Facility-level program components leading to population impact: a coincidence analysis of obesity treatment options within the Veterans Health Administration.

Obesity is a well-established risk factor for increased morbidity and mortality. Comprehensive lifestyle interventions, pharmacotherapy, and bariatric surgery are three effective treatment approaches for obesity. The Veterans Health Administration (VHA) offers all three domains but in different configurations across medical facilities.

Interpretability, credibility, and usability of hospital-specific template matching versus regression-based hospital performance assessments; a multiple methods study.

Background: Hospital-specific template matching (HS-TM) is a newer method of hospital performance assessment.

Objective: To assess the interpretability, credibility, and usability of HS-TM-based vs. regression-based performance assessments.

Endoscopist-directed sedation rarely fails: implications for the value of anesthesia assistance for routine GI endoscopy.

Objectives: Use of anesthesia-assisted (AA) sedation for routine gastrointestinal (GI) endoscopy has increased markedly. Clinical uncertainty about which patients are most likely to benefit from AA sedation contributes to this increased use. We aimed to estimate the prevalence of failed endoscopist-directed sedation and to identify patients at elevated risk of failing standard sedation.

Hospital-specific Template Matching for Benchmarking Performance in a Diverse Multihospital System.

Background: Hospital-specific template matching is a newer method of hospital performance measurement that may be fairer than regression-based benchmarking. However, it has been tested in only limited research settings.

Objective: The objective of this study was to test the feasibility of hospital-specific template matching assessments in the Veterans Affairs (VA) health care system and determine power to detect greater-than-expected 30-day mortality.

Replicating prediction algorithms for hospitalization and corticosteroid use in patients with inflammatory bowel disease.

Introduction: Previous work had shown that machine learning models can predict inflammatory bowel disease (IBD)-related hospitalizations and outpatient corticosteroid use based on patient demographic and laboratory data in a cohort of United States Veterans. This study aimed to replicate this modeling framework in a nationally representative cohort.

Methods: A retrospective cohort design using Optum Electronic Health Records (EHR) were used to identify IBD patients, with at least 12 months of follow-up between 2007 and 2018.

Facility-level conditions leading to higher reach: a configurational analysis of national VA weight management programming.

Background: While the Veterans Health Administration (VHA) MOVE! weight management program is effective in helping patients lose weight and is available at every VHA medical center across the United States, reaching patients to engage them in treatment remains a challenge. Facility-based MOVE! programs vary in structures, processes of programming, and levels of reach, with no single factor explaining variation in reach. Configurational analysis, based on Boolean algebra and set theory, represents a mathematical approach to data analysis well-suited for discerning how conditions interact and identifying multiple pathways leading to the same outcome.

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.

Developing a template matching algorithm for benchmarking hospital performance in a diverse, integrated healthcare system.

Template matching is a proposed approach for hospital benchmarking, which measures performance based on matching a subset of comparable patient hospitalizations from each hospital. We assessed the ability to create the required matched samples and thus the feasibility of template matching to benchmark hospital performance in a diverse healthcare system.Nationwide Veterans Affairs (VA) hospitals, 2017.

Inpatient and Discharge Fluoroquinolone Prescribing in Veterans Affairs Hospitals Between 2014 and 2017.

Background: Between 2007 and 2015, inpatient fluoroquinolone use declined in US Veterans Affairs (VA) hospitals. Whether fluoroquinolone use at discharge also declined, in particular since antibiotic stewardship programs became mandated at VA hospitals in 2014, is unknown.

Methods: In this retrospective cohort study of hospitalizations with infection between January 1, 2014, and December 31, 2017, at 125 VA hospitals, we assessed inpatient and discharge fluoroquinolone (ciprofloxacin, levofloxacin, moxifloxacin) use as (a) proportion of hospitalizations with a fluoroquinolone prescribed and (b) fluoroquinolone-days per 1000 hospitalizations.

Construction and Use of Body Weight Measures from Administrative Data in a Large National Health System: A Systematic Review.

Objective: Administrative data are increasingly used in research and evaluation yet lack standardized guidelines for constructing measures using these data. Body weight measures from administrative data serve critical functions of monitoring patient health, evaluating interventions, and informing research. This study aimed to describe the algorithms used by researchers to construct and use weight measures.

Increased Cardiovascular Disease Risk in Veterans With Mental Illness.

Background: Although previous studies have demonstrated an association between various mental illnesses and cardio-cerebrovascular disease (CVD) risk, few have compared the strength of association between different mental illnesses and CVD risk.

Methods And Results: We assessed the association of psychiatric diagnoses (psychosis, bipolar disorder, depression, anxiety, and posttraumatic stress disorder) with major CVD outcomes (CVD events and CVD mortality) over 5 years, using a national primary prevention cohort of military veterans receiving care in the Department of Veterans Affairs. Data were linked from the Department of Veterans Affairs, Centers for Medicare and Medicaid Services, and Centers for Disease Control and Prevention National Death Index databases.

The Association of Medications and Vaccination with Risk of Pneumonia in Inflammatory Bowel Disease.

Background: Patients with inflammatory bowel disease (IBD) are at increased risk for pneumonia, and corticosteroids are reported to amplify this risk. Less is known about the impact of corticosteroid-sparing IBD therapies on pneumonia risk or the efficacy of pneumococcal vaccination in reducing all-cause pneumonia in real-world IBD cohorts.

Methods: We performed a population-based study using an established Veterans Health Administration cohort of 29,957 IBD patients.

Intensive Glucose Control in Patients with Type 2 Diabetes - 15-Year Follow-up.

Background: We previously reported that a median of 5.6 years of intensive as compared with standard glucose lowering in 1791 military veterans with type 2 diabetes resulted in a risk of major cardiovascular events that was significantly lower (by 17%) after a total of 10 years of combined intervention and observational follow-up. We now report the full 15-year follow-up.

Template matching for benchmarking hospital performance in the veterans affairs healthcare system.

Comparing hospital performance in a health system is traditionally done with multilevel regression models that adjust for differences in hospitals' patient case-mix. In contrast, "template matching" compares outcomes of similar patients at different hospitals but has been used only in limited patient settings.Our objective was to test a basic template matching approach in the nationwide Veterans Affairs healthcare system (VA), compared with a more standard regression approach.

Veterans Affairs patient database (VAPD 2014-2017): building nationwide granular data for clinical discovery.

Background: To study patient physiology throughout a period of acute hospitalization, we sought to create accessible, standardized nationwide data at the level of the individual patient-facility-day. This methodology paper summarizes the development, organization, and characteristics of the Veterans Affairs Patient Database 2014-2017 (VAPD 2014-2017). The VAPD 2014-2017 contains acute hospitalizations from all parts of the nationwide VA healthcare system with daily physiology including clinical data (labs, vitals, medications, risk scores, etc.

Effects of Severe Hypoglycemia on Cardiovascular Outcomes and Death in the Veterans Affairs Diabetes Trial.

Objective: To determine the risk factors for severe hypoglycemia and the association between severe hypoglycemia and serious cardiovascular adverse events and cardiovascular and all-cause mortality in the Veterans Affairs Diabetes Trial (VADT).

Research Design And Methods: This post hoc analysis of data from the VADT included 1,791 military veterans (age 60.5 ± 9.

Variation in Laboratory Test Naming Conventions in EHRs Within and Between Hospitals: A Nationwide Longitudinal Study.

Background: Electronic health records provide clinically rich data for research and quality improvement work. However, the data are often unstructured text, may be inconsistently recorded and extracted into centralized databases, making them difficult to use for research.

Objectives: We sought to quantify the variation in how key laboratory measures are recorded in the Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW) across hospitals and over time.

Using Veterans Affairs Corporate Data Warehouse to identify 30-day hospital readmissions.

Hospital readmission is a key metric of hospital quality, such as for comparing Veterans Affairs (VA) hospitals to private sector hospitals. To calculate readmission rates, one must first identify individual hospitalizations. However, in the VA Corporate Data Warehouse (CDW), data are organized by "bedded stays," that is, any stay in a healthcare facility where a patient is provided a bed, not hospitalizations.

Correction: Corticosteroid Use and Complications in a US Inflammatory Bowel Disease Cohort.

[This corrects the article DOI: 10.1371/journal.pone.

Predicting Hospitalization and Outpatient Corticosteroid Use in Inflammatory Bowel Disease Patients Using Machine Learning.

Background: Inflammatory bowel disease (IBD) is a chronic disease characterized by unpredictable episodes of flares and periods of remission. Tools that accurately predict disease course would substantially aid therapeutic decision-making. This study aims to construct a model that accurately predicts the combined end point of outpatient corticosteroid use and hospitalizations as a surrogate for IBD flare.

The Veterans Affairs Cardiac Risk Score: Recalibrating the Atherosclerotic Cardiovascular Disease Score for Applied Use.

Background: Accurately estimating cardiovascular risk is fundamental to good decision-making in cardiovascular disease (CVD) prevention, but risk scores developed in one population often perform poorly in dissimilar populations. We sought to examine whether a large integrated health system can use their electronic health data to better predict individual patients' risk of developing CVD.

Methods: We created a cohort using all patients ages 45-80 who used Department of Veterans Affairs (VA) ambulatory care services in 2006 with no history of CVD, heart failure, or loop diuretics.

Corrected ROC analysis for misclassified binary outcomes.

Creating accurate risk prediction models from Big Data resources such as Electronic Health Records (EHRs) is a critical step toward achieving precision medicine. A major challenge in developing these tools is accounting for imperfect aspects of EHR data, particularly the potential for misclassified outcomes. Misclassification, the swapping of case and control outcome labels, is well known to bias effect size estimates for regression prediction models.

Age Disparities in the Use of Steroid-sparing Therapy for Inflammatory Bowel Disease.

Background: Corticosteroids are effective rescue therapies for patients with inflammatory bowel disease (IBD), but have significant side effects, which may be amplified in the growing population of elderly patients with IBD. We aimed to compare the use of steroids and steroid-sparing therapies (immunomodulators and biologics) and rates of complications among elderly (≥65) and younger patients in a national cohort of veterans with IBD.

Methods: We used national Veterans Health Administrative data to conduct a retrospective study of veterans with IBD between 2002 and 2010.

Corticosteroid Use and Complications in a US Inflammatory Bowel Disease Cohort.

Background And Aims: Corticosteroids are effective for the short-term treatment of inflammatory bowel disease (IBD). Long-term use, however, is associated with significant adverse effects. To define the: (1) frequency and duration of corticosteroid use, (2) frequency of escalation to corticosteroid-sparing therapy, (3) rate of complications related to corticosteroid use, (4) rate of appropriate bone density measurements (dual energy X-ray absorptiometry [DEXA] scans), and (5) factors associated with escalation and DEXA scans.