Veterans Affairs Patients Research Articles

A Cohort Study of Lt. Col. Luke J. Weathers VA Medical Center Patients with Positive FIT and Incomplete GI Evaluation during the COVID-19 Pandemic.

The reasons for and incidence of delay in screening colonoscopies during the coronavirus disease 2019 (COVID-19) pandemic are of major public health interest. The risks and reasons for delay likely vary between public and private institutions. This research sought to analyze data regarding the completion of screening colonoscopies after a positive fecal immunochemical test (FIT) before and during the COVID-19 pandemic and the reasons for a delay in obtaining these results at the Lt. Col. Luke Weathers, Jr. Veterans Affairs Medical Center. The goals were to evaluate the institutional resilience and analyze the problems associated with this major healthcare crisis. This closed cohort study included all positive FITs from our local Veterans Affairs (VA) medical center from October 2019 to January 2020 and July 2020 to May 2021. A total of 115 VA patients with a positive FIT prepandemic and 157 VA patients with a positive FIT during the pandemic were included. Completion rates within 180 days were measured, and charts were reviewed to identify the reasons for lack of completion. Both community and local VA procedures for veterans were included. Univariate and multivariable analyses were applied to calculate odds ratios (ORs). The Pearson χ2 test was applied to calculate P values. VA patients' percentage of timely completion was lower pre-COVID-19 than it was during the pandemic, and the percentage of delayed completion was higher pre-COVID-19 than it was during the pandemic. Comparing patients who completed a colonoscopy with those who did not, increasing age had an OR of 0.947 (95% CI 0.920-0.975), and White race had an OR of 0.504 (95% CI 0.291-0.873). Evaluating delays in colonoscopy completion, VA colonoscopies versus referral to the community had an OR of 4.472 (95% CI 1.602-12.483), and pre-COVID-19 completion versus during COVID-19 had an OR of 4.663 (95% CI 1.727-12.594) with multivariable logistic regression. There was a statistically significant increase in timely colonoscopy completion during the study period when compared with the pre-COVID-19 period. The completion rate was higher at the Lt. Col. Luke Weathers, Jr. VA Medical Center than a large population average in 2020, possibly related to community colonoscopies and an aggressive case management system. In addition, increasing age and White race were associated with decreased colonoscopy completion. Predictors of an increased delay in colonoscopy completion included a pre-COVID-19 positive FIT and colonoscopies performed within the VA rather than being referred to providers in the community. A common reason for delay in all of the groups was patients declining intervention and delay/lack of referral.

Demographic, Social, Behavioral, and Clinical Characteristics Associated with Long-Term Opioid Therapy and Any Opioid Prescription in High-Risk VA Patients.

Social risks (individual social and economic conditions) have been implicated as playing a major role in the opioid epidemic and may be more prevalent in the most medically vulnerable patients. However, the extent to which specific social risks and other patient factors are associated with opioid use among high-risk patients has not been comprehensively assessed. To identify patient-reported and electronic health record (EHR)-derived demographic, social, behavioral/psychological, and clinical characteristics associated with opioid use in Veterans Affairs (VA) patients at high risk for hospitalization or death. We used generalized estimating equations to calculate the probability of long-term opioid therapy (LTOT) and the probability of filling any opioid prescription (regardless of duration) over five intervals during a 4-year period (12/2016-12/2020). Prospective cohort of 4121 medically high-risk VA patients not receiving palliative or end-of-life care, and who responded to a survey mailed to a nationally representative sample of 10,000 high-risk VA patients. Patient-reported demographic, social risk, behavioral/psychological, and clinical measures, and linked EHR-derived data. The average age was 69.8years, 6.7% were female, and 17.5% were Non-Hispanic Black race/ethnicity. The majority had diagnosed chronic pain (76.1%). LTOT and any opioid prescription were positively associated with the following: younger age, non-Hispanic White race/ethnicity (compared to non-Hispanic Black race/ethnicity), male sex assigned at birth (LTOT only), not being currently employed, current tobacco use, no alcohol use, higher grit (any opioid prescription only), functional limitations, diagnosed chronic pain, lower comorbidity burden (LTOT only), obesity class I or class II/III (any opioid prescription only), undergoing surgery (any opioid prescription only), and diagnosed cancer (any opioid prescription only). Multifactor screening could help identify individuals at elevated risk for adverse opioid-related outcomes and augment current multifaceted initiatives, as several social risks and patient characteristics were predictors of LTOT and any opioid prescription.

Understanding Pregnancy-Related Cardiovascular Disease Risk Communication and Management Among Women Veterans.

Background: Women veterans who experience certain conditions during pregnancy, such as gestational hypertension, pre-eclampsia, and gestational diabetes, are at increased risk of developing cardiovascular disease (CVD) later in life. Many women are unaware of this risk. Furthermore, women often face financial, socioeconomic, or physical challenges when trying to make healthy behavior modifications to reduce CVD risk. Objective: To examine Veterans' pregnancy-related cardiovascular (CV) risk conditions, risk identification, and risk communication with primary care providers. Research Design: Telephone/video interviews were conducted with female Veterans who had experienced at least one sex-specific CV risk condition during pregnancy. Interviews were recorded, transcribed, and analyzed using content analysis techniques. Major themes and representative quotes were derived. Results: Twenty-eight women Veterans participated in the study, conducted between October and December 2023. A majority of participants were racial/ethnic minorities, and the average age was 38. Four themes arose: (1) Veterans Affairs (VA) medical records may contain limited information regarding CV risk factors experienced during pregnancy; (2) strong relationships between Veterans and their VA primary care providers can facilitate management of CV risk factors following pregnancy; (3) some Veterans receive vague and/or conflicting recommendations for CV risk reduction following pregnancy; and (4) social determinants of health may play a key role in Veterans' ability to follow recommended CV risk reduction behaviors. Conclusions: Women Veterans with pregnancy-related CV risk conditions may not know that they are at increased risk of developing future CVD conditions, often because VA providers receive limited records from outside providers. Those who are aware often receive conflicting or vague recommendations to address these risk factors. When trying to follow CV health recommendations, many women have difficulty due to lack of finances, childcare, or safe areas. Future interventions should be aimed at improving access to medical records between outside and VA providers, patient education, and access to heart-healthy resources.

Provision of Home & Community Based Services to Veterans by Race, Rurality, and Neighborhood Deprivation Index.

Home and community-based services (HCBS) enable frail patients to remain at home. We examined whether there were neighborhood-deprivation, racial, or rural disparities in HCBS utilization provided to Veterans by the Department of Veterans Affairs (VA) or Medicare by comparing the adjusted utilization rate of a historically disadvantaged group with the predicted utilization rate had it been treated as the historically dominant group. Among the 2.7 million VA patients over 66 years old in 2019, 11.0% were Black, 39.2% lived in rural settings, 15.3%/29.2%/30.9%/24.7% lived in least/mild/moderate/most-deprived neighborhoods. On average, 11.2% received VA or Medicare HCBS. Veterans residing in more deprived neighborhoods had 0.11-0.95% higher adjusted probability of receiving HCBS than expected had they resided in the least deprived neighborhoods. Veterans residing in rural areas had 0-0.7% lower HCBS rates than expected had they been treated like urban Veterans. Black Veterans were 0.8-1.2% more likely to receive HCBS than expected had they been treated like White Veterans. Findings indicate that VA resources were equitably employed, aligning with probable HCBS needs, suggesting that VA's substantial and long-standing investment in HCBS for care of frail Veterans could serve as a model for other payers and providers in the U.S.

Weight management medications for chronic use in 37 veterans affairs medical centers-A medication use evaluation.

Controlled trials have demonstrated successful weight loss associated with certain weight management medications (WMMs). However, there are limited real-world data on prescribing patterns and efficacy and safety profiles of WMMs in Veterans Affairs (VA) patients. To evaluate: utilization patterns of WMMs liraglutide, naltrexone/bupropion, orlistat, phentermine, phentermine/topiramate, and semaglutide; weight loss at three, six, twelve, and more than 12 months; safety; and treatment barriers. A retrospective, cross-sectional medication use evaluation (MUE) was conducted using electronic health records of outpatient Veterans newly initiated on WMMs at 37 VA Medical Centers between 1 March 2020 and 31 March 2022. Chart review was used to identify WMM utilization and capture rates of clinical response, defined as 5% and 10% or greater weight loss at the final weight, adverse drug events (ADEs), non-adherence, and discontinuations. Site-specific surveys evaluated local practices and barriers. Among 1959 eligible Veterans, semaglutide, phentermine/topiramate, and orlistat were most frequently prescribed. The clinical response was highest among phentermine/topiramate, liraglutide, and semaglutide. Naltrexone/bupropion and phentermine demonstrated the highest and lowest ADE rates, respectively. Potential barriers to WMM utilization and successful treatment by site reports were drug shortages, patient perceptions of therapeutic course, personal preferences, and VA WMM use criteria. Smaller weight loss and higher discontinuation rates were observed relative to clinical trials. The MUE data allow for better assessment of benefits and risks for Veterans prescribed WMMs.

Using Natural Language Processing to develop risk-tier specific suicide prediction models for Veterans Affairs patients

Suicide is a leading cause of death. Suicide rates are particularly elevated among Department of Veterans Affairs (VA) patients. While VA has made impactful suicide prevention advances, efforts primarily target high-risk patients with documented suicide risk. This high-risk population accounts for less than 10% of VA patient suicide deaths. We previously evaluated epidemiological patterns among VA patients that had lower classified suicide risk and derived moderate- and low-risk groupings. Expanding upon VA's leading suicide prediction model, this study uses national VA data to refine high-, moderate-, and low-risk specific suicide prediction methods. We selected all VA patients who died by suicide in 2017 or 2018 (n = 4584), matching each case with five controls who remained alive during treatment year and shared suicide risk percentiles. We extracted all sample unstructured electronic health record notes, analyzed them using natural language processing, and applied machine-learning classification algorithms to develop risk-tier-specific predictive models. We calculated area under the curve (AUC) and suicide risk concentration to evaluate predictive accuracy and analyzed derived words. ResultsOur high-risk model (AUC = 0.621 (95% CI: 0.55–0.68)), moderate-risk (AUC = 0.669 (95% CI: 0.64–0.71)), and low-risk (AUC = 0.673 (95% CI: 0.63–0.72)) models offered significant predictive accuracy over VA's leading suicide prediction algorithm. Derived words varied considerably, the high-risk model including chronic condition service words, moderate-risk model including outpatient care, and low-risk model including acute condition care.Study suggests benefit of leveraging unstructured electronic health records and expands prediction resources for non-high-risk suicide decedents, an historically underserved population.

Characterizing Veteran suicide decedents that were not classified as high-suicide-risk.

Although the Department of Veterans Affairs (VA) has made important suicide prevention advances, efforts primarily target high-risk patients with documented suicide risk, such as suicidal ideation, prior suicide attempts, and recent psychiatric hospitalization. Approximately 90% of VA patients that go on to die by suicide do not meet these high-risk criteria and therefore do not receive targeted suicide prevention services. In this study, we used national VA data to focus on patients that were not classified as high-risk, but died by suicide. Our sample included all VA patients who died by suicide in 2017 or 2018. We determined whether patients were classified as high-risk using the VA's machine learning risk prediction algorithm. After excluding these patients, we used principal component analysis to identify moderate-risk and low-risk patients and investigated demographics, service-usage, diagnoses, and social determinants of health differences across high-, moderate-, and low-risk subgroups. High-risk (n = 452) patients tended to be younger, White, unmarried, homeless, and have more mental health diagnoses compared to moderate- (n = 2149) and low-risk (n = 2209) patients. Moderate- and low-risk patients tended to be older, married, Black, and Native American or Pacific Islander, and have more physical health diagnoses compared to high-risk patients. Low-risk patients had more missing data than higher-risk patients. Study expands epidemiological understanding about non-high-risk suicide decedents, historically understudied and underserved populations. Findings raise concerns about reliance on machine learning risk prediction models that may be biased by relative underrepresentation of racial/ethnic minorities within health system.

Motivators, Barriers, and Facilitators to Choosing Care in VA Facilities Versus VA-Purchased Care.

Many Veterans receive Department of Veterans Affairs (VA)-purchased care from non-VA facilities but little is known about factors that Veterans consider for this choice. Between May 2020 and August 2021, we surveyed VA-purchased care-eligible VA patients about barriers and facilitators to choosing where to receive care. We examined the association between travel time to their VA facility and their choice of VA-purchased care (VA-paid health care received in non-VA settings) versus VA facility and whether this association was modified by distrust. We received 1,662 responses and 692 (42%) chose a VA facility. Eighty percent reported quality care was in their top three factors that influenced their decision. Respondents with the highest distrust and who lived >1 hr from the nearest VA facility had the lowest predicted probability (PP) of choosing VA (PP 15%; 95% confidence interval: 10%-20%). Veterans value quality of care. VA and other health care systems should consider patient-centered ways to improve and publicize quality and reduce distrust.

Using natural language processing to evaluate temporal patterns in suicide risk variation among high-risk Veterans

Measuring suicide risk fluctuation remains difficult, especially for high-suicide risk patients. Our study addressed this issue by leveraging Dynamic Topic Modeling, a natural language processing method that evaluates topic changes over time, to analyze high-suicide risk Veterans Affairs patients’ unstructured electronic health records. Our sample included all high-risk patients that died (cases) or did not (controls) by suicide in 2017 and 2018. Cases and controls shared the same risk, location, and treatment intervals and received nine months of mental health care during the year before the relevant end date. Each case was matched with five controls. We analyzed case records from diagnosis until death and control records from diagnosis until matched case's death date. Our final sample included 218 cases and 943 controls. We analyzed the corpus using a Python-based Dynamic Topic Modeling algorithm. We identified five distinct topics, “Medication,” “Intervention,” “Treatment Goals,” “Suicide,” and “Treatment Focus.” We observed divergent change patterns over time, with pathology-focused care increasing for cases and supportive care increasing for controls. The case topics tended to fluctuate more than the control topics, suggesting the importance of monitoring lability. Our study provides a method for monitoring risk fluctuation and strengthens the groundwork for time-sensitive risk measurement.

Email recruitment for chronic pain clinical trials: results from the LAMP trial

BackgroundRecruitment for clinical trials and large-scale studies is challenging, especially for patients with complex conditions like chronic pain. Email recruitment has the potential to increase efficiency, to reduce costs, and to improve access for underrepresented patient populations. The objective of this study was to examine the effectiveness, efficiency, and equitability of email versus postal mail recruitment for the Learning to Apply Mindfulness to Pain (LAMP) study, a three-site clinical trial of mindfulness-based interventions for chronic pain.MethodsPatients with chronic pain diagnoses were recruited from three United States Department of Veterans Affairs (VA) facilities using the VA electronic health record (EHR). Recruitment materials were sent using either postal mail (n = 7986) or email (n = 19,333). Patients in the email recruitment group were also mailed introductory postcards before any emails. Mailing addresses and email addresses were obtained from the EHR. Effectiveness was measured by the response rate of patients who logged into the secure LAMP study website. Efficiency was measured by the number of days from when the recruitment materials were sent to when patients logged into the LAMP portal as well as the estimated costs of each recruitment approach. To assess equitability, we examined whether email recruitment was less effective for underrepresented populations, based on demographic information from the EHR.ResultsEffectiveness—unadjusted response rates were greater for email versus postal-mail recruitment (18.9% versus 6.3%), and adjusted response rates were over three times greater for email recruitment (RR = 3.5, 95% CI 3.1–3.8) based on a multivariable analysis controlling for age, gender, race, ethnicity, rurality, and site. Efficiency—email recruitment had a significantly lower mean response time (1 day versus 8 days) and a lower cost. Equity—email recruitment led to higher response rates for all subpopulations, including older, non-White, Hispanic, rural, and female Veterans.ConclusionsEmail recruitment is an effective, efficient, and equitable way to recruit VA patients to large-scale, chronic pain clinical trials.Trial registrationClinical Trial Registration Number: NCT04526158. Patient enrollment began on December 4, 2020.

Non-Muscle Invasive Bladder Cancer: Many More Patients Die With It Than Of It.

The National Cancer Institute SEER Program regularly publishes bladder-cancer specific survival statistics. However, this data is for all bladder cancers, and information for non-muscle invasive bladder cancer (NMIBC) is difficult to obtain. To quantify 5-year overall and bladder cancer-specific survival in a cohort of Department of Veterans Affairs (VA) patients diagnosed with NMIBC. We identified VA patients diagnosed with NMIBC who underwent a transurethral resection from 2003-2013. The patient demographics and Charlson Comorbidity Index were categorized. We acquired the patients' date of death from the Veterans Health Administration's Death Ascertainment File and their cause of death from the Mortality Data Repository. We calculated Kaplan Meier estimates of survival. A total of 27,008 patients were included; median age was 69 and almost all were male (99%). The median comorbidity score was 4. The most prevalent comorbidity indicators included Chronic Pulmonary Disease (48%), cancer other than Bladder (41%), and diabetes (40%). This cohort was found to have a 5-year overall survival of 68% (99% CI 67% -69%) and a 5-year bladder cancer-specific survival of 93% (99% CI 92% -94%). The 5-year bladder cancer-specific survival in patients diagnosed with non-muscle invasive bladder cancer is substantially higher than the 5-year overall survival. This difference may be related to the severity and number of comorbidities that patients in this population must manage. This warrants further research into the necessity of currently recommended high-intensity cancer surveillance for individuals with NMIBC.

Contribution of Potentially Inappropriate Medications to Polypharmacy-Associated Risk of Mortality in Middle-Aged Patients: A National Cohort Study.

The role of potentially inappropriate medications (PIMs) in mortality has been studied among those 65years or older. While middle-aged individuals are believed to be less susceptible to the harms of polypharmacy, PIMs have not been as carefully studied in this group. To estimate PIM-associated risk of mortality and evaluate the extent PIMs explain associations between polypharmacy and mortality in middle-aged patients, overall and by sex and race/ethnicity. Observational cohort study. Department of Veterans Affairs (VA), the largest integrated healthcare system in the US. Patients aged 41 to 64 who received a chronic medication (continuous use of ≥ 90days) between October 1, 2008, and September 30, 2017. Patients were followed for 5years until death or end of study period (September 30, 2019). Time-updated polypharmacy and hyperpolypharmacy were defined as 5-9 and ≥ 10 chronic medications, respectively. PIMs were identified using the Beers criteria (2015) and were time-updated. Cox models were adjusted for demographic, behavioral, and clinical characteristics. Of 733,728 patients, 676,935 (92.3%) were men, 479,377 (65.3%) were White, and 156,092 (21.3%) were Black. By the end of follow-up, 104,361 (14.2%) patients had polypharmacy, 15,485 (2.1%) had hyperpolypharmacy, and 129,992 (17.7%) were dispensed ≥ 1 PIM. PIMs were independently associated with mortality (HR 1.11, 95% CI 1.04-1.18). PIMs also modestly attenuated risk of mortality associated with polypharmacy (HR 1.07, 95% CI 1.03-1.11 before versus HR 1.05, 95% CI 1.01-1.09 after) and hyperpolypharmacy (HR 1.18, 95% CI 1.09-1.28 before versus HR 1.12, 95% CI 1.03-1.22 after). Patterns varied when stratified by sex and race/ethnicity. The predominantly male VA patient population may not represent the general population. PIMs were independently associated with increased mortality, and partially explained polypharmacy-associated mortality in middle-aged people. Other mechanisms of injury from polypharmacy should also be studied.

Evaluating the impact of translational research enrollment on the patient care experience of Veterans with prostate cancer who receive care through the Veterans Affairs (VA) healthcare system.

e23210 Background: Veterans with cancer represent a unique subset of patients with distinct exposure histories and cancer epidemiology. Translational research studies that incorporate Veteran-derived biospecimens are therefore critical to advance our understanding of Veteran cancer biology and improve treatment options for Veterans with cancer. Biospecimen-based translational studies also offer an opportunity to enhance the Veteran care experience by enabling Veterans to directly contribute to cancer research efforts. While the biologic benefits of biospecimen research have been well established, the benefit of translational research on the Veteran care experience has yet to be defined. In this study, we evaluated: 1. Whether Veteran enrollment in a biospecimen-based prostate cancer research study improved their VA patient care experience and satisfaction and 2. Whether a VA-based data analyst tool could be used to optimize patient enrollment in translational research studies. Methods: Beginning in January, 2022, Veterans with a diagnosis of prostate cancer receiving care at the William S. Middleton VA were enrolled in a translational research study that collected blood and tissue biospecimens for subsequent investigation and analysis. After at least 30 days of enrollment, subjects were sent an anonymous survey inquiring about how participation in the translational research study impacted their VA care experience and healthcare satisfaction. To optimize enrollment in the study, an ICD-9 code search function was employed within the medical record database to readily identify eligible VA clinic patients based on an active prostate cancer diagnosis. Descriptive analyses were performed using Prism statistical software. Results: Nearly all Veterans who responded to the questionnaire agreed that participation in translational research was a meaningful experience that increased their satisfaction with their VA medical care. In addition, a vast majority of Veterans surveyed felt that their research participation could help improve care for other Veterans, and most expressed willingness to participate in future VA research opportunities. In a secondary analysis, our ICD-9 search function accurately identified eligible VA clinic patients with a prostate cancer diagnosis, and implementation of this tool has saved approximately 30 minutes of weekly physician and research coordinator work compared to manual chart review. Conclusions: Veteran enrollment in translational research studies provides a meaningful experience for Veterans that can lead to increased satisfaction with the VA healthcare system. Future VA initiatives to improve the Veteran care experience should focus on expanding translational research opportunities for Veterans as well as addressing potential barriers to enrollment.

CO211 Gout Epidemiology, Pharmacotherapy, Healthcare Utilization, and Outcomes for United States Veterans Affairs Patients From 2016 to 2022

CO211 Gout Epidemiology, Pharmacotherapy, Healthcare Utilization, and Outcomes for United States Veterans Affairs Patients From 2016 to 2022

Epidemiology and Racial Differences of EoE Patients in a U.S. Veterans Population.

Eosinophilic esophagitis (EoE) is increasing in prevalence but there is a lack of population-based studies. We sought to determine the prevalence, demographics, and associated atopic diseases in the Veterans Affairs (VA) population. A nationwide analysis of data from the VA patient population was done using a Veterans Health Administration database. EoE was identified using ICD9 (530.13) and ICD10 (K20.0) codes from October 2008 to June 2020. Demographic data, smoking status, BMI, treatment, and ICD codes for atopic diagnoses were collected. Two sample proportion z-tests, Chi-square tests, two-sample t tests, and one-way ANOVA were used to assess associations across demographic categories. We identified a total of 11,775 patients with an EoE diagnosis: 91% male, 83% White, 8.6% Black, and 5% were of Hispanic ethnicity. The prevalence of EoE increased over time. At diagnosis, the mean age was 48.5years overall, 51.6years for Black patients, 45.3years for Hispanic patients, and 48.2years for Whites. Dysphagia was the most common symptom overall, but a higher percentage of Blacks and females were found to report chest pain (p < 0.0001, h = 0.32). With the exception of urticaria and atopic dermatitis, both Blacks and Hispanics had a higher incidence of atopic conditions compared to other races and ethnicities (p < 0.0001). While EoE is seen primarily in White males, our study shows that a notable percentage of patients were Black or Hispanic, suggesting that EoE should be considered in non-white patients. The later age of diagnosis in this group could represent a lack of awareness about EoE among non-white patients. More research is needed to study these associations.

Associations Between a Primary Care-Delivered Alcohol-Related Brief Intervention and Subsequent Opioid-Related Outcomes.

The co-occurrence of unhealthy alcohol use and opioid misuse is high and associated with increased rates of overdose, emergency health care utilization, and death. The current study examined whether receipt of an alcohol-related brief intervention is associated with reduced risk of negative downstream opioid-related outcomes. This retrospective cohort study included all VISN-6 Veterans Affairs (VA) patients with Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) screening results (N=492,748) from 2014 to 2019. Logistic regression was used to examine the association between documentation of an alcohol-related brief intervention and probability of a new 1) opioid prescription, 2) opioid use disorder (OUD) diagnosis, or 3) opioid-related hospitalization in the following year, controlling for demographic and clinical covariates. Of the veterans, 13% (N=63,804) had "positive" AUDIT-C screen results. Of those, 72% (N=46,216) had a documented alcohol-related brief intervention. Within 1 year, 8.5% (N=5,430) had a new opioid prescription, 1.1% (N=698) had a new OUD diagnosis, and 0.8% (N=499) had a new opioid-related hospitalization. In adjusted models, veterans with positive AUDIT-C screen results who did not receive an alcohol-related brief intervention had higher odds of new opioid prescriptions (adjusted odds ratio [OR]=1.10, 95% CI=1.03-1.17) and new OUD diagnoses (adjusted OR=1.19, 95% CI=1.02-1.40), while new opioid-related hospitalizations (adjusted OR=1.19, 95% CI=0.99-1.44) were higher although not statistically significant. Removal of medications for OUD (MOUD) did not impact associations. All outcomes were significantly associated with an alcohol-related brief intervention in unadjusted models. The VA's standard alcohol-related brief intervention is associated with subsequent lower odds of a new opioid prescription or a new OUD diagnosis. Results suggest a reduction in a cascade of new opioid-related outcomes from prescriptions through hospitalizations.

Mining clinical data for novel medications to treat alcohol use disorder

BackgroundAlcohol 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. MethodsWe 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. ResultsMedications 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. ConclusionMost 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.

Longitudinal assessment of health-related quality of life and clinical outcomes with at home advanced pneumatic compression treatment of lower extremity lymphedema

ObjectiveThis prospective, longitudinal, pragmatic study describes at home treatment with a proprietary advanced pneumatic compression device (APCD) for patients with lower extremity lymphedema (LED). MethodsFollowing institutiona review board approval, four participating Veterans Affairs centers enrolled LED patients from 2016 to 2022. The primary outcome measures were health-related quality of life (HR-QoL) questionnaires (lymphedema quality of life-leg and the generic SF-36v2) obtained at baseline and 12, 24, and 52 weeks. The secondary outcome measures were limb circumference, cellulitis events, skin quality, and compliance with APCD and other compression therapies. ResultsBecause a portion of the trial was conducted during the coronavirus disease 2019 pandemic, 179 patients had 52 weeks of follow-up, and 143 had complete measurements at all time points. The baseline characteristics were a mean age of 66.9 ± 10.8 years, 91% were men, and the mean body mass index was 33.8 ± 6.9 kg/m2. LED was bilateral in 92.2% of the patients. Chronic venous insufficiency or phlebolymphedema was the most common etiology of LED (112 patients; 62.6%), followed by trauma or surgery (20 patients; 11.2%). Cancer treatment as a cause was low (4 patients; 2.3%). Patients were classified as having International Society for Lymphology (ISL) stage I (68.4%), II (27.6%), or III (4.1%). Of the primary outcome measures, significant improvements were observed in all lymphedema quality of life-leg domains of function, appearance, symptoms, and emotion and the overall score after 12 weeks of treatment (P < .0001) and through 52 weeks of follow-up. The SF-36v2 demonstrated significant improvement in three domains at 12 weeks and in the six domains of physical function, bodily pain, physical component (P < .0001), social functioning (P = .0181), role-physical (P < .0005), and mental health (P < .0334) at 52 weeks. An SF-36v2 score <40 indicates a substantial reduction in HR-QoL in LED patients compared with U.S. norms. Regarding the secondary outcome measures at 52 weeks, compared with baseline, the mean limb girth decreased by 1.4 cm (P < .0001). The maximal reduction in mean limb girth was 1.9 cm (6.0%) at 12 weeks in ISL stage II and III limbs. New episodes of cellulitis in patients with previous episodes (21.4% vs 6.1%, P = .001) were reduced. The 75% of patients with skin hyperpigmentation at baseline decreased to 40% (P < .01) at 52 weeks. At 52 weeks, compliance, defined as use for 5 to 7 days per week, was reported for the APCD by 72% and for elastic stockings by 74%. ConclusionsThis longitudinal study of Veterans Affairs patients with LED demonstrated improved generic and disease-specific HR-QoL through 52 weeks with at home use of an APCD. Limb girth, cellulitis episodes, and skin discoloration were reduced, with excellent compliance.

VA Providers' Perceptions of Cannabis Use Policies in a Legalized and Nonlegalized State.

Background: Providers in the Department of Veterans Affairs (VA) system are caught between two opposing sets of laws regarding cannabis and cannabidiol (CBD) use by their patients. As VA is a federal agency, it must abide by federal regulations, including that the Food and Drug Administration classifies cannabis as a Schedule 1 drug and therefore cannot recommend or help Veterans obtain it. Meanwhile, 38 states have passed legislation, legalizing medical use of cannabis. Objective: The goal of this project is to examine how VA providers understand state and federal laws, and VA policies about cannabis and CBD use, and to learn more about providers' experiences with patients who use cannabis and CBD within a legalized and nonlegalized state. Materials and Methods: We identified 432 health care providers from two VA facilities in northern Illinois (IL) where medical and recreational cannabis is legal, and two VA facilities in southern Wisconsin (WI) where medical and recreational cannabis is illegal. Participants were invited via e-mail to complete an anonymous online survey, including 31 closed- and open-ended questions about knowledge of state and federal laws and VA policies regarding cannabis and CBD oil, thoughts about the value of cannabis or CBD for treating medical conditions, and behaviors regarding cannabis use by their patients. Results: We received 50 responses (IL N=20, WI N=30). Providers in both states were knowledgeable about cannabis laws in their state but unsure whether they could recommend cannabis. There were more providers who were unclear if they could have a conversation about cannabis with their VA patients in WI compared with IL. Providers were more likely to agree than disagree that cannabis can be beneficial, χ2 (1, 49)=4.74, p=0.030. Providers in both states (81.6%) believe cannabis use is acceptable for end-of-life care, but responses varied for other conditions and symptoms. Discussion: Findings suggest that VA providers could use more guidance on what is allowable within their VA facilities and how state laws affect their practice. Education about safety related to cannabis and other drug interactions would be helpful. There is limited information about possible interactions, warranting future research.

Exploring variations in recommended first-choice therapy for complicated urinary tract infections in males: Insights from outpatient settings across age, race, and ethnicity.

There are known disparities in the treatment of infectious diseases. However, disparities in treatment of complicated urinary tract infections (UTIs) are largely uninvestigated. We characterized UTI treatment among males in Veterans Affairs (VA) outpatient settings by age, race, and ethnicity and identified demographic characteristics predictive of recommended first-choice antibiotic therapy. We conducted a national, retrospective cohort study of male VA patients diagnosed with a UTI and dispensed an outpatient antibiotic from January 2010 through December 2020. Recommended first-choice therapy for complicated UTI was defined as use of a recommended first-line antibiotic drug choice regardless of area of involvement (ciprofloxacin, levofloxacin, or sulfamethoxazole/trimethoprim) and a recommended duration of 7 to 10 days of therapy. Multivariable models were used to identify demographic predictors of recommended first-choice therapy (adjusted odds ratio [aOR] > 1). We identified a total of 157,898 males diagnosed and treated for a UTI in the outpatient setting. The average antibiotic duration was 9.4 days (±standard deviation [SD] 4.6), and 47.6% of patients were treated with ciprofloxacin, 25.1% with sulfamethoxazole/trimethoprim, 7.6% with nitrofurantoin, and 6.6% with levofloxacin. Only half of the male patients (50.6%, n = 79,928) were treated with recommended first-choice therapy (first-line drug choice and appropriate duration); 77.6% (n = 122,590) were treated with a recommended antibiotic choice and 65.9% (n = 104,070) with a recommended duration. Age 18-49 years (aOR 1.07, 95% confidence interval [CI] 1.03-1.11) versus age ≥65 years was the only demographic factor predictive of recommended first-choice therapy. Nearly half of the patients included in this study did not receive recommended first-choice therapies; however, racial and ethnic disparities were not identified. Underutilization of recommended first-choice antibiotic therapy in complicated UTIs continues to be an area of focus for antimicrobial stewardship programs.