Implementation and Impact of Intimate Partner Violence Screening Expansion in the Veterans Health Administration: Protocol for a Mixed Methods Evaluation.

BACKGROUND: Intimate partner violence (IPV) is a significant public health problem with far-reaching consequences. The health care system plays an integral role in the detection of and response to IPV. Historically, the majority of IPV screening initiatives have targeted women of reproductive age, with little known about men's IPV screening experiences or the impact of screening on men's health care. The Veterans Health Administration (VHA) has called for an expansion of IPV screening, providing a unique opportunity for a large-scale evaluation of IPV screening and response across all patient populations. OBJECTIVE: In this protocol paper, we describe the recently funded Partnered Evaluation of Relationship Health Innovations and Services through Mixed Methods (PRISM) initiative, aiming to evaluate the implementation and impact of the VHA's IPV screening and response expansion, with a particular focus on identifying potential gender differences. METHODS: The PRISM Initiative is guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) and Consolidated Framework for Implementation Research (CFIR 2.0) frameworks. We will use mixed methods data from 139 VHA facilities to evaluate the IPV screening expansion, including electronic health record data and qualitative interviews with patients, clinicians, and national IPV program leadership. Quantitative data will be analyzed using a longitudinal observational design with repeated measurement periods at baseline (T0), year 1 (T1), and year 2 (T2). Qualitative interviews will focus on identifying multilevel factors, including potential implementation barriers and facilitators critical to IPV screening and response expansion, and examining the impact of screening on patients and clinicians. RESULTS: The PRISM initiative was funded in October 2023. We have developed the qualitative interview guides, obtained institutional review board approval, extracted quantitative data for baseline analyses, and began recruitment for qualitative interviews. Reports of progress and results will be made available to evaluation partners and funders through quarterly and end-of-year reports. All data collection and analyses across time points are expected to be completed in June 2026. CONCLUSIONS: Findings from this mixed methods evaluation will provide a comprehensive understanding of IPV screening expansion at the VHA, including the implementation and impact of screening and the scope of IPV detected in the VHA patient population. Moreover, data generated by this initiative have critical policy and clinical practice implications in a national health care system. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/59918.

Development and Validation of Case-Finding Algorithms to Identify Pancreatic Cancer in the Veterans Health Administration.

BACKGROUND: Survival in pancreatic ductal adenocarcinoma (PDAC) remains poor due to late diagnosis. Electronic Health Records (EHRs) can be used to study this rare disease, but validated algorithms to identify PDAC in the United States EHRs do not currently exist. AIMS: To develop and validate an algorithm using Veterans Health Administration (VHA) EHR data for the identification of patients with PDAC. METHODS: We developed two algorithms to identify patients with PDAC in the VHA from 2002 to 2023. The algorithms required diagnosis of exocrine pancreatic cancer in either ≥ 1 or ≥ 2 of the following domains: (i) the VA national cancer registry, (ii) an inpatient encounter, or (iii) an outpatient encounter in an oncology setting. Among individuals identified with ≥ 1 of the above criteria, a random sample of 100 were reviewed by three gastroenterologists to adjudicate PDAC status. We also adjudicated fifty patients not qualifying for either algorithm. These patients died as inpatients and had alkaline phosphatase values within the interquartile range of patients who met ≥ 2 of the above criteria for PDAC. These expert adjudications allowed us to calculate the positive and negative predictive value of the algorithms. RESULTS: Of 10.8 million individuals, 25,533 met ≥ 1 criteria (PPV 83.0%, kappa statistic 0.93) and 13,693 individuals met ≥ 2 criteria (PPV 95.2%, kappa statistic 1.00). The NPV for PDAC was 100%. CONCLUSIONS: An algorithm incorporating readily available EHR data elements to identify patients with PDAC achieved excellent PPV and NPV. This algorithm is likely to enable future epidemiologic studies of PDAC.

Screening for Intimate Partner Violence Experience and Use in the Veterans Health Administration.

Importance: The practice of screening women for intimate partner violence (IPV) in health care settings has been a critical part of responding to this major public health problem. Yet, IPV prevention would be enhanced with detection efforts that extend beyond screening for IPV experiences to identifying those who use violence in relationships as well. Objective: To determine rates of IPV experiences and use (ie, among perpetrators of IPV) and factors associated with disclosures among adult patients seeking mental health services at the Veterans Health Administration. Design, Setting, and Participants: This cross-sectional study used electronic medical record data drawn from a quality improvement initiative at 5 Veterans Health Administration medical centers conducted between November 2021 and February 2022 to examine IPV disclosures following concurrent screening for IPV experience and use. Participants included patients engaged in mental health services. Data were analyzed in April and May 2023. Exposure: Mental health clinicians were trained to screen for IPV experience and use concurrently and instructed to screen all patients encountered through routine mental health care visits during a 3-month period. Main Outcomes and Measures: Outcomes of interest were past-year prevalence of IPV use and experience, sociodemographic characteristics, and clinical diagnoses among screened patients. Results: A total of 200 patients were offered IPV screening. Of 155 participants (mean [SD] age, 52.45 [15.65] years; 124 [80.0%] men) with completed screenings, 74 (47.7%) denied past-year IPV experience and use, 76 (49.0%) endorsed past-year IPV experience, and 72 (46.4%) endorsed past-year IPV use, including 67 participants (43.2%) who reported IPV experience and use concurrently; only 9 participants (5.8%) endorsed unidirectional IPV experiences and 5 participants (3.2%) endorsed unidirectional IPV use. Patients who reported past-year IPV experience and use were younger than those who denied IPV (experience: mean difference, -7.34 [95% CI, 2.51-12.17] years; use: mean difference, -7.20 [95% CI, 2.40-12.00] years). Patients with a posttraumatic stress disorder diagnosis were more likely to report IPV use (43 patients [59.7%]) than those without a posttraumatic stress disorder diagnosis (29 patients [40.3%]; odds ratio, 2.14; [95% CI, 1.12-4.06]). No other demographic characteristics or clinical diagnoses were associated with IPV use or experience. Conclusions and Relevance: In this cross-sectional study of IPV rates and associated factors, screening for IPV found high rates of both IPV experience and use among patients receiving mental health care. These findings highlight the benefit of screening for IPV experience and use concurrently across gender and age. Additionally, the associations found between PTSD and IPV use underscore the importance of strengthening and developing additional targeted treatment for IPV.

Racial, Ethnic, and Rural Disparities in US Veteran COVID-19 Vaccine Rates.

Background: Race, ethnicity, and rurality-related disparities in coronavirus disease 2019 (COVID-19) vaccine uptake have been documented in the United States (US). Objective: We determined whether these disparities existed among patients at the Department of Veterans Affairs (VA), the largest healthcare system in the US. Design Settings Participants Measurements: Using VA Corporate Data Warehouse data, we included 5,871,438 patients (9.4% women) with at least one primary care visit in 2019 in a retrospective cohort study. Each patient was assigned a single race/ethnicity, which were mutually exclusive, self-reported categories. Rurality was based on 2019 home address at the zip code level. Our primary outcome was time-to-first COVID-19 vaccination between December 15, 2020-June 15, 2021. Additional covariates included age (in years), sex, geographic region (North Atlantic, Midwest, Southeast, Pacific, Continental), smoking status (current, former, never), Charlson Comorbidity Index (based on ≥1 inpatient or two outpatient ICD codes), service connection (any/none, using standardized VA-cutoffs for disability compensation), and influenza vaccination in 2019-2020 (yes/no). Results: Compared with unvaccinated patients, those vaccinated (n=3,238,532; 55.2%) were older (mean age in years vaccinated=66.3, (standard deviation=14.4) vs. unvaccinated=57.7, (18.0), p<.0001)). They were more likely to identify as Black (18.2% vs. 16.1%, p<.0001), Hispanic (7.0% vs. 6.6% p<.0001), or Asian American/Pacific Islander (AA/PI) (2.0% vs. 1.7%, P<.0001). In addition, they were more likely to reside in urban settings (68.0% vs. 62.8, p<.0001). Relative to non-Hispanic White urban Veterans, the reference group for race/ethnicity-urban/rural hazard ratios reported, all urban race/ethnicity groups were associated with increased likelihood for vaccination except American Indian/Alaskan Native (AI/AN) groups. Urban Black groups were 12% more likely (Hazard Ratio (HR)=1.12 [CI 1.12-1.13]) and rural Black groups were 6% more likely to receive a first vaccination (HR=1.06 [1.05-1.06]) relative to white urban groups. Urban Hispanic, AA/PI and Mixed groups were more likely to receive vaccination while rural members of these groups were less likely (Hispanic: Urban HR=1.17 [1.16-1.18], Rural HR=0.98 [0.97-0.99]; AA/PI: Urban HR=1.22 [1.21-1.23], Rural HR=0.86 [0.84-0.88]). Rural White Veterans were 21% less likely to receive an initial vaccine compared with urban White Veterans (HR=0.79 [0.78-0.79]). AI/AN groups were less likely to receive vaccination regardless of rurality: Urban HR=0.93 [0.91-0.95]; AI/AN-Rural HR=0.76 [0.74-0.78]. Conclusions: Urban Black, Hispanic, and AA/PI Veterans were more likely than their urban White counterparts to receive a first vaccination; all rural race/ethnicity groups except Black patients had lower likelihood for vaccination compared with urban White patients. A better understanding of disparities and rural outreach will inform equitable vaccine distribution.

Development of REDCap-based architecture for a clinical decision support tool linked to the electronic health record for assessment of medication appropriateness.

Objective: To develop the architecture for a clinical decision support system (CDSS) linked to the electronic health record (EHR) using the tools provided by Research Electronic Data Capture (REDCap) to assess medication appropriateness in older adults with polypharmacy. Materials and Methods: The tools available in REDCap were used to create the architecture for replicating a previously developed stand-alone system while overcoming its limitations. Results: The architecture consists of data input forms, drug- and disease-mapper, rules engine, and report generator. The input forms integrate medication and health condition data from the EHR with patient assessment data. The rules engine evaluates medication appropriateness through rules built through a series of drop-down menus. The rules generate output, which are a set of recommendations to the clinician. Discussion and conclusion: This architecture successfully replicates the stand-alone CDSS while addressing its limitations. It is compatible with several EHRs, easily shared among the large community using REDCap, and readily modifiable.

Assessing the contributions of modifiable risk factors to serious falls and fragility fractures among older persons living with HIV.

BACKGROUND: Although 50 years represents middle age among uninfected individuals, studies have shown that persons living with HIV (PWH) begin to demonstrate elevated risk for serious falls and fragility fractures in the sixth decade; the proportions of these outcomes attributable to modifiable factors are unknown. METHODS: We analyzed 21,041 older PWH on antiretroviral therapy (ART) from the Veterans Aging Cohort Study from 01/01/2010 through 09/30/2015. Serious falls were identified by Ecodes and a machine-learning algorithm applied to radiology reports. Fragility fractures (hip, vertebral, and upper arm) were identified using ICD9 codes. Predictors for both models included a serious fall within the past 12 months, body mass index, physiologic frailty (VACS Index 2.0), illicit substance and alcohol use disorders, and measures of multimorbidity and polypharmacy. We separately fit multivariable logistic models to each outcome using generalized estimating equations. From these models, the longitudinal extensions of average attributable fraction (LE-AAF) for modifiable risk factors were estimated. RESULTS: Key risk factors for both outcomes included physiologic frailty (VACS Index 2.0) (serious falls [15%; 95% CI 14%-15%]; fractures [13%; 95% CI 12%-14%]), a serious fall in the past year (serious falls [7%; 95% CI 7%-7%]; fractures [5%; 95% CI 4%-5%]), polypharmacy (serious falls [5%; 95% CI 4%-5%]; fractures [5%; 95% CI 4%-5%]), an opioid prescription in the past month (serious falls [7%; 95% CI 6%-7%]; fractures [9%; 95% CI 8%-9%]), and diagnosis of alcohol use disorder (serious falls [4%; 95% CI 4%-5%]; fractures [8%; 95% CI 7%-8%]). CONCLUSIONS: This study confirms the contributions of risk factors important in the general population to both serious falls and fragility fractures among older PWH. Successful prevention programs for these outcomes should build on existing prevention efforts while including risk factors specific to PWH.

Depression, Insomnia, and Obesity Among Post-9/11 Veterans: Eating Pathology as a Distinct Health Risk Behavior.

INTRODUCTION: Understanding the interrelationships between co-occurring chronic health conditions and health behaviors is critical to developing interventions to successfully change multiple health behaviors and related comorbidities. The objective of the present study was to examine the effects of depression, insomnia, and their co-occurrence on risk of obesity and to examine the role of health risk behaviors as potential confounders of these relationships with an emphasis on eating pathologies. METHODS: Iraq and Afghanistan conflict era veterans (n = 1,094, 51.2% women) who participated in the Women Veterans Cohort Study between July 2014 and September 2019 were categorized as having depression, insomnia, both, or neither condition. Logistic regression models were used to examine group differences in the risk of obesity. Health risk behaviors (i.e., eating pathology, physical activity, smoking, and hazardous drinking) were then assessed as potential confounders of the effects of depression and insomnia on the likelihood of obesity. RESULTS: Obesity was most prevalent in individuals with co-occurring insomnia and depression (53.2%), followed by depression only (44.6%), insomnia only (38.5%), and neither condition (30.1%). Importantly, maladaptive eating behaviors confounded the depression-obesity association but not the insomnia-obesity association. There was no evidence that insufficient physical activity, smoking, or hazardous drinking confounded the effects of insomnia or depression on obesity. CONCLUSIONS: These findings exemplify the complex relationships between multiple health conditions and behaviors that contribute to obesity. Elucidating these associations can enhance the precision with which interventions are tailored to efficiently allocate resources and reduce the severe health impact of obesity among veterans.

Post-9/11 deployment history and the incidence of breast cancer among women veterans.

PURPOSE: To determine if women Veterans who deployed in support of Operations Enduring Freedom/Iraqi Freedom (OEF/OIF) would show a greater likelihood of breast cancer (BC) than other women Veterans. METHODS: This was a retrospective cohort study of women aged <60 years who received Veterans Affairs medical center primary care, 2001-2021. The exposure was OEF/OIF deployment and the outcome was a BC diagnosis after entering Veterans Affairs care. Poisson models evaluated the association between deployment and BC incidence, covarying demographics, lifestyle factors, and hormonal contraceptive and hormone replacement therapy use. Analyses were also stratified by age and race, and a sensitivity analysis adjusted for healthcare utilization over the initial 2 years. RESULTS: Of 576,601 women, 24.6% (n = 141,935) deployed during post-9/11 conflicts. Across follow-up [median: 8.2 years], 1.2% women were diagnosed with BC. Those who deployed in support of OEF/OIF were 23% less likely to be diagnosed with BC than women who did not deploy (95% CI: 0.73, 0.86). The association remained in stratified models and when including healthcare utilization. CONCLUSIONS: Despite the exposures of OEF/OIF deployment, there was a significantly lower incidence of BC among women who deployed versus not, possibly due to a healthy soldier effect or to differences in screening.

Predictive Risk Model for Serious Falls Among Older Persons Living With HIV.

BACKGROUND: Older (older than 50 years) persons living with HIV (PWH) are at elevated risk for falls. We explored how well our algorithm for predicting falls in a general population of middle-aged Veterans (age 45-65 years) worked among older PWH who use antiretroviral therapy (ART) and whether model fit improved with inclusion of specific ART classes. METHODS: This analysis included 304,951 six-month person-intervals over a 15-year period (2001-2015) contributed by 26,373 older PWH from the Veterans Aging Cohort Study who were taking ART. Serious falls (those falls warranting a visit to a health care provider) were identified by external cause of injury codes and a machine-learning algorithm applied to radiology reports. Potential predictors included a fall within the past 12 months, demographics, body mass index, Veterans Aging Cohort Study Index 2.0 score, substance use, and measures of multimorbidity and polypharmacy. We assessed discrimination and calibration from application of the original coefficients (model derived from middle-aged Veterans) to older PWH and then reassessed by refitting the model using multivariable logistic regression with generalized estimating equations. We also explored whether model performance improved with indicators of ART classes. RESULTS: With application of the original coefficients, discrimination was good (C-statistic 0.725; 95% CI: 0.719 to 0.730) but calibration was poor. After refitting the model, both discrimination (C-statistic 0.732; 95% CI: 0.727 to 0.734) and calibration were good. Including ART classes did not improve model performance. CONCLUSIONS: After refitting their coefficients, the same variables predicted risk of serious falls among older PWH nearly and they had among middle-aged Veterans.

Joint longitudinal trajectories of pain intensity and opioid prescription in veterans with back pain.

PURPOSE: We describe pain intensity and opioid prescription jointly over time in Veterans with back pain to better understand their relationship. METHODS: We performed a retrospective cohort study on electronic health record data from 117 126 Veterans (mean age 49.2 years) diagnosed with back pain in 2015. We used latent class growth analysis to jointly model pain intensity (0-10 scores) and opioid prescriptions over 2 years to identify classes of individuals similar in their trajectory of pain and opioid over time. Multivariable multinomial logit models assessed sociodemographic and clinical predictors of class membership. RESULTS: We identified six trajectory classes: a "no pain/no opioid" class (22.2%), a "mild pain/no opioid" class (45.0%), a "moderate pain/no opioid" class (24.6%), a "moderate, decreasing pain/decreasing opioid" class (3.3%), a "moderate pain/high opioid" class (2.6%), and a "moderate, increasing pain/increasing opioid" class (2.3%). Among those in moderate pain classes, being white (vs. non-white) and older were associated with higher odds of being prescribed opioids. Veterans with mental health diagnoses had increased odds of being in the painful classes versus "no pain/no opioid" class. CONCLUSION: We found distinct patterns in the long-term joint course of pain and opioid prescription in Veterans with back pain. Understanding these patterns and associated predictors may help with development of targeted interventions for patients with back pain.

Pain and smoking study (PASS): A comparative effectiveness trial of smoking cessation counseling for veterans with chronic pain.

INTRODUCTION: Smoking is associated with greater pain intensity and pain-related functional interference in people with chronic pain. Interventions that teach smokers with chronic pain how to apply adaptive coping strategies to promote both smoking cessation and pain self-management may be effective. METHODS: The Pain and Smoking Study (PASS) is a randomized clinical trial of a telephone-delivered, cognitive behavioral intervention among Veterans with chronic pain who smoke cigarettes. PASS participants are randomized to a standard telephone counseling intervention that includes five sessions focusing on motivational interviewing, craving and relapse management, rewards, and nicotine replacement therapy versus the same components with the addition of a cognitive behavioral intervention for pain management. Participants are assessed at baseline, 6, and 12 months. The primary outcome is smoking cessation. RESULTS: The 371 participants are 88% male, a median age of 60 years old (range 24-82), and smoke a median of 15 cigarettes per day. Participants are mainly white (61%), unemployed (70%), 33% had a high school degree or less, and report their overall health as "Fair" (40%) to "Poor" (11%). Overall, pain was moderately high (mean pain intensity in past week = 5.2 (Standard Deviation (SD) = 1.6) and mean pain interference = 5.5 (SD = 2.2)). Pain-related anxiety was high (mean = 47.0 (SD = 22.2)) and self-efficacy was low (mean = 3.8 (SD = 1.6)). CONCLUSIONS: PASS utilizes an innovative smoking and pain intervention to promote smoking cessation among Veterans with chronic pain. Baseline characteristics reflect a socioeconomically vulnerable population with a high burden of mental health comorbidities.

Polygenic Breast Cancer Risk for Women Veterans in the Million Veteran Program.

Accurate breast cancer (BC) risk assessment allows personalized screening and prevention. Prospective validation of prediction models is required before clinical application. Here, we evaluate clinical- and genetic-based BC prediction models in a prospective cohort of women from the Million Veteran Program. MATERIALS AND METHODS: Clinical BC risk prediction models were validated in combination with a genetic polygenic risk score of 313 (PRS313) single-nucleotide polymorphisms in genetic females without prior BC diagnosis (n = 35,130, mean age 49 years) with 30% non-Hispanic African ancestry (AA). Clinical risk models tested were Breast and Prostate Cancer Cohort Consortium, literature review, and Breast Cancer Risk Assessment Tool, and implemented with or without PRS313. Prediction accuracy and association with incident breast cancer was evaluated with area under the receiver operating characteristic curve (AUC), hazard ratios, and proportion with high absolute lifetime risk. RESULTS: Three hundred thirty-eight participants developed incident breast cancers with a median follow-up of 3.9 years (2.5 cases/1,000 person-years), with 196 incident cases in women of European ancestry and 112 incident cases in AA women. Individualized Coherent Absolute Risk Estimator-literature review in combination with PRS313 had an AUC of 0.708 (95% CI, 0.659 to 0.758) in women with European or non-African ancestries and 0.625 (0.539 to 0.711) in AA women. Breast Cancer Risk Assessment Tool with PRS313 had an AUC of 0.695 (0.62 to 0.729) in European or non-AA and 0.675 (0.626 to 0.723) in AA women. Incorporation of PRS313 with clinical models improved prediction in European but not in AA women. Models estimated up to 9% of European and 18% of AA women with absolute lifetime risk > 20%. CONCLUSION: Clinical and genetic BC risk models predict incident BC in a large prospective multiracial cohort; however, more work is needed to improve genetic risk estimation in AA women.

Pain intensity and pain medication prescription patterns in Veterans with heart failure and back pain.

BACKGROUND: Pain and heart failure are highly comorbid. OBJECTIVES: The purpose of this study was to examine differences in pain intensity and pain medication prescriptions among Veterans with comorbid heart failure and pain and those with pain alone. METHODS: The Musculoskeletal Disorder (MSD) cohort includes 5,237,763 Veteran diagnosed with a musculoskeletal disorder between 2000 and 2013. Veterans with comorbid heart failure and back pain (heart failure+, n = 3,950, Mage = 70.5 ± 12) were compared to those with back pain alone (heart failure-, n = 165,290, Mage = 52.1 ± 17.5). RESULTS: In multivariate adjusted models, heart failure+ was associated with a higher likelihood of moderate/severe pain (OR = 1.12; 95% CI 1.04-1.21), a higher likelihood of opioids (OR = 1.63; CI = 1.52-1.75) and/or gabapentin prescriptions (OR = 1.18; CI = 1.02-1.36), but a lower likelihood of NSAID prescriptions (OR = 0.57; CI = 0.50-0.66). CONCLUSIONS: Comorbid cardiovascular and pain conditions present a challenge in clinical management that warrants further study.

Documentation of Screening for Firearm Access by Healthcare Providers in the Veterans Healthcare System: A Retrospective Study.

INTRODUCTION: Presence of a firearm is associated with increased risk of violence and suicide. United States military veterans are at disproportionate risk of suicide. Routine healthcare provider screening of firearm access may prompt counseling on safe storage and handling of firearms. The objective of this study was to determine the frequency with which Veterans Health Administration (VHA) healthcare providers document firearm access in electronic health record (EHR) clinical notes, and whether this varied by patient characteristics. METHODS: The study sample is a post-9-11 cohort of veterans in their first year of VHA care, with at least one outpatient care visit between 2012-2017 (N = 762,953). Demographic data, veteran military service characteristics, and clinical comorbidities were obtained from VHA EHR. We extracted clinical notes for outpatient visits to primary, urgent, or emergency clinics (total 105,316,004). Natural language processing and machine learning (ML) approaches were used to identify documentation of firearm access. A taxonomy of firearm terms was identified and manually annotated with text anchored by these terms, and then trained the ML algorithm. The random-forest algorithm achieved 81.9% accuracy in identifying documentation of firearm access. RESULTS: The proportion of patients with EHR-documented access to one or more firearms during their first year of care in the VHA was relatively low and varied by patient characteristics. Men had significantly higher documentation of firearms than women (9.8% vs 7.1%; P < .001) and veterans >50 years old had the lowest (6.5%). Among veterans with any firearm term present, only 24.4% were classified as positive for access to a firearm (24.7% of men and 20.9% of women). CONCLUSION: Natural language processing can identify documentation of access to firearms in clinical notes with acceptable accuracy, but there is a need for investigation into facilitators and barriers for providers and veterans to improve a systemwide process of firearm access screening. Screening, regardless of race/ethnicity, gender, and age, provides additional opportunities to protect veterans from self-harm and violence.

Predictors of prenatal smoking among US women veterans.

This study investigated prevalence and factors associated with prenatal smoking among US women veterans using cross-sectional data from a cohort study of veterans from recent wars utilizing Veterans Health Administration primary care (N = 6190). Among the participants, 747 (12.0%) were current smokers and 1039 (16.8%) were former smokers. Multivariable logistic regression indicated that White race, substance use disorder, and posttraumatic stress disorder were associated with increased likelihood of smoking during pregnancy. Conversely, being married and officer rank were associated with decreased likelihood of prenatal smoking. Findings suggest a need for empirical testing of interventions to address perinatal smoking, substance use, and mental health.

Serious Falls in Middle-Aged Veterans: Development and Validation of a Predictive Risk Model.

BACKGROUND/OBJECTIVES: Due to high rates of multimorbidity, polypharmacy, and hazardous alcohol and opioid use, middle-aged Veterans are at risk for serious falls (those prompting a visit with a healthcare provider), posing significant risk to their forthcoming geriatric health and quality of life. We developed and validated a predictive model of the 6-month risk of serious falls among middle-aged Veterans. DESIGN: Cohort study. SETTING: Veterans Health Administration (VA). PARTICIPANTS: Veterans, aged 45 to 65 years, who presented for care within the VA between 2012 and 2015 (N = 275,940). EXPOSURES: The exposures of primary interest were substance use (including alcohol and prescription opioid use), multimorbidity, and polypharmacy. Hazardous alcohol use was defined as an Alcohol Use Disorders Identification Test - Consumption (AUDIT-C) score of 3 or greater for women and 4 or greater for men. We used International Classification of Diseases, Ninth Revision (ICD-9), codes to identify alcohol and illicit substance use disorders and identified prescription opioid use from pharmacy fill-refill data. We included counts of chronic medications and of physical and mental health comorbidities. MEASUREMENTS: We identified serious falls using external cause of injury codes and a machine-learning algorithm that identified serious falls in radiology reports. We used multivariable logistic regression with general estimating equations to calculate risk. We used an integrated predictiveness curve to identify intervention thresholds. RESULTS: Most of our sample (54%) was aged 60 years or younger. Duration of follow-up was up to 4 years. Veterans who fell were more likely to be female (11% vs 7%) and White (72% vs 68%). They experienced 43,641 serious falls during follow-up. We identified 16 key predictors of serious falls and five interaction terms. Model performance was enhanced by addition of opioid use, as evidenced by overall category-free net reclassification improvement of 0.32 (P < .001). Discrimination (C-statistic = 0.76) and calibration were excellent for both development and validation data sets. CONCLUSION: We developed and internally validated a model to predict 6-month risk of serious falls among middle-aged Veterans with excellent discrimination and calibration.

Factors Associated With Posttraumatic Stress Disorder Among Veterans of Recent Wars Receiving Veterans Affairs Chiropractic Care.

OBJECTIVES: Post-traumatic stress disorder (PTSD) is thought to complicate pain management outcomes, which is consistent with the impact of other psychosocial factors in the biopsychosocial model of pain. This study aimed to identify patient sociodemographic and clinical characteristics associated with PTSD prevalence among veterans of Operations Enduring Freedom/Iraqi Freedom/New Dawn (OEF/OIF/OND) who received Veterans Affairs (VA) chiropractic care. METHODS: A cross-sectional analysis of electronic health record data from a national cohort study of OEF/OIF/OND veterans with at least 1 visit to a VA chiropractic clinic from 2001 to 2014 was performed. The primary outcome measure was a prior PTSD diagnosis. Variables including sex, race, age, body mass index, pain intensity, alcohol and substance use disorders, and smoking status were examined in association with PTSD diagnosis using logistic regression. RESULTS: We identified 14,025 OEF/OIF/OND veterans with at least 1 VA chiropractic visit, with a mean age of 38 years and 54.2% having a diagnosis of PTSD. Male sex (adjusted odds ratio [OR] = 1.23, 95% CI = 1.11-1.37), younger age (OR = 0.99, CI = 0.98-0.99), moderate-to-severe pain intensity (numerical rating scale ≥ 4) (OR = 1.72, CI = 1.59-1.87), body mass index ≥ 30 (OR = 1.34, CI = 1.24-1.45), current smoking (OR = 1.32, CI = 1.20-1.44), and having an alcohol or substance use disorder (OR = 4.51, CI = 4.01-5.08) were significantly associated with a higher likelihood of PTSD diagnosis. CONCLUSION: Post-traumatic stress disorder is a common comorbidity among OEF/OIF/OND veterans receiving VA chiropractic care and is significantly associated with several patient characteristics. Recognition of these factors is important for the appropriate diagnosis and management of veterans with PTSD seeking chiropractic treatment for pain conditions.

Natural Language Processing for Surveillance of Cervical and Anal Cancer and Precancer: Algorithm Development and Split-Validation Study.

BACKGROUND: Accurate identification of new diagnoses of human papillomavirus-associated cancers and precancers is an important step toward the development of strategies that optimize the use of human papillomavirus vaccines. The diagnosis of human papillomavirus cancers hinges on a histopathologic report, which is typically stored in electronic medical records as free-form, or unstructured, narrative text. Previous efforts to perform surveillance for human papillomavirus cancers have relied on the manual review of pathology reports to extract diagnostic information, a process that is both labor- and resource-intensive. Natural language processing can be used to automate the structuring and extraction of clinical data from unstructured narrative text in medical records and may provide a practical and effective method for identifying patients with vaccine-preventable human papillomavirus disease for surveillance and research. OBJECTIVE: This study's objective was to develop and assess the accuracy of a natural language processing algorithm for the identification of individuals with cancer or precancer of the cervix and anus. METHODS: A pipeline-based natural language processing algorithm was developed, which incorporated machine learning and rule-based methods to extract diagnostic elements from the narrative pathology reports. To test the algorithm's classification accuracy, we used a split-validation study design. Full-length cervical and anal pathology reports were randomly selected from 4 clinical pathology laboratories. Two study team members, blinded to the classifications produced by the natural language processing algorithm, manually and independently reviewed all reports and classified them at the document level according to 2 domains (diagnosis and human papillomavirus testing results). Using the manual review as the gold standard, the algorithm's performance was evaluated using standard measurements of accuracy, recall, precision, and F-measure. RESULTS: The natural language processing algorithm's performance was validated on 949 pathology reports. The algorithm demonstrated accurate identification of abnormal cytology, histology, and positive human papillomavirus tests with accuracies greater than 0.91. Precision was lowest for anal histology reports (0.87, 95% CI 0.59-0.98) and highest for cervical cytology (0.98, 95% CI 0.95-0.99). The natural language processing algorithm missed 2 out of the 15 abnormal anal histology reports, which led to a relatively low recall (0.68, 95% CI 0.43-0.87). CONCLUSIONS: This study outlines the development and validation of a freely available and easily implementable natural language processing algorithm that can automate the extraction and classification of clinical data from cervical and anal cytology and histology.

Association of prescription opioids and incident cardiovascular risk factors among post-9/11 Veterans.

Reports indicate that long-term opioid therapy is associated with cardiovascular disease (CVD). Using VA electronic health record data, we measured the impact of opioid use on the incidence of modifiable CVD risk factors. We included Veterans whose encounter was between October 2001 to November 2014. We identified Veterans without CVD risk factors during our baseline period, defined as the date of first primary care visit plus 365 days. The main exposure was opioid prescriptions (yes/no, long-term (i.e. ≥90 days) vs no opioid, and long-term vs short-term (i.e. <90 days)), which was time-updated yearly from the end of the baseline period to February 2015. The main outcome measures were incident CVD risk factors (hypertension, dyslipidemia, diabetes, obesity, and current smoking). After excluding prevalent CVD risk factors, we identified 308,015 Veterans. During the first year of observation, 12,725 (4.1%) Veterans were prescribed opioids, including 2028 (0.6%) with long-term exposure. Compared to patients without opioid use, Veterans with opioid use were more likely to have CVD risk factors. Those with long-term exposure were at higher risk of having hypertension (adjusted average hazards ratio [HR] 1.45, 99% confidence interval [CI] 1.33-1.59), dyslipidemia (HR 1.45, 99% CI 1.35-156), diabetes (HR 1.30, 99% CI 1.07-1.57), current smoking status (HR 1.34, 99% CI 1.24-1.46), and obesity (HR 1.22, 99% CI 1.12-1.32). Compared to short-term exposure, long-term had higher risk of current smoking status (HR 1.12, 99% CI 1.01-1.24). These findings suggest potential benefit to screening and surveillance of CVD risk factors for patients prescribed opioids, especially long-term opioid therapy.

Underutilization of Pulmonary Function Testing in Veterans Hospitalized for Chronic Obstructive Pulmonary Disease Exacerbation: Who are We Missing?

Pulmonary function testing (PFT) is required to diagnose chronic obstructive pulmonary disease (COPD) but is completed for only 30-50% of patients with the disease. We determined patient factors associated with decreased likelihood for PFT acquisition (i.e. underutilization) in the United States Veterans Affairs (VA) health care system.We performed a retrospective analysis of Veterans who survived a VA-based COPD hospitalization between 2012 and 2015. COPD was identified using International Classification of Disease (ICD)-9 codes. Our primary outcome was PFT acquisition, using Current Procedural Terminology (CPT) codes any time prior to the index hospitalization. We compared patients with and without PFTs and used logistic regression to identify associations with PFT underutilization.Of the 48,888 Veterans included, 78% underwent PFTs prior to hospitalization. Patients without PFTs were younger and more likely to be: women (4.2% vs. 3.6%; p = 0.01), nonwhite (22% vs. 19%; p < 0.0001), and current smokers (66% vs 61%; p < 0.0001). PFT acquisition was less likely in Veterans with alcohol and drug use disorders. Using logistic regression, Veterans who were women (Odds Ratio (OR) = 1.17 [95% confidence limit 1.03-1.32]), nonwhite (OR 1.12 [1.06-1.20]), and with a history of alcohol (OR = 1.07 [1.00-1.14]) or drug use disorders (OR = 1.15 [1.06-1.24]) were less likely to undergo PFTs.Though most Veterans hospitalized for COPD had PFTs prior to admission, PFTs are underutilized in Veterans who are: women, younger, nonwhite, and have alcohol or drug use disorders. These groups may be "at-risk" for delayed diagnosis or substandard COPD quality care.