies, and all-cause mortality. KEY RESULTS: Mandated review inclusion was associated with a significant decrease in all-cause mortality within 4 months of inclusion (OR: 0.78; 95% CI: 0.65-0.94). There was no detectable effect on SAEs. Stepped-wedge analyses found that mandated review patients were five times more likely to receive a case review than non-mandated patients with similar risk (OR: 5.1; 95% CI: 3.64-7.23) and received more risk mitigation strategies than non-mandated patients (0.498; CI: 0.39-0.61). CONCLUSIONS: Among VHA patients prescribed opioid analgesics, identifying high risk patients and mandating they receive an interdisciplinary case review was associated with a decrease in all-cause mortality. Results suggest that providers can leverage predictive analytic-targeted population health approaches and interdisciplinary collaboration to improve patient outcomes. TRIAL REGISTRATION: ISRCTN16012111.

Randomized Policy Evaluation of the Veterans Health Administration Stratification Tool for Opioid Risk Mitigation (STORM).

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.

A genome-wide association study of suicide attempts in the million veterans program identifies evidence of pan-ancestry and ancestry-specific risk loci.

To identify pan-ancestry and ancestry-specific loci associated with attempting suicide among veterans, we conducted a genome-wide association study (GWAS) of suicide attempts within a large, multi-ancestry cohort of U.S. veterans enrolled in the Million Veterans Program (MVP). Cases were defined as veterans with a documented history of suicide attempts in the electronic health record (EHR; N = 14,089) and controls were defined as veterans with no documented history of suicidal thoughts or behaviors in the EHR (N = 395,064). GWAS was performed separately in each ancestry group, controlling for sex, age and genetic substructure. Pan-ancestry risk loci were identified through meta-analysis and included two genome-wide significant loci on chromosomes 20 (p = 3.64 × 10-9) and 1 (p = 3.69 × 10-8). A strong pan-ancestry signal at the Dopamine Receptor D2 locus (p = 1.77 × 10-7) was also identified and subsequently replicated in a large, independent international civilian cohort (p = 7.97 × 10-4). Additionally, ancestry-specific genome-wide significant loci were also detected in African-Americans, European-Americans, Asian-Americans, and Hispanic-Americans. Pathway analyses suggested over-representation of many biological pathways with high clinical significance, including oxytocin signaling, glutamatergic synapse, cortisol synthesis and secretion, dopaminergic synapse, and circadian rhythm. These findings confirm that the genetic architecture underlying suicide attempt risk is complex and includes both pan-ancestry and ancestry-specific risk loci. Moreover, pathway analyses suggested many commonly impacted biological pathways that could inform development of improved therapeutics for suicide prevention.

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.

Investigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach.

BACKGROUND: Healthcare systems monitor and improve mental health treatment quality, access, continuity and satisfaction through use of population-based and efficiency-based staffing models, the former focused on staffing ratios and the latter, staff productivity. Preliminary evidence suggests that both high staffing ratios and moderate-to-high staff productivity are important for ensuring a full continuum of mental health services to indicated populations. METHODS & FINDINGS: With an information-theoretic approach, we conducted a longitudinal investigation of mental health staffing, productivity and treatment at the largest integrated healthcare system in American, the Veterans Health Administration (VHA). VHA facilities (N = 140) served as the unit of measure, with mental health treatment quality, access, continuity and satisfaction predicted by facility staffing and productivity in longitudinal mixed models. An information-theoretic approach: (a) entails the development of a comprehensive set of plausible models that are fit, ranked and weighted to quantitatively assess the relative support for each, and (b) accounts for model uncertainty while identifying best-fit model(s) that include important and exclude unimportant explanatory variables. In best-fit models, higher staffing was the strongest and most consistent predictor of better treatment quality, access, continuity and satisfaction. Higher staff productivity was often, but not always associated with better treatment quality, access, continuity and satisfaction. Results were further nuanced by differential prediction of treatment by between- and within-facility predictor effects and variable interactions. CONCLUSIONS: A population-based mental health staffing ratio and an efficiency-based productivity value are important longitudinal predictors of mental health treatment quality, access, continuity and satisfaction. Our longitudinal design and use of mixed regression models and an information-theoretic approach addresses multiple limitations of prior studies and strengthen our results. Results are discussed in terms of the provision of mental health treatment by healthcare systems, and analytical modeling of treatment quality, access, continuity and satisfaction.

Impact of treatment duration on mortality among Veterans with opioid use disorder in the United States Veterans Health Administration.

BACKGROUND AND AIMS: While long-term medication-assisted treatment (MAT) using methadone or buprenorphine is associated with significantly lower all-cause mortality for individuals with opioid use disorder (OUD), periods of initiating or discontinuing treatment are associated with higher mortality risks relative to stable treatment. This study aimed to identify the OUD treatment durations necessary for the elevated mortality risks during treatment transitions to be balanced by reductions in mortality while receiving treatment. DESIGN: Simulation model based on a compartmental model of OUD diagnosis, MAT receipt and all-cause mortality among Veterans with OUD in the United States Veterans Health Administration (VA) in 2017-2018. We simulated methadone and buprenorphine treatments of varying durations using parameters obtained through calibration and published meta-analyses of studies from North America, Europe and Australia. SETTING: United States. PARTICIPANTS: Simulated cohorts of 10 000 individuals with OUD. MEASUREMENTS: All-cause mortality over 12 months. FINDINGS: Receiving methadone for 4 months or longer or buprenorphine for 2 months or longer resulted in 54 [95% confidence interval (CI) = 5-90] and 65 (95% CI = 21-89) fewer deaths relative to not receiving MAT for the same duration, using VA-specific mortality rates. We estimated shorter treatment durations necessary to achieve net mortality benefits of 2 months or longer for methadone and 1 month or longer for buprenorphine, using non-VA population literature estimates. Sensitivity analyses demonstrated that necessary treatment durations increased more with smaller mortality reductions on treatment than with larger relative risks during treatment transitions. CONCLUSIONS: Short periods (< 6 months) of treatment with either methadone or buprenorphine are likely to yield net mortality benefits for people with opioid use disorder relative to receiving no medications, despite periods of elevated all-cause mortality risk during transitions into and out of treatment. Retaining people with opioid use disorder in treatment longer can increase these benefits.

Efficacy of motivational-interviewing and guided opioid tapering support for patients undergoing orthopedic surgery (MI-Opioid Taper): A prospective, assessor-blind, randomized controlled pilot trial.

BACKGROUND: Postoperative opioid use can lead to chronic use and misuse. Few studies have examined effective approaches to taper postoperative opioid use while maintaining adequate analgesia. METHODS: This randomized, assessor-blinded, pilot trial of postoperative motivational interviewing and guided opioid tapering support (MI-Opioid Taper) added to usual care (UC) enrolled patients undergoing total hip or knee arthroplasty at a single U.S. academic medical center. MI-Opioid Taper involved weekly (to seven weeks) and monthly (to one year) phone calls until patient-reported opioid cessation. Opioid tapering involved 25% weekly dose reductions. The primary feasibility outcome was study completion in the group to which participants were randomized. The primary efficacy outcome, time to baseline opioid use, was the first of five consecutive days of return to baseline preoperative dose. Intention-to-treat analysis with Cox proportional hazards regression was adjusted for operation. ClinicalTrials.gov registration: NCT02070003. FINDINGS: From November 26, 2014, to April 27, 2018, 209 patients were screened, and 104 patients were assigned to receive MI-Opioid Taper (49 patients) or UC only (55 patients). Study completion after randomization was similar between groups (96.4%, 53 patients receiving UC, 91.8%, 45 patients receiving MI-Opioid Taper). Patients receiving MI-Opioid Taper had a 62% increase in the rate of return to baseline opioid use after surgery (HR 1.62; 95%CI 1.06-2.46; p = 0•03). No trial-related adverse events occurred. INTERPRETATION: In patients undergoing total joint arthroplasty, MI-Opioid Taper is feasible and future research is needed to establish the efficacy of MI-Opioid Taper to promote postoperative opioid cessation. FUNDING: National Institute on Drug Abuse.

Tracking implementation strategies in the randomized rollout of a Veterans Affairs national opioid risk management initiative.

BACKGROUND: In 2018, the Department of Veterans Affairs (VA) issued Notice 2018-08 requiring facilities to complete "case reviews" for Veterans identified in the Stratification Tool for Opioid Risk Mitigation (STORM) dashboard as high risk for adverse outcomes among patients prescribed opioids. Half of the facilities were randomly assigned to a Notice version including additional oversight. We evaluated implementation strategies used, whether strategies differed by randomization arm, and which strategies were associated with case review completion rates. METHODS: Facility points of contact completed a survey assessing their facility's use of 68 implementation strategies based on the Expert Recommendations for Implementing Change taxonomy. We collected respondent demographic information, facility-level characteristics, and case review completion rates (percentage of high-risk patients who received a case review). We used Kruskal-Wallis tests and negative binomial regression to assess strategy use and factors associated with case reviews. RESULTS: Contacts at 89 of 140 facilities completed the survey (64%) and reported using a median of 23 (IQR 16-31) strategies. The median case review completion rate was 71% (IQR 48-95%). Neither the number or types of strategies nor completion rates differed by randomization arm. The most common strategies were using the STORM dashboard (97%), working with local opinion leaders (80%), and recruiting local partners (80%). Characteristics associated with case review completion rates included respondents being ≤ 35 years old (incidence rate ratio, IRR 1.35, 95% CI 1.09-1.67) and having < 5 years in their primary role (IRR 1.23; 95% CI 1.01-1.51), and facilities having more prior academic detailing around pain and opioid safety (IRR 1.40, 95% CI 1.12-1.75). Controlling for these characteristics, implementation strategies associated with higher completion rates included (1) monitoring and adjusting practices (adjusted IRR (AIRR) 1.40, 95% CI 1.11-1.77), (2) identifying adaptations while maintaining core components (AIRR 1.28, 95% CI 1.03-1.60), (3) conducting initial training (AIRR 1.16, 95% CI 1.02-1.50), and (4) regularly sharing lessons learned (AIRR 1.32, 95% CI 1.09-1.59). CONCLUSIONS: In this national evaluation of strategies used to implement case reviews of patients at high risk of opioid-related adverse events, point of contact age and tenure in the current role, prior pain-related academic detailing at the facility, and four specific implementation strategies were associated with case review completion rates, while randomization to additional centralized oversight was not. TRIAL REGISTRATION: This project is registered at the ISRCTN Registry with number ISRCTN16012111. The trial was first registered on May 3, 2017.

Using patient-reported outcome measures for program evaluation: Design and findings on intention-to-treat outcomes from the Veterans Outcome Assessment survey.

The Veterans Outcomes Assessment (VOA) program surveys Veteran Health Administration (VHA) patients when they begin mental health treatment and at follow-up at three months to obtain patient-reported outcomes measures (PROM). It complements VA's evolving program in measurement-based care by providing additional data that can be useful for program evaluation including assessments of patients who have not been seen for ongoing mental health care. In principle, it provides data on intention-to-treat outcomes for program evaluation to complement the outcomes for patients who are receiving ongoing treatment that can be derived from measurement-based care. VOA findings confirm differences in outcomes between patients who have continued to be seen for treatment and those who have not. Patients in general mental health clinics with no encounters between the baseline and follow-up assessments who reported discontinuing care because they did not want or need treatment improved more, and those who discontinued due to problems improved less than those who remained in treatment. Experience with VOA has identified a number of issues that must be addressed before it is possible to use intention-to-treat outcomes for program evaluation.

Associations between stopping prescriptions for opioids, length of opioid treatment, and overdose or suicide deaths in US veterans: observational evaluation.

OBJECTIVE: To examine the associations between stopping treatment with opioids, length of treatment, and death from overdose or suicide in the Veterans Health Administration. DESIGN: Observational evaluation. SETTING: Veterans Health Administration. PARTICIPANTS: 1 394 102 patients in the Veterans Health Administration with an outpatient prescription for an opioid analgesic from fiscal year 2013 to the end of fiscal year 2014 (1 October 2012 to 30 September 2014). MAIN OUTCOME MEASURES: A multivariable Cox non-proportional hazards regression model examined death from overdose or suicide, with the interaction of time varying opioid cessation by length of treatment (≤30, 31-90, 91-400, and >400 days) as the main covariates. Stopping treatment with opioids was measured as the time when a patient was estimated to have no prescription for opioids, up to the end of the next fiscal year (2014) or the patient's death. RESULTS: 2887 deaths from overdose or suicide were found. The incidence of stopping opioid treatment was 57.4% (n=799 668) overall, and based on length of opioid treatment was 32.0% (≤30 days), 8.7% (31-90 days), 22.7% (91-400 days), and 36.6% (>400 days). The interaction between stopping treatment with opioids and length of treatment was significant (P<0.001); stopping treatment was associated with an increased risk of death from overdose or suicide regardless of the length of treatment, with the risk increasing the longer patients were treated. Hazard ratios for patients who stopped opioid treatment (with reference values for all other covariates) were 1.67 (≤30 days), 2.80 (31-90 days), 3.95 (91-400 days), and 6.77 (>400 days). Descriptive life table data suggested that death rates for overdose or suicide increased immediately after starting or stopping treatment with opioids, with the incidence decreasing over about three to 12 months. CONCLUSIONS: Patients were at greater risk of death from overdose or suicide after stopping opioid treatment, with an increase in the risk the longer patients had been treated before stopping. Descriptive data suggested that starting treatment with opioids was also a risk period. Strategies to mitigate the risk in these periods are not currently a focus of guidelines for long term use of opioids. The associations observed cannot be assumed to be causal; the context in which opioid prescriptions were started and stopped might contribute to risk and was not investigated. Safer prescribing of opioids should take a broader view on patient safety and mitigate the risk from the patient's perspective. Factors to address are those that place patients at risk for overdose or suicide after beginning and stopping opioid treatment, especially in the first three months.

Changing Trends in Opioid Overdose Deaths and Prescription Opioid Receipt Among Veterans.

INTRODUCTION: To inform overdose prevention, this study assessed both recent trends in opioid overdose mortality across opioid categories and receipt of prescription opioid analgesics among Veterans who died from overdose in the Veterans Health Administration. METHODS: Using Veterans Health Administration records linked to National Death Index data, annual cohorts (2010-2016) of Veterans who received Veterans Health Administration care were obtained and were examined by opioid overdose categories (natural/semisynthetic opioids, heroin, methadone, and other synthetic opioids) on (1) overdose rates and changes in rates adjusted for age, sex, and race/ethnicity; and (2) Veterans Health Administration prescription opioid receipt. Analyses were conducted in 2018. RESULTS: The overall rate of opioid overdose among Veterans increased from 14.47 per 100,000 person-years in 2010 to 21.08 per 100,000 person-years in 2016 (adjusted rate ratio=1.65, 95% CI=1.51, 1.81). There was a decline in methadone overdose (adjusted rate ratio=0.66, 95% CI=0.51, 0.84) and no significant change in natural/semisynthetic opioid overdose (adjusted rate ratio=1.08, 95% CI=0.94, 1.24). However, the synthetic opioid overdose rate (adjusted rate ratio=5.46, 95% CI=4.41, 6.75) and heroin overdose rate (adjusted rate ratio=4.91, 95% CI=3.92, 6.15) increased substantially. Among all opioid overdose decedents, prescription opioid receipt within 3 months before death declined from 54% in 2010 to 26% in 2016. CONCLUSIONS: Opioid overdose rates among Veterans Health Administration Veterans increased because of increases in heroin and synthetic opioid overdose rates. Prescriptions of opioids declined among patients who died from all categories of opioid overdose; by 2016, only a minority received an opioid analgesic from Veterans Health Administration within 3 months of overdose. Future prevention efforts should extend beyond patients actively receiving opioid prescriptions.

Randomized program evaluation of the Veterans Health Administration Stratification Tool for Opioid Risk Mitigation (STORM): A research and clinical operations partnership to examine effectiveness.

The United States is facing an opioid crisis in which overdose is the leading cause of injury death-misuse of opioids constitutes the vast majority of those deaths. In 2016 alone, over 42,000 people died from opioid overdose, an increase of 27% from the prior year. Deployment of the Stratification Tool for Opioid Risk Mitigation (STORM), a clinical decision support tool to improve opioid safety, is one response by the Veterans Health Administration (VHA) to the opioid crisis. STORM identifies VHA patients at very high risk of opioid-related adverse events and lists potential risk mitigation strategies. Deployment of STORM also helps VHA meet certain requirements of the Comprehensive Addiction and Recovery Act of 2016. In alignment with the VHA's learning health care system initiative, a multidisciplinary team designed a randomized evaluation of a policy approach to mandating case reviews of very-high-risk patients identified by STORM and the impacts of patient inclusion versus exclusion in mandated STORM case reviews using a stepped-wedge design. The STORM evaluation involves drafting the policy notice, shepherding it through the VHA approval process, and implementing the cluster randomized design. This mixed-methods evaluation includes (1) a qualitative assessment of medical center implementation strategies with the aim of understanding of how STORM is incorporated into practice, and (2) quantitative analyses of the relations between policy mandates and STORM inclusion on opioid-related adverse events. The findings from this synergistic research design will yield critical insights for VHA leadership to refine opioid prescribing-related policy and practice.

Mental Health Treatment Quality, Access, and Satisfaction: Optimizing Staffing in an Era of Fiscal Accountability.

OBJECTIVE: Mental health treatment access and quality are influenced by the interplay of structural, organizational, and performance factors-including the number of mental health staff providing direct clinical care relative to patients treated (i.e., staffing ratio), mental health staff productivity, and wait times for scheduled mental health appointments. With no industry standards to follow, the Veterans Health Administration (VHA) developed an outpatient mental health staffing model and a recommended minimum total staffing ratio. METHODS: At the level of VHA health care facility (N=140), we conducted cross-sectional regression analyses to examine the relative importance of outpatient mental health staffing and productivity and mental health patient wait times in predicting measures of mental health treatment access and quality. RESULTS: Outpatient mental health staffing ratios (especially total and therapist staffing ratios) had substantial, positive relationships with overall mental health treatment access and quality, broadly and in specific domains. Staffing ratios generally had stronger relationships with treatment access and quality than did staff productivity and patient wait times. CONCLUSIONS: Mental health staffing ratios should be a primary consideration when trying to improve mental health treatment access and quality at the facility level. Having more mental health staff of all types is associated with better overall access to and quality of mental health services, and multiple staff types are needed to provide high-quality mental health care. Knowledge gained may guide efforts to address challenges in improving access to and quality of mental health services within and outside of VHA.