Mining clinical data for novel medications to treat alcohol use disorder.

BACKGROUND: Alcohol use disorder (AUD) is a highly prevalent and often debilitating condition associated with high morbidity and mortality. Current AUD medications have limited efficacy and uptake. Alternative pharmacological options are needed. METHODS: We constructed a mechanistic tree of all US Food and Drug Administration approved medications and used a tree-based scan statistic, TreeScan, to identify medications associated with greater than expected improvements in alcohol consumption. Our cohort included all United States (US) Department of Veterans Affairs (VA) patients with a diagnosis of AUD between 10/1/1999 and 9/30/2019 with multiple Alcohol Use Disorders Identification Test-Consumption Module scores within the VA electronic health record data. RESULTS: Medications statistically associated with decreased alcohol consumption had, at large, minor effect sizes. Medications used in the treatment of chronic or life-threatening conditions like diabetes, chronic kidney disease, hepatitis C virus, or cancer produced larger effect sizes. Asenapine, an atypical antipsychotic, had a large effect with an observed to expected ratio of 1.78 (p = 0.003). Our findings were replicated in a propensity score matched population. CONCLUSION: Most medications significantly associated with decreased alcohol consumption in our analysis were either contraindicated with alcohol or likely attributable to patients abstaining from alcohol due to severe illness. However, the large effect of asenapine is notable, and a worthwhile candidate for more careful analysis.

Development of Health Professions Education Competencies for a National Fellowship Program: A Group Consensus Process.

ABSTRACT: Health professions educators need knowledge, skills, and attitudes to provide high-quality education within dynamic clinical learning environments. Although postgraduate training opportunities in health professions education (HPE) have increased significantly, no shared competencies exist across the field. This article describes the systematic development of postgraduate HPE competencies for the Health Professions Education, Evaluation, and Research (HPEER) Advanced Fellowship, a 2-year, interprofessional, post-master's degree and postdoctoral HPE training program funded through the Department of Veterans Affairs' Office of Academic Affiliations. Using a modified RAND/University of California at Los Angeles Appropriateness Method, the authors developed competencies from March 2021 to August 2021 that were informed by current practices and standards in HPE. Literature reviews were conducted of published literature from November 2020 to February 2021 and gray literature from February to March 2021, identifying 78 and 274 HPE training competencies, respectively. These competencies were combined with 71 competencies submitted by program faculty from 6 HPEER fellowship sites, resulting in 423 initial competencies. Competencies were organized into 6 primary domains and condensed by deleting redundant items and combining overlapping concepts. Eight subject matter experts completed 3 Delphi surveys and met during 2 nominal group technique meetings. The final 25 competencies spanned 6 domains: teaching methods and learning theories; educational assessment and program evaluation; educational research methods; diversity, equity, and inclusion; interprofessional practice and team science; and leadership and management. In addition to informing the national HPEER curriculum, program evaluation, and learner assessment, these advanced competencies describe the knowledge, skills, and attitudes health professions educators need to provide high-quality education with an emphasis on the global and societal impact of HPE. These competencies represent a step toward leveraging HPE expertise to establish competencies to drive HPE program changes. Other programs should report their competencies and competency development processes to spur further dialog and progress.

Pilot randomized controlled trial of a brief strategy to prevent suicide after discharge from residential addiction treatment.

INTRODUCTION: Veterans are at greater risk for suicide and veterans with substance use disorder (SUD) have an even greater risk. Little research has looked into brief interventions to prevent suicide in this population in residential substance use treatment programs. METHOD: We conducted a pilot, randomized controlled trial of a brief suicide prevention strategy called Veterans Affairs Brief Intervention and Contact Program (VA BIC) in patients participating in the Residential Recovery Center (RRC) SUD 28-day program and deemed at risk for suicide. We measured changes in symptoms at 1-, 3-, and 6-months. We looked at social connectedness, suicidal ideation, hopelessness, thwarted belongingness, perceived burdensomeness, and treatment engagement. RESULTS: The study enrolled twenty patients. One participant withdrew immediately after baseline. We found that adherence to VA BIC components was high, as 100 % of patients (N = 10) completed 70 % or more of the VA BIC visits. Furthermore, 80 % of intervention group patients (N = 8) completed all VA BIC components. During the six-month follow-up, suicidal ideation improved in patients assigned to VA BIC, while it worsened in the standard care arm. Similarly, patients assigned to VA BIC reported a reduction in perceived burdensomeness over the six-month follow-up period while it worsened in the standard care arm. Additionally, VA BIC may modestly improve treatment engagement in the first month postdischarge. CONCLUSION: We were able to recruit and enroll patients from a residential SUD treatment program into a clinical trial of the VA BIC intervention. Our preliminary results suggest that VA BIC may be useful in reducing suicidal ideation and perceived burdensomeness in patients who are discharged from residential SUD treatment programs and increasing treatment engagement. Future trials of VA BIC should determine whether VA BIC can reduce the risk of suicide in patients who are discharged from residential SUD treatment programs.

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.

Current Programs and Incentives to Overcome Rural Physician Shortages in the United States: A Narrative Review.

Access to healthcare continues to be a top priority and prominent challenge in rural communities, with 20% of the total U.S. population living in rural areas while only 10% of physicians practice in rural areas. In response to physician shortages, a variety of programs and incentives have been implemented to recruit and retain physicians in rural areas; however, less is known about the types and structures of incentives that are offered in rural areas and how that compares to physician shortages. The purpose of our study is to conduct a narrative review of the literature to identify and compare current incentives that are offered by rural physician shortage areas to better understand how resources are being allocated to vulnerable areas. We reviewed published peer-reviewed articles from 2015-2022 to identify incentives and programs designed to address physician shortages in rural areas. We augment that review by examining the gray literature, including reports and white papers on the topic. Identified incentive programs were aggregated for comparison and translated into a map that depicts high, medium, and low levels of geographically designated Health Professional Shortage Areas (HPSAs) and the number of incentives offered by state. Surveying current literature regarding different types of incentivization strategies while comparing to primary care HPSAs provides general insights on the potential influence of incentive programs on shortages, allows easy visual review, and may provide greater awareness of available support for potential recruits. Providing a broad overview of the incentives offered in rural areas will help illuminate whether diverse and appealing incentives are offered in the most vulnerable areas and guide future efforts to address these issues.

An Analysis of Irregular Discharges From Residential Treatment Programs in the Department of Veterans Affairs Health Care System.

INTRODUCTION: Veteran populations are frequently diagnosed with mental health conditions such as substance use disorder and PTSD. These conditions are associated with adverse outcomes including a higher risk of suicide. The Veterans Health Administration (VHA) has designed a robust mental health system to address these concerns. Veterans can access mental health treatment in acute inpatient, residential, and outpatient settings. Residential programs play an important role in meeting the needs of veterans who need more structure and support. Residential specialty types in the VHA include general mental health, substance use disorder, PTSD, and homeless/work programs. These programs are affiliated with a DVA facility (i.e., medical center). Although residential care can improve outcomes, there is evidence that some patients are discharged from these settings before achieving the program endpoint. These unplanned discharges are referred to using language such as against medical advice, self-discharge, or irregular discharge. Concerningly, unplanned discharges are associated with patient harm including death by suicide. Although there is some initial evidence to locate factors that predict irregular discharge in VHA residential programs, no work has been done to examine features associated with irregular discharge in each residential specialty. METHODS: We conducted a retrospective cohort study of patients who were discharged from VHA residential treatment programs between January 2018 and September 2022. We included the following covariates: Principal diagnosis, gender, age, race/ethnicity, number of physical health conditions, number of mental health diagnostic categories, marital status, risk of homelessness, urbanicity, and service connection. We considered two discharge types: Regular and irregular. We used logistic regression to determine the odds of irregular discharge using models stratified by bed specialty as well as combined odds ratios and 95% CIs across program specialties. The primary purposes are to identify factors that predict irregular discharge and to determine if the factors are consistent across bed specialties. In a secondary analysis, we calculated facility-level adjusted rates of irregular discharge, limiting to facilities with at least 50 discharges. We identified the amount of residual variation that exists between facilities after adjusting for patient factors. RESULTS: A total of 279 residential programs (78,588 patients representing 124,632 discharges) were included in the analysis. Substance use disorder and homeless/work programs were the most common specialty types. Both in the overall and stratified analyses, the number of mental health diagnostic categories and younger age were predictors of irregular discharge. In the facility analysis, there was substantial variation in irregular discharge rates across residential specialties even after adjusting for all patient factors. For example, PTSD programs had a mean adjusted irregular discharge rate of 15.3% (SD: 7.4; range: 2.1-31.2; coefficient of variation: 48.4%). CONCLUSIONS: Irregular discharge is a key concern in VHA residential care. Patient characteristics do not account for all of the observed variation in rates across residential specialty types. There is a need to develop specialty-specific measures of irregular discharge to learn about system-level factors that contribute to irregular discharge. These data can inform strategies to avoid harms associated with irregular discharge.

Rural-urban trends in health care utilization, treatment, and mortality among US veterans with congestive heart failure: A retrospective cohort study.

PURPOSE: To compare longitudinal rates of health care utilization, evidence-based treatment, and mortality between rural and urban-dwelling patients with congestive heart failure (CHF). METHODS: We used electronic medical record data from the Veterans Health Administration (VHA) to identify adult patients with CHF from 2012 through 2017. We stratified our cohort using left ventricular ejection fraction percentage at diagnosis (<40% = reduced ejection fraction [HFrEF]; 40%-50% = midrange ejection fraction [HFmrEF]; >50% = preserved ejection fraction [HFpEF]). Within each ejection fraction cohort, we stratified patients into rural or urban groups. We used Poisson regression to estimate annual rates of health care utilization and CHF treatment. We used Fine and Gray regression to estimate annual hazards of CHF and non-CHF mortality. FINDINGS: One-third of patients with HFrEF (N = 37,928/109,110), HFmrEF (N = 24,447/68,398), and HFpEF (N = 39,298/109,283) resided in a rural area. Rural compared to urban patients used VHA facilities at similar or lower annual rates for outpatient specialty care across all ejection fraction cohorts. Rural patients used VHA facilities at similar or higher rates for primary care and telemedicine-delivered specialty care. They also had lower and declining rates of VHA inpatient and urgent care use over time. There were no meaningful rural-urban differences in treatment receipt among patients with HFrEF. On multivariable analysis, the rate of CHF and non-CHF mortality was similar between rural and urban patients in each ejection fraction cohort. CONCLUSIONS: Our findings suggest the VHA may have mitigated access and health outcome disparities typically observed for rural patients with CHF.

The efficacy and safety of buprenorphine for the treatment of depression: A systematic review and meta-analysis.

BACKGROUND: Depressive disorders are common. Many patients with major depression do not achieve remission with available treatments. Buprenorphine has been raised as a potential treatment for depression as well as suicidal behavior but may pose certain risks. METHODS: A meta-analysis comparing the efficacy, tolerability, and safety of buprenorphine (or combinations such as buprenorphine/samidorphan) versus control in improving symptoms in patients with depression. Medline, Cochrane Database, PsycINFO, Excerpta Medica Database and The Cumulative Index to Nursing and Allied Health Literature were searched from inception through January 2, 2022. Depressive symptoms were pooled using Hedge's g with 95% Confidence Intervals (CI). Tolerability, safety, suicide outcomes were summarized qualitatively. RESULTS: 11 studies (N = 1699) met inclusion criteria. Buprenorphine had a small effect on depressive symptoms (Hedges' g 0.17, 95%CI: 0.05-0.29). Results were driven by six trials of buprenorphine/samidorphan (N = 1,343, Hedges's g 0.17, 95%CI: 0.04-0.29). One study reported significant improvement in suicidal thoughts (Least Squares Mean Change: -7.1, 95%CI: -12.0 - 2.3). Most studies found buprenorphine was well-tolerated with no evidence of abuse behavior or dependency. CONCLUSIONS: Buprenorphine may have a small benefit for depressive symptoms. Future research should clarify the dose response relationship between buprenorphine and depression.

Are suicide risk scales sensitive to change? A scoping review.

INTRODUCTION: Clinician- or self-administered scales are frequently used to assist in detecting risk of death by suicide and to determine the effectiveness of interventions. No recent review studies have examined whether these scales are sensitive to change. We conducted a scoping review to identify suicide risk scales that are sensitive to change. MATERIAL AND METHODS: We searched Medline and Excerpta Medica Database from inception through March 17, 2022, to identify randomized trials, pooled analysis, quasi-experimental studies, and cohort studies reporting on sensitivity to change of suicide risk scales. We assessed sensitivity to change by examining internal and external responsiveness. Internal responsiveness evaluates whether the scale measures changes in suicide-related symptoms in response to an intervention while external responsiveness assess whether changes in the scale correspond to changes in risk of suicide. We summarized findings across studies using descriptive analysis. RESULTS: Among 38 eligible scales, we identified 27 scales that included items that were modifiable to change. However, only 7 scales had been studied to determine their sensitivity to change based on internal or external responsiveness. While the results of studies suggested that 6 scales have internal responsiveness, none of the included studies confirmed that scales have external responsiveness. DISCUSSION: A few suicide risk scales are internally responsive and may be useful in a clinical or research setting. It is unclear, however, whether changes in scores correspond to an actual change in suicide risk. Future research should confirm the external responsiveness of scales using robust metrics including suicide mortality.

A comparison of mortality rates for buprenorphine versus methadone treatments for opioid use disorder.

OBJECTIVE: Mortality from opioid use disorder (OUD) can be reduced for patients who receive opioid agonist treatment (OAT). In the United States (US), OATs have different requirements including nearly daily visits to a dispensing facility for methadone but weekly to monthly prescriptions for buprenorphine. Our objective was to compare mortality rates for buprenorphine and methadone treatments among a large sample of US patients with OUD. METHODS: We measured all-cause mortality, overdose mortality, and suicide mortality among US Department of Veterans Affairs patients with a diagnosis of OUD who received OAT from 2010 through 2019. We leveraged substantial and sustained regional variation in prescribing buprenorphine versus methadone as an instrumental variable (IV) and used inverse propensity of treatment weighting to balance relevant covariates across treatment groups. We compared mortality with true two-stage IV using both probit and linear probability models, as well as a reduced form IV model, adjusting for demographics and health status. RESULTS: Our cohort consisted of 61,997 patients with OUD who received OAT, of whom 92.7% were male with a mean age of 47.9 (SD = 14.1) years. Patients were followed for a median of 2 (IQR = 1,4) calendar years. Across regional terciles, mean methadone prescribing was 4.8%, 19.5%, and 75.1% of OAT patients. All models identified significant reductions in all-cause and suicide mortality for buprenorphine relative to methadone. For example, predicted all-cause mortality from the probit model was 169.7 per 10,000 person years (95% CI, 157.8, 179.6) in the lowest tercile of methadone prescribing compared with 206.1 (95% CI, 196.0, 216.3) in the highest tercile. No difference was identified for overdose mortality. CONCLUSION: We found significantly lower all-cause mortality and suicide mortality rates for buprenorphine compared with methadone. Our results support the less restrictive prescribing practices for buprenorphine as OAT in the US.

Examination of increasing suicide rates among rural Hispanic VA patients.

PURPOSE: Death by suicide is increasing more rapidly among Hispanics than non-Hispanics who use United States Department of Veterans Affairs (VA) health services, and the increase is most rapid among those living in rural areas. Our goal was to identify characteristics of rural Hispanic VA patients that contribute to this emerging disparity. METHODS: We linked electronic medical records from the VA, personnel data from the US Department of Defense, mortality data from the US National Death Index, and data on area characteristics from the US Census Bureau to examine suicide trends among Hispanic VA patients from 2005 through 2019. After identifying the strongest predictors of suicide in the rural and urban Hispanic populations, we examined how those characteristics changed over time. FINDINGS: Age and sex-adjusted suicide mortality rates were consistently higher for rural versus urban Hispanic patients beginning in 2012, with the most recent rolling 5-year average rates being 31.0 per 100,000 for rural compared to 20.3 per 100,000 for urban in 2019. Models to predict suicide had fair performance in the rural (accuracy = 0.62, 95% CI: 0.51, 0.73) and urban (accuracy = 0.67, 95% CI: 0.63, 0.70) groups. Mental health diagnoses were predictive of suicide among rural Hispanic patients, but there was no evidence that mental health diagnoses were increasing more rapidly in rural compared to urban patients. CONCLUSIONS: While we confirmed that there is a higher rate of death by suicide among rural Hispanic VA patients relative to their urban counterparts, we were unable to identify clear drivers of this finding.

Tools to Detect Risk of Death by Suicide: A Systematic Review and Meta-Analysis.

Objective: There is limited knowledge about the ability of instruments to detect risk of suicide in a range of settings. Prior reviews have not considered whether the utility of instruments depends on prior probability of risk. We performed a systematic review to determine the diagnostic accuracy of instruments to detect risk of suicide in adults using likelihood ratio analysis. This method aids evaluation of prior probabilities of risk.Data Sources: We searched MEDLINE, Cochrane Database of Systematic Reviews, PsycINFO, EMBASE, and Scopus from inception through January 19, 2021.Study Selection: We included clinical trials, observational studies, and quasi-experimental studies assessing the diagnostic accuracy of instruments to detect risk of suicide in adults. There were no language restrictions.Data Extraction: Three reviewers in duplicate assessed full texts to determine eligibility and extracted data from included studies. Positive (LR+) and negative likelihood ratio (LR-) and 95% CIs were calculated for each instrument.Results: Thirty studies met inclusion criteria. Most instruments showed minimal utility to detect or rule out risk of suicide, with LR+ ≤ 2.0 and LR- ≥ 0.5. A few instruments had a high utility for improving risk detection in emergency department, inpatient mental health, and prison settings when patients scored above the cutoff (LR+ > 10). For example, among patients discharged from an emergency department, the Columbia Suicide Severity Rating Scale-Clinical Practice Screener had a LR+ of 10.3 (95% CI, 6.3-16.8) at 3-month follow-up. The clinical utility of the instruments depends on the pretest probability of suicide in the setting. Because studies spanned over 6 decades, the findings are at risk for secular trends.Discussion: We identified several instruments that may hold promise for detecting risk of suicide in emergency department, inpatient mental health, or prison settings. The utility of the instrument hinges, in part, on baseline suicide risk.Registration: PROSPERO: CRD42021285528.

Lithium in the prevention of suicide in adults: systematic review and meta-analysis of clinical trials.

Controversy exists regarding the efficacy of lithium for suicide prevention. Except for a recent trial that enrolled over 500 patients, available trials of lithium for suicide prevention have involved small samples. It is challenging to measure suicide in a single randomised controlled trial (RCT). Adding a single large study to existing meta-analyses may provide insights into lithium's anti-suicidal effects. We performed a meta-analysis of RCTs comparing lithium with a control condition for suicide prevention. MEDLINE and other databases were searched up to 30 November 2021. Efficacy was assessed by calculating the summary Peto odds ratio (OR) and incidence rate ratio (IRR) with 95% confidence intervals. Among seven RCTs, the odds of suicide were lower among patients receiving lithium versus control (OR = 0.30, 95% CI 0.09-1.02; IRR = 0.22, 95% CI 0.05-1.05), although the findings were still not statistically significant. The role of lithium in suicide prevention remains uncertain.

Changes in Alcohol Consumption following Direct-Acting Antiviral Treatment for Hepatitis C in VA Patients with Comorbid Alcohol Use Disorder and PTSD.

OBJECTIVE: To investigate whether direct-acting antivirals (DAA) for hepatitis C viral infection (HCV): glecaprevir/pibrentasvir (GLE/PIB), ledipasvir/sofosbuvir (LDV/SOF), and sofosbuvir/velpatasvir (SOF/VEL) are associated with reduced alcohol consumption among veterans with alcohol use disorder (AUD) and co-occurring post-traumatic stress disorder (PTSD). METHODS: We measured change in Alcohol Use Disorder Identification Test-Consumption Module (AUDIT-C) scores in a retrospective cohort of veterans with PTSD and AUD receiving DAAs for HCV. RESULTS: One thousand two hundred and eleven patients were included (GLE/PIB n = 174, LDV/SOF n = 808, SOF/VEL n = 229). Adjusted frequencies of clinically meaningful improvement were 30.5% for GLE/PIB, 45.5% for LDV/SOF, and 40.5% for SOF/VEL. The frequency was lower for GLE/PIB than for LDV/SOF (OR = 0.59; 95% CI [0.40, 0.87]) or SOF/VEL (OR = 0.66; 95% CI [0.42, 1.04]). CONCLUSIONS: DAA treatment for HCV was associated with a substantial reduction in alcohol use in patients with AUD and co-occurring PTSD. Further exploration of the role of DAAs in AUD treatment is warranted.

Association between post-traumatic stress disorder severity and death by suicide in US military veterans: retrospective cohort study.

BACKGROUND: There is mixed evidence regarding the direction of a potential association between post-traumatic stress disorder (PTSD) and suicide mortality. AIMS: This is the first population-based study to account for both PTSD diagnosis and PTSD symptom severity simultaneously in the examination of suicide mortality. METHOD: Retrospective study that included all US Department of Veterans Affairs (VA) patients with a PTSD diagnosis and at least one symptom severity assessment using the PTSD Checklist (PCL) between 1 October 1999 and 31 December 2018 (n = 754 197). We performed multivariable proportional hazards regression models using exposure groups defined by level of PTSD symptom severity to estimate suicide mortality rates. For patients with multiple PCL scores, we performed additional models using exposure groups defined by level of change in PTSD symptom severity. We assessed suicide mortality using the VA/Department of Defense Mortality Data Repository. RESULTS: Any level of PTSD symptoms above the minimum threshold for symptomatic remission (i.e. PCL score >18) was associated with double the suicide mortality rate at 1 month after assessment. This relationship decreased over time but patients with moderate to high symptoms continued to have elevated suicide rates. Worsening PTSD symptoms were associated with a 25% higher long-term suicide mortality rate. Among patients with improved PTSD symptoms, those with symptomatic remission had a substantial and sustained reduction in the suicide rate compared with those without symptomatic remission (HR = 0.56; 95% CI 0.37-0.88). CONCLUSIONS: Ameliorating PTSD can reduce risk of suicide mortality, but patients must achieve symptomatic remission to attain this benefit.

Leveraging unstructured electronic medical record notes to derive population-specific suicide risk models.

Electronic medical record (EMR)-based suicide risk prediction methods typically rely on analysis of structured variables such as demographics, visit history, and prescription data. Leveraging unstructured EMR notes may improve predictive accuracy by allowing access to nuanced clinical information. We utilized natural language processing (NLP) to analyze a large EMR note corpus to develop a data-driven suicide risk prediction model. We developed a matched case-control sample of U.S. Department of Veterans Affairs (VA) patients in 2015 and 2016. We randomly matched each case (all patients that died by suicide in that interval, n = 5029) with five controls (patients that remained alive). We processed note corpus using NLP methods and applied machine-learning classification algorithms to output. We calculated area under the curve (AUC) and risk tiers to determine predictive accuracy. NLP-derived models demonstrated strong predictive accuracy. Patients that scored within top 10% of risk model accounted for up to 29% of suicide decedents. NLP-derived model compares positively to other leading prediction methods. Our approach is highly implementable, only requiring access to text data and open-source software. Additional studies should evaluate ensemble models incorporating NLP-derived information alongside more typical structured variables.

Comparative Effectiveness of Direct-Acting Antivirals for Posttraumatic Stress Disorder in Veterans Affairs Patients With Hepatitis C Virus Infection.

We recently conducted an exploratory study that indicated that several direct-acting antivirals (DAAs), highly effective medications for hepatitis C virus (HCV) infection, were also associated with improvement in posttraumatic stress disorder (PTSD) among a national cohort of US Department of Veterans Affairs (VA) patients treated between October 1, 1999, and September 30, 2019. Limiting the same cohort to patients with PTSD and HCV, we compared the associations of individual DAAs with PTSD symptom improvement using propensity score weighting. After identifying patients who had available baseline and endpoint PTSD symptom data as measured with the PTSD Checklist (PCL), we compared changes over the 8-12 weeks of DAA treatment. The DAAs most prescribed in conjunction with PCL measurement were glecaprevir/pibrentasvir (GLE/PIB; n = 54), sofosbuvir/velpatasvir (SOF/VEL; n = 54), and ledipasvir/sofosbuvir (LDV/SOF; n = 145). GLE/PIB was superior to LDV/SOF, with a mean difference in improvement of 7.3 points on the PCL (95% confidence interval (CI): 1.1, 13.6). The mean differences in improvement on the PCL were smaller between GLE/PIB and SOF/VEL (3.0, 95% CI: -6.3, 12.2) and between SOF/VEL and LDV/SOF (4.4, 95% CI: -2.4, 11.2). While almost all patients were cured of HCV (92.5%) regardless of the agent received, PTSD outcomes were superior for those receiving GLE/PIB compared with those receiving LDV/SOF, indicating that GLE/PIB may merit further investigation as a potential PTSD treatment.

National cross-sectional cohort study of the relationship between quality of mental healthcare and death by suicide.

BACKGROUND: Patient safety-based interventions aimed at lethal means restriction are effective at reducing death by suicide in inpatient mental health settings but are more challenging in the outpatient arena. As an alternative approach, we examined the association between quality of mental healthcare and suicide in a national healthcare system. METHODS: We calculated regional suicide rates for Department of Veterans Affairs (VA) Healthcare users from 2013 to 2017. To control for underlying variation in suicide risk in each of our 115 mental health referral regions (MHRRs), we calculated standardised rate ratios (SRRs) for VA users compared with the general population. We calculated quality metrics for outpatient mental healthcare in each MHRR using individual metrics as well as an Overall Quality Index. We assessed the correlation between quality metrics and suicide rates. RESULTS: Among the 115 VA MHRRs, the age-adjusted, sex-adjusted and race-adjusted annual suicide rates varied from 6.8 to 92.9 per 100 000 VA users, and the SRRs varied between 0.7 and 5.7. Mean regional-level adherence to each of our quality metrics ranged from a low of 7.7% for subspecialty care access to a high of 58.9% for care transitions. While there was substantial regional variation in quality, there was no correlation between an overall index of mental healthcare quality and SRR. CONCLUSION: There was no correlation between overall quality of outpatient mental healthcare and rates of suicide in a national healthcare system. Although it is possible that quality was not high enough anywhere to prevent suicide at the population level or that we were unable to adequately measure quality, this examination of core mental health services in a well-resourced system raises doubts that a quality-based approach alone can lower population-level suicide rates.