Autonomy in work location decision and burnout in behavioral health providers: Lessons learned from COVID-19.

Objective: The ability to choose one's work-location can influence burnout from employment. We sought to evaluate potential associations between autonomy in work-location decision and burnout.

Methods: We used 2020 Veterans Health Administration Annual All Employee Survey data from behavioral health providers at 129 medical facilities.

Impact of lung cancer screening on stage migration and mortality among the national Veterans Health Administration population with lung cancer.

Background: Despite randomized trials demonstrating a mortality benefit to low-dose computed tomography screening to detect lung cancer, uptake of lung cancer screening (LCS) has been slow, and the benefits of screening remain unclear in clinical practice.

Methods: This study aimed to assess the impact of screening among patients in the Veterans Health Administration (VA) health care system diagnosed with lung cancer between 2011 and 2018. Lung cancer stage at diagnosis, lung cancer-specific survival, and overall survival between patients with cancer who did and did not receive screening before diagnosis were evaluated.

The Importance of Autonomy and Performance Goals in Perceived Workload Among Behavioral Health Providers.

Objective: The authors sought to assess workplace characteristics associated with perceived reasonable workload among behavioral health care providers in the Veterans Health Administration.

Methods: The authors evaluated perceived reasonable workload and workplace characteristics from the 2019 All Employee Survey (AES; N=14,824) and 2019 Mental Health Provider Survey (MHPS; N=10,490) and facility-level staffing ratios from Mental Health Onboard Clinical Dashboard data. Nine AES and 15 MHPS workplace predictors of perceived reasonable workload, 11 AES and six MHPS demographic predictors, and facility-level staffing ratios were included in mixed-effects logistic regression models.

Role of Institutional Support for Evidence-Based Psychotherapy in Satisfaction and Burnout Among Veterans Affairs Therapists.

Objective: Burnout is widespread among psychotherapists and leads to negative mental and other health outcomes, absenteeism, and turnover. Job resources, including institutional support for evidence-based practices, can buffer against burnout and may improve satisfaction among therapists. The Veterans Health Administration (VHA) is the nation's largest integrated health system and employs 23,000 therapists, including psychologists, social workers, and counselors.

Behavioral Health Provider Burnout and Mental Health Care in the Veterans Health Administration.

Background: Although many studies assess predictors of provider burnout, few analyses provide high-quality, consistent evidence on the impact of provider burnout on patient outcomes exist, particularly among behavioral health providers (BHPs).

Objective: To assess the impact of burnout among psychiatrists, psychologists, and social workers on access-related quality measures in the Veterans Health Administration (VHA).

Design: This study used burnout in VA All Employee Survey (AES) and Mental Health Provider Survey (MHPS) data to predict metrics assessed by the Strategic Analytics for Improvement and Learning Value, Mental Health Domain (MH-SAIL), VHA's quality monitoring system.

Characteristics of Facilities With Early and Rapid Ustekinumab Adoption for Patients With Inflammatory Bowel Disease.

Introduction: To examine which facility characteristics, including teamwork, are associated with early or rapid inflammatory bowel disease-related ustekinumab adoption.

Methods: We examined the association between ustekinumab adoption and the characteristics of 130 Veterans Affairs facilities.

Results: Mean ustekinumab adoption increased by 3.

Understanding clinician connections to inform efforts to promote high-quality inflammatory bowel disease care.

Background: Highly connected individuals disseminate information effectively within their social network. To apply this concept to inflammatory bowel disease (IBD) care and lay the foundation for network interventions to disseminate high-quality treatment, we assessed the need for improving the IBD practices of highly connected clinicians. We aimed to examine whether highly connected clinicians who treat IBD patients were more likely to provide high-quality treatment than less connected clinicians.

The Association Between Nonsteroidal Anti-Inflammatory Drug Use and Inflammatory Bowel Disease Exacerbations: A True Association or Residual Bias?

Introduction: Studies suggest that nonsteroidal anti-inflammatory drugs (NSAID) may contribute to inflammatory bowel disease (IBD) exacerbations. We examined whether variation in the likelihood of IBD exacerbations is attributable to NSAID.

Methods: In a cohort of patients with IBD (2004-2015), we used 3 analytic methods to examine the likelihood of an exacerbation after an NSAID exposure.

Reinforcement learning evaluation of treatment policies for patients with hepatitis C virus.

Background: Evaluation of new treatment policies is often costly and challenging in complex conditions, such as hepatitis C virus (HCV) treatment, or in limited-resource settings. We sought to identify hypothetical policies for HCV treatment that could best balance the prevention of cirrhosis while preserving resources (financial or otherwise).

Methods: The cohort consisted of 3792 HCV-infected patients without a history of cirrhosis or hepatocellular carcinoma at baseline from the national Veterans Health Administration from 2015 to 2019.

Relationships between work-environment characteristics and behavioral health provider burnout in the Veterans Health Administration.

Objective: To identify work-environment characteristics associated with Veterans Health Administration (VHA) behavioral health provider (BHP) burnout among psychiatrists, psychologists, and social workers.

Data Sources: The 2015-2018 data from Annual All Employee Survey (AES); Mental Health Provider Survey (MHPS); N = 57,397 respondents; facility-level Mental Health Onboard Clinical (MHOC) staffing and productivity data, N = 140 facilities.

Study Design: For AES and MHPS separately, we used mixed-effects logistic regression to predict BHP burnout using surveys from year pairs (2015-2016, 2016-2017, 2017-2018; six models).

Trends in Incident Varenicline Prescribing Among Veterans Following the US Food and Drug Administration Drug Safety Warnings.

To evaluate national trends in incident varenicline and nicotine replacement therapy (NRT) prescribing among Department of Veterans Affairs (VA) beneficiaries before and after US Food and Drug Administration (FDA) warnings regarding neuropsychiatric side effects with varenicline use. All adult VA patients identified as smokers from 2007 to 2019 (N = 3,600,947) were determined and monthly counts of new varenicline and NRT users were calculated. An interrupted time-series analysis estimated the effect of the FDA warnings on varenicline and NRT prescribing overall and among Veterans with and without mental health disorders.

Adapted time-varying covariates Cox model for predicting future cirrhosis development performs well in a large hepatitis C cohort.

Background: Patients with hepatitis C virus (HCV) frequently remain at risk for cirrhosis after sustained virologic response (SVR). Existing cirrhosis predictive models for HCV do not account for dynamic antiviral treatment status and are limited by fixed laboratory covariates and short follow up time. Advanced fibrosis assessment modalities, such as transient elastography, remain inaccessible in many settings.

Employment After Vocational Rehabilitation Predicts Decreased Health Care Utilization in Veterans With Mental Health Diagnoses.

Introduction: Although the benefits of employment for veterans with mental health conditions are well-known, the effect of veterans' employment on a health system has not been evaluated. The purpose of this study was to evaluate the effect of veterans' employment (versus unemployment) on subsequent health care utilization in the Veterans Health Administration (VHA).

Materials And Methods: This study used a sample of 29,022 veterans with mental health and substance use disorders who were discharged from VHA's employment services programs between fiscal years 2006 and 2010.

The Use of Readily Available Longitudinal Data to Predict the Likelihood of Surgery in Crohn Disease.

Background: Although imaging, endoscopy, and inflammatory biomarkers are associated with future Crohn disease (CD) outcomes, common laboratory studies may also provide prognostic opportunities. We evaluated machine learning models incorporating routinely collected laboratory studies to predict surgical outcomes in U.S.

Association of Anti-Tumor Necrosis Factor Therapy With Mortality Among Veterans With Inflammatory Bowel Disease.

Importance: Inflammatory bowel disease (IBD) is commonly treated with corticosteroids and anti-tumor necrosis factor (TNF) drugs; however, medications have well-described adverse effects. Prior work suggests that anti-TNF therapy may reduce all-cause mortality compared with prolonged corticosteroid use among Medicare and Medicaid beneficiaries with IBD.

Objective: To examine the association between use of anti-TNF or corticosteroids and all-cause mortality in a national cohort of veterans with IBD.

Assessment of a Deep Learning Model to Predict Hepatocellular Carcinoma in Patients With Hepatitis C Cirrhosis.

Importance: Deep learning, a family of machine learning models that use artificial neural networks, has achieved great success at predicting outcomes in nonmedical domains.

Objective: To examine whether deep learning recurrent neural network (RNN) models that use raw longitudinal data extracted directly from electronic health records outperform conventional regression models in predicting the risk of developing hepatocellular carcinoma (HCC).

Design, Setting, And Participants: This prognostic study included 48 151 patients with hepatitis C virus (HCV)-related cirrhosis in the national Veterans Health Administration who had at least 3 years of follow-up after the diagnosis of cirrhosis.

Predictors of Veterans Affairs Health Service Utilization by Women Veterans during Pregnancy.

Background: Researchers have examined predictors of Veterans Affairs (VA) service use by women veterans in general, but less is known about predictors of VA service use by pregnant veterans. This study examined characteristics associated with planned and actual VA service use by pregnant veterans.

Methods: This study includes data from 510 pregnant veterans enrolled in the Center for Maternal and Infant Outcomes Research in Translation Study.

Nurse staffing and healthcare-associated infections in a national healthcare system that implemented a nurse staffing directive: Multi-level interrupted time series analyses.

Background: In 2010, the Veterans Health Administration Office of Nursing Services (VHA ONS) issued a Staffing Methodology (SM) Directive, standardizing the method of determining appropriate nurse staffing for VHA facilities.

Objectives: To assess associations between the Directive, nurse staffing trends, and healthcare-associated infections.

Research Design: We conducted multi-level interrupted time series analyses of nurse staffing trends and the rates of two healthcare-associated infections before and after implementation of the Directive, October 1, 2008 - June 30, 2014.

Predictors of Long-Term and High-Dose Use of Zolpidem in Veterans.

Objective: Prescriptions for sedative hypnotics are routinely initiated and renewed to treat insomnia, despite evidence supporting nonpharmacologic treatments as comparable and more favorable over time. We used national Veterans Health Administration data to assess patient characteristics associated with high-dose and long-term zolpidem use.

Method: The study included outpatients with new zolpidem prescriptions (January 1, 2013, to June 3, 2014).

Machine learning models to predict disease progression among veterans with hepatitis C virus.

Background: Machine learning (ML) algorithms provide effective ways to build prediction models using longitudinal information given their capacity to incorporate numerous predictor variables without compromising the accuracy of the risk prediction. Clinical risk prediction models in chronic hepatitis C virus (CHC) can be challenging due to non-linear nature of disease progression. We developed and compared two ML algorithms to predict cirrhosis development in a large CHC-infected cohort using longitudinal data.

Virtual Consultations Through the Veterans Administration SCAN-ECHO Project Improves Survival for Veterans With Liver Disease.

Access to specialty care has been associated with improved survival in patients with liver disease but universal access is not always feasible. Methods of care delivery using virtual modalities including the SCAN-ECHO (Specialty Access Network-Extension of Community Healthcare Outcome) program were implemented by the Veterans Health Administration (VHA) to address this need but limited data are available on patient outcomes. We sought to evaluate the efficacy of a SCAN-ECHO visit within the context of a regional cohort of patients with liver disease in the VHA (n = 62,237) following implementation in the Ann Arbor SCAN-ECHO Liver Clinic from June 1, 2011, to March 31, 2015.

Access to Subspecialty Care And Survival Among Patients With Liver Disease.

Objectives: Access to subspecialty care may be difficult for patients with liver disease, but it is unknown whether access influences outcomes among this population. Our objectives were to determine rates and predictors of access to ambulatory gastrointestinal (GI) subspecialty care for patients with liver disease and to determine whether access to subspecialty GI care is associated with better survival.

Methods: We studied 28,861 patients within the Veterans Administration VISN 11 Liver Disease cohort who had an ICD-9-CM diagnosis code for liver disease from 1 January 2000 through 30 May 2011.