Leveraging Electronic Health Records to Assess Residential Mobility Among Veterans in the Veterans Health Administration.

BACKGROUND: Residential mobility, or a change in residence, can influence health care utilization and outcomes. Health systems can leverage their patients' residential addresses stored in their electronic health records (EHRs) to better understand the relationships among patients' residences, mobility, and health. The Veteran Health Administration (VHA), with a unique nationwide network of health care systems and integrated EHR, holds greater potential for examining these relationships. METHODS: We conducted a cross-sectional analysis to examine the association of sociodemographics, clinical conditions, and residential mobility. We defined residential mobility by the number of VHA EHR residential addresses identified for each patient in a 1-year period (1/1-12/31/2018), with 2 different addresses indicating one move. We used generalized logistic regression to model the relationship between a priori selected correlates and residential mobility as a multinomial outcome (0, 1, ≥2 moves). RESULTS: In our sample, 84.4% (n=3,803,475) veterans had no move, 13.0% (n=587,765) had 1 move, and 2.6% (n=117,680) had ≥2 moves. In the multivariable analyses, women had greater odds of moving [aOR=1.11 (95% CI: 1.10,1.12) 1 move; 1.27 (1.25,1.30) ≥2 moves] than men. Veterans with substance use disorders also had greater odds of moving [aOR=1.26 (1.24,1.28) 1 move; 1.77 (1.72,1.81) ≥2 moves]. DISCUSSION: Our study suggests about 16% of veterans seen at VHA had at least 1 residential move in 2018. VHA data can be a resource to examine relationships between place, residential mobility, and health.

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

BACKGROUND: The role of potentially inappropriate medications (PIMs) in mortality has been studied among those 65 years 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. OBJECTIVE: 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. DESIGN: Observational cohort study. SETTING: Department of Veterans Affairs (VA), the largest integrated healthcare system in the US. PARTICIPANTS: Patients aged 41 to 64 who received a chronic medication (continuous use of ≥ 90 days) between October 1, 2008, and September 30, 2017. MEASUREMENT: Patients were followed for 5 years 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. RESULTS: 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. LIMITATIONS: The predominantly male VA patient population may not represent the general population. CONCLUSION: 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.

A roadmap to artificial intelligence (AI): Methods for designing and building AI ready data to promote fairness.

OBJECTIVES: We evaluated methods for preparing electronic health record data to reduce bias before applying artificial intelligence (AI). METHODS: We created methods for transforming raw data into a data framework for applying machine learning and natural language processing techniques for predicting falls and fractures. Strategies such as inclusion and reporting for multiple races, mixed data sources such as outpatient, inpatient, structured codes, and unstructured notes, and addressing missingness were applied to raw data to promote a reduction in bias. The raw data was carefully curated using validated definitions to create data variables such as age, race, gender, and healthcare utilization. For the formation of these variables, clinical, statistical, and data expertise were used. The research team included a variety of experts with diverse professional and demographic backgrounds to include diverse perspectives. RESULTS: For the prediction of falls, information extracted from radiology reports was converted to a matrix for applying machine learning. The processing of the data resulted in an input of 5,377,673 reports to the machine learning algorithm, out of which 45,304 were flagged as positive and 5,332,369 as negative for falls. Processed data resulted in lower missingness and a better representation of race and diagnosis codes. For fractures, specialized algorithms extracted snippets of text around keywork "femoral" from dual x-ray absorptiometry (DXA) scans to identify femoral neck T-scores that are important for predicting fracture risk. The natural language processing algorithms yielded 98% accuracy and 2% error rate The methods to prepare data for input to artificial intelligence processes are reproducible and can be applied to other studies. CONCLUSION: The life cycle of data from raw to analytic form includes data governance, cleaning, management, and analysis. When applying artificial intelligence methods, input data must be prepared optimally to reduce algorithmic bias, as biased output is harmful. Building AI-ready data frameworks that improve efficiency can contribute to transparency and reproducibility. The roadmap for the application of AI involves applying specialized techniques to input data, some of which are suggested here. This study highlights data curation aspects to be considered when preparing data for the application of artificial intelligence to reduce bias.

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.

Temporal and Geographic Patterns of Documentation of Sexual Orientation and Gender Identity Keywords in Clinical Notes.

OBJECTIVE: Disclosure of sexual orientation and gender identity correlates with better outcomes, yet data may not be available in structured fields in electronic health record data. To gain greater insight into the care of sexual and gender-diverse patients in the Veterans Health Administration (VHA), we examined the documentation patterns of sexual orientation and gender identity through extraction and analyses of data contained in unstructured electronic health record clinical notes. METHODS: Salient terms were identified through authoritative vocabularies, the research team's expertise, and frequencies, and the use of consistency in VHA clinical notes. Term frequencies were extracted from VHA clinical notes recorded from 2000 to 2018. Temporal analyses assessed usage changes in normalized frequencies as compared with nonclinical use, relative growth rates, and geographic variations. RESULTS: Over time most terms increased in use, similar to Google ngram data, especially after the repeal of the "Don't Ask Don't Tell" military policy in 2010. For most terms, the usage adoption consistency also increased by the study's end. Aggregated use of all terms increased throughout the United States. CONCLUSION: Term usage trends may provide a view of evolving care in a temporal continuum of changing policy. These findings may be useful for policies and interventions geared toward sexual and gender-diverse individuals. Despite the lack of structured data, the documentation of sexual orientation and gender identity terms is increasing in clinical notes.

Changes in opioid prescribing in veterans with headache during the COVID-19 pandemic: A regression discontinuity in time analysis.

OBJECTIVE: To determine changes in opioid prescribing among veterans with headaches during the coronavirus disease of 2019 (COVID-19) pandemic by comparing the stay-at-home phase (March 15 to May 30, 2020) and the reopening phase (May 31 to December 31, 2020). BACKGROUND: Opioid prescribing for chronic pain has declined substantially since 2016; however, changes in opioid prescribing during the COVID-19 pandemic among veterans with headaches remain unknown. METHODS: This retrospective cohort study utilized regression discontinuity in time and difference-in-differences design to analyze veterans aged ≥18 years with a previous diagnosis of headache disorders and an outpatient visit to the Veterans Health Administration (VHA) during the study period. We measured the weekly number of opioid prescriptions, the number of days supplied, the daily dose in morphine milligram equivalents (MMEs), and the number of prescriptions with ≥50 morphine equivalent daily doses (MEDD). RESULTS: A total of 81,376 veterans were analyzed with 589,950 opioid prescriptions. The mean (SD) age was 51.6 (13.5) years, 57,242 (70.3%) were male, and 53,464 (65.7%) were White. During the pre-pandemic period, 323.6 opioid prescriptions (interquartile range 292.1-325.8) were dispensed weekly, with an median (IQR) of 24.1 (24.0-24.4) days supplied and 31.8 (31.2-32.5) MMEs. Transition to stay-at-home was associated with a 7.7% decrease in the number of prescriptions (incidence rate ratio [IRR] 1.077, 95% confidence interval [CI] 0.866-0.984) and a 9.8% increase in days supplied (IRR 1.098, 95% CI 1.078-1.119). Similar trends were observed during the reopening period. Subgroup analysis among veterans on long-term opioid therapy also revealed 1.7% and 1.4% increases in days supplied during the stay-at-home (IRR 1.017, 95% CI 1.009-1.025) and reopening phase (IRR 1.014, 95% CI 1.007-1.021); however, changes in the total number of prescriptions, MME/day, or the number of prescriptions >50 MEDD were insignificant. CONCLUSION: Prescription opioid access was maintained for veterans within VHA during the pandemic. The de-escalation of opioid prescribing observed prior to the pandemic was not seen in our study.

Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV.

PURPOSE: Hepatic steatosis (fatty liver disease) affects 25% of the world's population, particularly people with HIV (PWH). Pharmacoepidemiologic studies to identify medications associated with steatosis have not been conducted because methods to evaluate liver fat within digitized images have not been developed. We determined the accuracy of a deep learning algorithm (automatic liver attenuation region-of-interest-based measurement [ALARM]) to identify steatosis within clinically obtained noncontrast abdominal CT images compared to manual radiologist review and evaluated its performance by HIV status. METHODS: We performed a cross-sectional study to evaluate the performance of ALARM within noncontrast abdominal CT images from a sample of patients with and without HIV in the US Veterans Health Administration. We evaluated the ability of ALARM to identify moderate-to-severe hepatic steatosis, defined by mean absolute liver attenuation <40 Hounsfield units (HU), compared to manual radiologist assessment. RESULTS: Among 120 patients (51 PWH) who underwent noncontrast abdominal CT, moderate-to-severe hepatic steatosis was identified in 15 (12.5%) persons via ALARM and 12 (10%) by radiologist assessment. Percent agreement between ALARM and radiologist assessment of absolute liver attenuation <40 HU was 95.8%. Sensitivity, specificity, positive predictive value, and negative predictive value of ALARM were 91.7% (95%CI, 51.5%-99.8%), 96.3% (95%CI, 90.8%-99.0%), 73.3% (95%CI, 44.9%-92.2%), and 99.0% (95%CI, 94.8%-100%), respectively. No differences in performance were observed by HIV status. CONCLUSIONS: ALARM demonstrated excellent accuracy for moderate-to-severe hepatic steatosis regardless of HIV status. Application of ALARM to radiographic repositories could facilitate real-world studies to evaluate medications associated with steatosis and assess differences by HIV status.

Trajectory of blood pressure after initiating anti-calcitonin gene-related peptide treatment of migraine: a target trial emulation from the veterans health administration.

BACKGROUND: Calcitonin gene-related peptide (CGRP) is involved in migraine pathophysiology and blood pressure regulation. Although clinical trials have established the cardio-cerebrovascular safety profile of anti-CGRP treatment, limited high-quality real-world evidence exists on its long-term effects on blood pressure (BP). To address this gap, we examined the safety of anti-CGRP treatment on BP in patients with migraine headache in the Veterans Health Administration (VHA). METHODS: We emulated a target trial of patients who initiated anti-CGRP treatment or topiramate for migraine prevention between May 17th, 2018 and February 28th, 2023. We calculated stabilized inverse probability weights to balance between groups and then used weighted linear mixed-effect models to estimate the systolic and diastolic BP changes over the study period. For patients without hypertension at baseline, we estimated the cumulative incidence of hypertension using Kaplan-Meier curve. We also used weight mixed-effect Poisson model to estimate the number of antihypertension medications for patients with hypertension at baseline. RESULTS: This analysis included 69,589 patients and 554,437 blood pressure readings. of these, 18,880 patients received anti-CGRP treatment, and they were more likely to be women, have a chronic migraine diagnosis and higher healthcare utilization than those received topiramate. Among patients without hypertension at baseline, we found no significant differences in systolic BP changes over the four-year follow-up between anti-CGRP (slope [standard error, SE] = 0.48[0.06]) and topiramate treated patients (slope[SE] = 0.39[0.04]). The incidence of hypertension was similar for anti-CGRP and topiramate group (4.4 vs 4.3 per 100 person-years). Among patients with hypertension at baseline who initiated anti-CGRP treatment, we found a small but persistent effect on exacerbating hypertension during the first four years of treatment, as evidenced by a significant annual 3.7% increase in the number of antihypertensive medications prescribed (RR = 1.037, 95%CI 1.025-1.048). CONCLUSIONS: Our findings suggest that anti-CGRP treatment is safe regarding blood pressure in patients without hypertension. However, for those with baseline hypertension, anti-CGRP treatment resulted in a small but persistent increase in the number of antihypertensives, indicating an exacerbation of hypertension. Future studies are needed to evaluate the cardio-cerebrovascular safety of anti-CGRP treatment beyond the first four years.

Twelve-Month Retention in Opioid Agonist Treatment for Opioid Use Disorder Among Patients With and Without HIV.

Although opioid agonist therapy (OAT) is associated with positive health outcomes, including improved HIV management, long-term retention in OAT remains low among patients with opioid use disorder (OUD). Using data from the Veterans Aging Cohort Study (VACS), we identify variables independently associated with OAT retention overall and by HIV status. Among 7,334 patients with OUD, 13.7% initiated OAT, and 27.8% were retained 12-months later. Likelihood of initiation and retention did not vary by HIV status. Variables associated with improved likelihood of retention included receiving buprenorphine (relative to methadone), receiving both buprenorphine and methadone at some point over the 12-month period, or diagnosis of HCV. History of homelessness was associated with a lower likelihood of retention. Predictors of retention were largely distinct between patients with HIV and patients without HIV. Findings highlight the need for clinical, systems, and research initiatives to better understand and improve OAT retention.

Association Between Potentially Inappropriate Medications and 30-Day Post-Hospital Discharge Outcomes in US Veterans.

BACKGROUND: Potentially inappropriate medication (PIMs) use is common in older inpatients and it may lead to increased risk of adverse drug events. OBJECTIVES: To examine prevalence of PIMs at hospital discharge and its contribution to health care utilization and mortality within 30-days of hospital discharge. METHODS: This was a prospective cohort of 117 570 veterans aged ≥65 years and hospitalized in 2013. PIMs at discharge were categorized into central nervous system acting (CNS) and non-CNS. Outcomes within 30-days of hospital discharge were: (1) time to first acute care hospital readmission, and all-cause mortality, (2) an emergency room visit, and (3) ≥3 primary care clinic visits. RESULTS: The cohort's mean age was 74.3 years (SD 8.1), with 51.3% exposed to CNS and 62.8% to non-CNS PIMs. Use of CNS and non-CNS PIMs, respectively, was associated with a reduced risk of readmission, with an adjusted hazard ratio (aHR) of 0.93 (95% CI = 0.89-0.96) for ≥2 (vs 0) CNS PIMs and an aHR of 0.85 (95% CI = 0.82-0.88) for ≥2 (vs 0) non-CNS PIMs. Use of CNS PIMs (≥2 vs 0) was associated with increased risk of mortality (aHR = 1.37 [95% CI = 1.25-1.51]), whereas non-CNS PIMs use was associated with a reduced risk of mortality (aHR = 0.75 [95% CI = 0.69-0.82]). CONCLUSION AND RELEVANCE: PIMs were highly common in this veteran cohort, and the association with outcomes differed by PIMs. Thus, it is important to consider whether PIMs are CNS acting to optimize short-term posthospitalization outcomes.

Risk Factors Associated with Healthcare Utilization for Spine Pain.

OBJECTIVE: This study examined potential risk factors associated with healthcare utilization among patients with spine (i.e., neck and back) pain. METHODS: A two-stage sampling approach examined spine pain episodes of care among veterans with a yearly outpatient visit for six consecutive years. Descriptive and bivariate statistics, followed by logistic regression analyses, examined baseline characteristics of veterans with new episodes of care who either continued or discontinued spine pain care. A multivariable logistic regression model examined correlates associated with seeking continued spine pain care. RESULTS: Among 331,908 veterans without spine pain episodes of care during the 2-year baseline observation period, 16.5% (n = 54,852) had a new episode of care during the following 2-year observation period. Of those 54,852 veterans, 37,025 had an outpatient visit data during the final 2-year follow-up period, with 53.7% (n = 19,865) evidencing continued spine pain care. Those with continued care were more likely to be overweight or obese, non-smokers, Army veterans, have higher education, and had higher rates of diagnoses of all medical and mental health conditions examined at baseline. Among several important findings, women had 13% lower odds of continued care during the final 2-year observation period, OR 0.87 (0.81, 0.95). CONCLUSIONS: A number of important demographics and clinical correlates were associated with increased likelihood of seeking new and continued episodes of care for spine pain; however, further examination of risk factors associated with healthcare utilization for spine pain is indicated.

Posttraumatic Stress Disorder, Antidepressant Use, and Hemorrhagic Stroke in Young Men and Women: A 13-Year Cohort Study.

BACKGROUND AND PURPOSE: Antidepressants are commonly prescribed for posttraumatic stress disorder (PTSD) and may increase the risk of bleeding, including hemorrhagic stroke. METHODS: We prospectively examined independent effects of PTSD, selective serotonin and norepinephrine reuptake inhibitors (SSRI and SNRI) on the risk of incident hemorrhagic stroke in a nationwide sample of 1.1 million young and middle-aged veterans. Time-varying multivariate Cox models were used to examine hemorrhagic stroke risk by PTSD status and use of SSRI or SNRI while adjusting for demographics, lifestyle factors, stroke, and psychiatric comorbidities. Sensitivity analyses controlled for health care utilization. RESULTS: During 13 years of follow-up (2.14 years on average), 507 patients (12% women) suffered a hemorrhagic stroke. The overall incidence rate was 1.70 events per 10 000-person years. In unadjusted models, PTSD was associated with an 82% greater risk of new-onset hemorrhagic stroke (hazard ratio [HR], 1.82 [95% CI, 1.48-2.24]), SSRI use was associated with a >2-fold risk (HR, 2.02 [95% CI, 1.66-2.57]), and SNRI use was associated with a 52% greater risk (HR, 1.52 [95% CI, 1.08-2.16]). In fully adjusted models, effects of PTSD and SNRI were attenuated (adjusted HR, 1.03 [95% CI, 0.81-1.34]; adjusted HR, 1.19 [95% CI, 0.83-1.71]), but SSRI use remained associated with a 45% greater risk of hemorrhagic stroke (adjusted HR, 1.45 [95% CI, 1.13-1.85]). Hypertension, drug abuse, and alcohol abuse were also associated with increased stroke risk. Nonobesity and being non-Hispanic were protective factors. In sensitivity analyses, health care utilization was a small but significant predictor of stroke. CONCLUSIONS: In the largest known investigation of PTSD and antidepressant-associated risk for hemorrhagic stroke in young adults, use of SSRIs, but neither PTSD nor SNRIs were independently associated with incident stroke. SNRIs may be preferable for treating PTSD and comorbid conditions, although pursuing other modifiable risk factors and non-pharmacological treatments for PTSD also remains essential.

Use of Proton Pump Inhibitors Increases Risk of Incident Kidney Stones.

BACKGROUND AND AIMS: Proton pump inhibitors (PPIs) are widely prescribed and have effects on gut ion absorption and urinary ion concentrations. PPIs might therefore protect against or contribute to development of kidney stones. We investigated the association between PPI use and kidney stones. METHODS: We performed a retrospective study using data from the Women's Veteran's Cohort Study, which comprised men and women, from October 1, 1999 through September 30, 2017. We collected data from 465,891 patients on PPI usage over time, demographics, laboratory results, comorbidities, and medication usage. Time-varying Cox proportional hazards and propensity matching analyses determined risk of PPI use and incident development of kidney stones. Use of histamine-2 receptor antagonists (H2RAs) was measured and levothyroxine use was a negative control exposure. RESULTS: PPI use was associated with kidney stones in the unadjusted analysis, with PPI use as a time-varying variable (hazard ratio [HR], 1.74; 95% CI, 1.67-1.82), and persisted in the adjusted analysis (HR, 1.46; CI, 1.38-1.55). The association was maintained in a propensity score-matched subset of PPI users and nonusers (adjusted HR, 1.25; CI 1.19-1.33). Increased dosage of PPI was associated with increased risk of kidney stones (HR, 1.11; CI, 1.09-1.14 for each increase in 30 defined daily doses over a 3-month period). H2RAs were also associated with increased risk (adjusted HR, 1.47; CI 1.31-1.64). We found no association, in adjusted analysis, of levothyroxine use with kidney stones (adjusted HR, 1.06; CI 0.94-1.21). CONCLUSIONS: In a large cohort study of veterans, we found PPI use to be associated with a dose-dependent increase in risk of kidney stones. H2RA use also has an association with risk of kidney stones, so acid suppression might be an involved mechanism. The effect is small and should not change prescribing for most patients.

Alcohol Use and Antiretroviral Adherence Among Patients Living with HIV: Is Change in Alcohol Use Associated with Change in Adherence?

Alcohol use increases non-adherence to antiretroviral therapy (ART) among persons living with HIV (PLWH). Dynamic longitudinal associations are understudied. Veterans Aging Cohort Study (VACS) data 2/1/2008-7/31/16 were used to fit linear regression models estimating changes in adherence (% days with ART medication fill) associated with changes in alcohol use based on annual clinically-ascertained AUDIT-C screening scores (range - 12 to + 12, 0 = no change) adjusting for demographics and initial adherence. Among 21,275 PLWH (67,330 observations), most reported no (48%) or low-level (39%) alcohol use initially, with no (55%) or small (39% ≤ 3 points) annual change. Mean initial adherence was 86% (SD 21%), mean annual change was - 3.1% (SD 21%). An inverted V-shaped association was observed: both increases and decreases in AUDIT-C were associated with greater adherence decreases relative to stable scores [p < 0.001, F (4, 21,274)]. PLWH with dynamic alcohol use (potentially indicative of alcohol use disorder) should be considered for adherence interventions.

RESUMEN: El consumo de alcohol aumenta el no-cumplimiento a la terapia antirretroviral (TARV) entre las personas que viven con VIH. No se han estudiado lo suficiente las dinámicas asociaciones longitudinales. Los datos del Estudio de la Envejecimiento de Cohorte de Veteranos (EECV) (1/2/2008­31/7/2016) fueron usados para encajar modelos de regresión lineal estimando los cambios en cumplimiento (% de días con medicaciones TARV surtidas) asociados con los cambios en el consumo de alcohol basado en los resultados anuales de las evaluaciones AUDIT-C, determinadas clínicamente, (una gama de -12 a + 12, 0 = cero cambio) adaptándose a las estadísticas demográficas y cumplimiento inicial. Entre 21,275 personas que viven con VIH (67,330 observaciones), la mayoría reportó ningún (48%) o bajos niveles del (39%) consumo de alcohol inicialmente, con ningún (55%) o muy pequeño (39% ≤ 3 puntos) cambio anual. la media inicial de cumplimiento fue 86% (DE 21%). La media de cambio anual fue -3.1% (DE 21%). Se observó una asociación de forma V invertida: tanto los aumentos como las disminuciones en AUDIT-C fueron asociados con mayor disminuciones de cumplimiento en comparación con resultados estables (p < 0.001, F (4, 21,274)). Personas que viven con VIH con el consumo dinámico de alcohol (potencialmente indicativo de un trastorno por consumo de alcohol) deben ser considerados por intervenciones de cumplimiento.

Patterns of COVID-19 testing and mortality by race and ethnicity among United States veterans: A nationwide cohort study.

BACKGROUND: There is growing concern that racial and ethnic minority communities around the world are experiencing a disproportionate burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19). We investigated racial and ethnic disparities in patterns of COVID-19 testing (i.e., who received testing and who tested positive) and subsequent mortality in the largest integrated healthcare system in the United States. METHODS AND FINDINGS: This retrospective cohort study included 5,834,543 individuals receiving care in the US Department of Veterans Affairs; most (91%) were men, 74% were non-Hispanic White (White), 19% were non-Hispanic Black (Black), and 7% were Hispanic. We evaluated associations between race/ethnicity and receipt of COVID-19 testing, a positive test result, and 30-day mortality, with multivariable adjustment for a wide range of demographic and clinical characteristics including comorbid conditions, health behaviors, medication history, site of care, and urban versus rural residence. Between February 8 and July 22, 2020, 254,595 individuals were tested for COVID-19, of whom 16,317 tested positive and 1,057 died. Black individuals were more likely to be tested (rate per 1,000 individuals: 60.0, 95% CI 59.6-60.5) than Hispanic (52.7, 95% CI 52.1-53.4) and White individuals (38.6, 95% CI 38.4-38.7). While individuals from minority backgrounds were more likely to test positive (Black versus White: odds ratio [OR] 1.93, 95% CI 1.85-2.01, p < 0.001; Hispanic versus White: OR 1.84, 95% CI 1.74-1.94, p < 0.001), 30-day mortality did not differ by race/ethnicity (Black versus White: OR 0.97, 95% CI 0.80-1.17, p = 0.74; Hispanic versus White: OR 0.99, 95% CI 0.73-1.34, p = 0.94). The disparity between Black and White individuals in testing positive for COVID-19 was stronger in the Midwest (OR 2.66, 95% CI 2.41-2.95, p < 0.001) than the West (OR 1.24, 95% CI 1.11-1.39, p < 0.001). The disparity in testing positive for COVID-19 between Hispanic and White individuals was consistent across region, calendar time, and outbreak pattern. Study limitations include underrepresentation of women and a lack of detailed information on social determinants of health. CONCLUSIONS: In this nationwide study, we found that Black and Hispanic individuals are experiencing an excess burden of SARS-CoV-2 infection not entirely explained by underlying medical conditions or where they live or receive care. There is an urgent need to proactively tailor strategies to contain and prevent further outbreaks in racial and ethnic minority communities.

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.

Evaluation of Complementary and Integrative Health Approaches Among US Veterans with Musculoskeletal Pain Using Propensity Score Methods.

Objectives: To examine the treatment effectiveness of complementary and integrative health approaches (CIH) on chronic pain using Propensity Score (PS) methods. Design, Settings, and Participants: A retrospective cohort of 309,277 veterans with chronic musculoskeletal pain assessed over three years after initial diagnosis. Methods: CIH exposure was defined as one or more clinical visits for massage, acupuncture, or chiropractic care. The treatment effect of CIH on self-rated pain intensity was examined using a longitudinal model. PS-matching and inverse probability of treatment weighting (IPTW) were used to account for potential selection and confounding biases. Results: At baseline, veterans with (7,621) and without (301,656) CIH exposure differed significantly in 21 out of 35 covariates. During the follow-up period, on average CIH recipients had 0.83 (95% confidence interval [CI] = 0.77 to 0.89) points higher pain intensity ratings (range = 0-10) than nonrecipients. This apparent unfavorable effect size was reduced to 0.37 (95% CI = 0.28 to 0.45) after PS matching, 0.36 (95% CI = 0.29 to 0.44) with IPTW on the treated (IPTW-T) weighting, and diminished to null when integrating IPTW-T with PS matching (0.004, 95% CI = -0.09 to 0.10). An alternative IPTW model and conventional covariate adjustment appeared least powerful in terms of potential bias reduction. Sensitivity analyses restricting the follow-up period to one year after CIH initiation derived consistent results. Conclusions: PS-based causal methods successfully eliminated baseline difference between exposure groups in all measured covariates, yet they did not detect a significant difference in the self-rated pain intensity outcome between veterans who received CIHs and those who did not during the follow-up period.

Healthcare Costs Related to Treatment of Hepatocellular Carcinoma Among Veterans With Cirrhosis in the United States.

BACKGROUND & AIMS: It is important to quantify medical costs associated with hepatocellular carcinoma (HCC), the incidence of which is rapidly increasing in the United States, for development of rational healthcare policies related to liver cancer surveillance and treatment of chronic liver disease. We aimed to comprehensively quantify healthcare costs for HCC among patients with cirrhosis in an integrated health system and develop a model for predicting costs that is based on clinically relevant variables. METHODS: Three years subsequent to liver cancer diagnosis, costs accrued by patients included in the Veteran's Outcome and Cost Associated with Liver disease cohort were compiled by using the Department of Veterans Affairs Corporate Data Warehouse. The cohort includes all patients with HCC diagnosed in 2008-2010 within the VA with 100% chart confirmation as well as chart abstraction of tumor and clinical characteristics. Cancer cases were matched 1:4 with non-cancer cirrhosis controls on the basis of severity of liver disease, age, and comorbidities to estimate background cirrhosis-related costs. Univariable and multivariable generalized linear models were developed and used to predict cancer-related overall cost. RESULTS: Our analysis included 3188 cases of HCC and 12,722 controls. The mean 3-year total cost of care in HCC patients was $154,688 (standard error, $150,953-$158,422) compared with $69,010 (standard error, $67,344-$70,675) in matched cirrhotic controls, yielding an incremental cost of $85,679; 64.9% of this value reflected increased inpatient costs. In univariable analyses, receipt of transplantation, Barcelona Clinic Liver Cancer (BCLC) stage, liver disease etiology, hospital academic affiliation, use of multidisciplinary tumor board, and identification through surveillance were associated with cancer-related costs. Multivariable generalized linear models incorporating transplantation status, BCLC stage, and multidisciplinary tumor board presentation accurately predicted liver cancer-related costs (Hosmer-Lemeshow goodness of fit; P value ≅ 1.0). CONCLUSIONS: In a model developed to comprehensively quantify healthcare costs for HCC among patients with cirrhosis in an integrated health system, we associated receipt of liver transplantation, BCLC stage, and multidisciplinary tumor board with higher costs. Models that predict total costs on the basis of receipt of liver transplantation were constructed and can be used to model cost-effectiveness of therapies focused on HCC prevention.

Variation in National Opioid Prescribing Patterns Following Surgery for Kidney Stones.

Background: Opioid misuse is a significant public health problem. As initial exposures to opioids are frequently encountered through the management of postoperative pain, we examined patterns of opioid prescribing following surgical treatment for nephrolithiasis. Methods: We identified patients with nephrolithiasis in the national Women Veterans Cohort Study (WVCS) who were treated surgically by diagnosis and procedure codes. Using standard conversion factors, we calculated the morphine milligram equivalent (MME) dose prescribed. We used descriptive statistics to characterize opioid prescription across management strategy and multivariable regression to examine clinical and demographic characteristics associated with dispensed dose. Results: We identified 22,609 patients diagnosed with kidney stones during 1999-2014, 1,976 of whom were treated surgically and 1,582 (80.1%) of whom received an opioid prescription. The median age was 39 years, and 1,366 (90%) were male; 1,314 (86.3%) were treated with ureteroscopy, 172 (11.3%) with extracorporeal shockwave lithotripsy, and 36 (2.4%) with percutaneous nephrolithotomy. The median number of days supplied per opioid prescription (interquartile range) was 10 (5-14), and patients were dispensed a median of 180 (140-300) MME. A total of 6.4% of patients received ≥50 MME/d. On multivariable analysis, comorbid diagnosis of post-traumatic stress disorder (PTSD) was associated with higher total dispensed dose, whereas surgery type was not. Conclusions: We observed substantial variation in opioid prescribing following surgical treatment of nephrolithiasis. Although type of surgical intervention did not impact opioid dosing, patients with a diagnosis of PTSD were more likely to receive higher doses. This work can inform efforts to improve the safety and efficacy of postoperative opioid prescribing.

Impact of Cigarette Smoking Status on Pain Intensity Among Veterans With and Without Hepatitis C.

Objective: Chronic pain is a significant problem in patients living with hepatitis C virus (HCV). Tobacco smoking is an independent risk factor for high pain intensity among veterans. This study aims to examine the independent associations with smoking and HCV on pain intensity, as well as the interaction of smoking and HCV on the association with pain intensity. Design/Particpants: Cross-sectional analysis of a cohort study of veterans of Operations Enduring Freedom/Iraqi Freedom/New Dawn (OEF/OIF/OND) who had at least one visit to a Veterans Health Administration (VHA) primary care clinic between 2001 and 2014. Methods: HCV was identified using ICD-9 codes from electronic medical records (EMRs). Pain intensity, reported on a 0-10 numeric rating scale, was categorized as none/mild (0-3) and moderate/severe (4-10). Results: Among 654,841 OEF/OIF/OND veterans (median age [interquartile range] = 26 [23-36] years), 2,942 (0.4%) were diagnosed with HCV. Overall, moderate/severe pain intensity was reported in 36% of veterans, and 37% were current smokers. The adjusted odds of reporting moderate/severe pain intensity were 1.23 times higher (95% confidence interval [CI] = 1.14-1.33) for those with HCV and 1.26 times higher (95% CI = 1.25-1.28) for current smokers. In the interaction model, there was a significant Smoking Status × HCV interaction (P = 0.03). Among veterans with HCV, smoking had a significantly larger association with moderate/severe pain (adjusted odds ratio [OR] = 1.50, P < 0.001) than among veterans without HCV (adjusted OR = 1.26, P < 0.001). Conclusions: We found that current smoking is more strongly linked to pain intensity among veterans with HCV. Further investigations are needed to explore the impact of smoking status on pain and to promote smoking cessation and pain management in veterans with HCV.