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Neighborhood characteristics are associated with residents' healthcare use. However, we understand less about these relationships among formerly homeless persons, who often have complex healthcare needs, including mental health and substance use disorders. Among formerly homeless Veterans, we examined: (a) how neighborhood characteristics are associated with Veteran Health Administration (VHA) healthcare use and, (b) if these relationships varied by Veterans' level of healthcare need. We obtained data on our cohort of 711 Veterans housed through VHA's permanent supportive housing program (HUD-VASH) in 2016-2017 from VHA's Homeless Registry, VHA's electronic health records, and the U.S. Census. We studied the relationships between neighborhood characteristics (% Veteran, % in poverty, % unemployed, % using public transportation, and % vacant properties) and VA healthcare use (primary care visits, outpatient mental health visits, and "high use" of emergency departments [> 4 visits]) using mixed-effects logistic and negative binomial regression models, controlling for patient demographics. We further examined moderation by patient healthcare need (calculated from cost and clinical data). We found that veterans in neighborhoods with higher percentages of residents who (a) were Veterans or (b) used public transportation were more likely to have high emergency department use. Those in neighborhoods with higher public transportation use had more primary care visits while those in neighborhoods with more property vacancies had more outpatient mental health visits. Among those with high healthcare needs, residents of areas with more Veterans had higher emergency department use. Promoting public transportation use and social engagement with other Veterans in residential neighborhoods may influence HUD-VASH Veterans' VA healthcare use. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

In this retrospective cohort study of 94 595 severe acute respiratory syndrome coronavirus 2–positive cases, we developed and validated an algorithm to assess the association between coronavirus disease 2019 (COVID-19) severity and long-term complications (stroke, myocardial infarction, pulmonary embolism/deep vein thrombosis, heart failure, and mortality). COVID-19 severity was associated with a greater risk of experiencing a long-term complication 31–120 days postinfection. Most incident events occurred 31–60 days postinfection and diminished after day 91, except heart failure for severe patients and death for moderate patients, which peaked on days 91–120. Understanding the differential impact of COVID-19 severity on long-term events provides insight into possible intervention modalities and critical prevention strategies.

PURPOSEAdvances in precision oncology, including RAS testing to predict response to epidermal growth factor receptor monoclonal antibodies (EGFR mAbs) in colorectal cancer (CRC), can extend patients’ lives. We evaluated uptake and clinical use of KRAS molecular testing, guideline recommended since 2010, in the Veterans Affairs Healthcare System (VA).MATERIALS AND METHODSWe conducted a retrospective cohort study of patients with stage IV CRC diagnosed in the VA 2006-2015. We gathered clinical, demographic, molecular, and treatment data from the VA Corporate Data Warehouse and 29 commercial laboratories. We performed multivariable analyses of associations between patient characteristics, KRAS testing, and EGFR mAb treatment.RESULTSAmong 5,943 patients diagnosed with stage IV CRC, only 1,053 (17.7%) had KRAS testing. Testing rates increased from 2.3% in 2006 to 28.4% in 2013. In multivariable regression, older patients (odds ratio, 0.17; 95% CI, 0.09 to 0.32 for ≥ age 85 v < 45 years) and those treated in the Northeast and South regions were less likely, and those treated at high-volume CRC centers were more likely to have KRAS testing (odds ratio, 2.32; 95% CI, 1.48 to 3.63). Rates of potentially guideline discordant care were high: 64.3% (321/499) of KRAS wild-type (WT) went untreated with EGFR mAb and 8.8% (401/4,570) with no KRAS testing received EGFR mAb. Among KRAS-WT patients, survival was better for patients who received EGFR mAb treatment (29.6 v 18.8 months; P < .001).CONCLUSIONWe found underuse of KRAS testing in advanced CRC, especially among older patients and those treated at lower-volume CRC centers. We found high rates of potentially guideline discordant underuse of EGFR mAb in patients with KRAS-WT tumors. Efforts to understand barriers to precision oncology are needed to maximize patient benefit.

Kristine E Lynch,1,2 Benjamin Viernes,1,2 Elise Gatsby,1 Scott L DuVall,1,2 Barbara E Jones,2,3 Tamára L Box,4 Craig Kreisler,4 Makoto Jones2,3 1VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Health Care System, Salt Lake City, UT, USA; 2Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA; 3Informatics, Decision-Enhancement, and Analytic Sciences (IDEAS) Center of Innovation, VA Salt Lake City Health Care System, Salt Lake City, UT, USA; 4Analytics and Performance Integration (API), Office of Quality and Patient Safety, Veterans Health Administration, Washington, DC, USACorrespondence: Kristine E LynchVA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Health Care System, 500 Foothill Drive, Salt Lake City, UT, 84148, USATel +1 801 582 1565 ext. 1913Email Kristine.Lynch@va.govPurpose: To estimate the positive predictive value (PPV) of International Classification of Diseases, Tenth Revision (ICD-10) code U07.1, COVID-19 virus identified, in the Department of Veterans of Affairs (VA).Patients and Methods: Records of ICD-10 code U07.1 from inpatient, outpatient, and emergency/urgent care settings were extracted from VA medical record data from 4/01/2020 to 3/31/2021. A weighted, random sample of 1500 records from each quarter of the one-year observation period was reviewed by study personnel to confirm active COVID-19 infection at the time of diagnosis and classify reasons for false positive records. PPV was estimated overall and compared across clinical setting and quarters.Results: We identified 664,406 records of U07.1. Among the 1500 reviewed, 237 were false positives (PPV: 84.2%, 95% CI: 82.4– 86.0). PPV ranged from 77.7% in outpatient settings to 93.8% in inpatient settings and was 83.3% in quarter 1, 80.5% in quarter 2, 86.1% in quarter 3, and 83.6% in quarter 4. The most common reasons for false positive records were history of COVID-19 (44.3%) and orders for laboratory tests (21.5%).Conclusion: The PPV of ICD-10 code U07.1 is low, especially in outpatient settings. Directed training may improve accuracy of coding to levels that are deemed adequate for future use in surveillance efforts.Keywords: SARS CoV-2, validation, administrative codes, electronic health records

Background: We described the demographics, cancer subtypes, comorbidities, and outcomes of patients with a history of cancer and coronavirus disease 2019 (COVID-19). Second, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza. Methods: We conducted a cohort study using eight routinely collected health care databases from Spain and the United States, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: (i) diagnosed with COVID-19, (ii) hospitalized with COVID-19, and (iii) hospitalized with influenza in 2017 to 2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes. Results: We included 366,050 and 119,597 patients diagnosed and hospitalized with COVID-19, respectively. Prostate and breast cancers were the most frequent cancers (range: 5%–18% and 1%–14% in the diagnosed cohort, respectively). Hematologic malignancies were also frequent, with non-Hodgkin's lymphoma being among the five most common cancer subtypes in the diagnosed cohort. Overall, patients were aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 2% to 14% and from 6% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n = 67,743) had a similar distribution of cancer subtypes, sex, age, and comorbidities but lower occurrence of adverse events. Conclusions: Patients with a history of cancer and COVID-19 had multiple comorbidities and a high occurrence of COVID-19-related events. Hematologic malignancies were frequent. Impact: This study provides epidemiologic characteristics that can inform clinical care and etiologic studies.

While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking.A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1-365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021.Advanced age (HR 2.77, 95%CI 2.53-3.04, p 0.0001), severe COVID-19 (HR 2.91, 95%CI 2.03-4.17, p 0.0001), severe AKI (KDIGO stage 3: HR 4.22, 95%CI 3.55-5.00, p 0.0001), and ischemic heart disease (HR 1.26, 95%CI 1.14-1.39, p 0.0001) were associated with worse mortality outcomes. AKI severity (KDIGO stage 3: HR 0.41, 95%CI 0.37-0.46, p 0.0001) was associated with worse kidney function recovery, whereas remdesivir use (HR 1.34, 95%CI 1.17-1.54, p 0.0001) was associated with better kidney function recovery. In a subset of patients without chronic kidney disease, advanced age (HR 1.38, 95%CI 1.20-1.58, p 0.0001), male sex (HR 1.67, 95%CI 1.45-1.93, p 0.0001), severe AKI (KDIGO stage 3: HR 11.68, 95%CI 9.80-13.91, p 0.0001), and hypertension (HR 1.22, 95%CI 1.10-1.36, p = 0.0002) were associated with post-AKI kidney function impairment. Furthermore, patients with COVID-19-associated AKI had significant and persistent elevations of baseline serum creatinine 125% or more at 180 days (RR 1.49, 95%CI 1.32-1.67) and 365 days (RR 1.54, 95%CI 1.21-1.96) compared to COVID-19 patients with no AKI.COVID-19-associated AKI was associated with higher mortality, and severe COVID-19-associated AKI was associated with worse long-term post-AKI kidney function recovery.Authors are supported by various funders, with full details stated in the acknowledgement section.

PURPOSE: The purpose of this study was to determine variation in sexual minority (SM) sexual orientation documentation within the electronic medical records of the Veterans Health Administration (VHA). METHODS: Documentation of SM sexual orientation was retrospectively extracted from clinical notes and administrative data in the VHA from October 1, 1999 to July 1, 2019. The rate of documentation overall and by calendar year was calculated, and differences across patient, provider, and clinic characteristics were evaluated. RESULTS: Approximately 1.4% of all VHA Veterans (n = 115,911) had at least one documentation of SM sexual orientation, including 79,455 men and 36,456 women. The rate of documentation increased from 81.01/100,000 in 2000 to 568.84/100,000 in 2018. The majority of documentations (58.7%) occurred in mental health settings by non-MD mental health/social work counselors, whereas only 9.6% occurred in primary care settings. Although 99% of these Veterans had a primary care visit, only 19% had SM status recorded in that setting. CONCLUSION: Documentation patterns of SM sexual orientation varied considerably in the VHA with notable gaps in primary care. Diverse approaches to culturally competent training for primary care clinicians and patient-facing collection strategies could facilitate documentation of sexual orientation.

Background Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) have been postulated to affect susceptibility to COVID-19. Observational studies so far have lacked rigorous ascertainment adjustment and international generalisability. We aimed to determine whether use of ACEIs or ARBs is associated with an increased susceptibility to COVID-19 in patients with hypertension. Methods In this international, open science, cohort analysis, we used electronic health records from Spain (Information Systems for Research in Primary Care [SIDIAP]) and the USA (Columbia University Irving Medical Center data warehouse [CUIMC] and Department of Veterans Affairs Observational Medical Outcomes Partnership [VA-OMOP]) to identify patients aged 18 years or older with at least one prescription for ACEIs and ARBs (target cohort) or calcium channel blockers (CCBs) and thiazide or thiazide-like diuretics (THZs; comparator cohort) between Nov 1, 2019, and Jan 31, 2020. Users were defined separately as receiving either monotherapy with these four drug classes, or monotherapy or combination therapy (combination use) with other antihypertensive medications. We assessed four outcomes: COVID-19 diagnosis; hospital admission with COVID-19; hospital admission with pneumonia; and hospital admission with pneumonia, acute respiratory distress syndrome, acute kidney injury, or sepsis. We built large-scale propensity score methods derived through a data-driven approach and negative control experiments across ten pairwise comparisons, with results meta-analysed to generate 1280 study effects. For each study effect, we did negative control outcome experiments using a possible 123 controls identified through a data-rich algorithm. This process used a set of predefined baseline patient characteristics to provide the most accurate prediction of treatment and balance among patient cohorts across characteristics. The study is registered with the EU Post-Authorisation Studies register, EUPAS35296. Findings Among 1 355 349 antihypertensive users (363 785 ACEI or ARB monotherapy users, 248 915 CCB or THZ monotherapy users, 711 799 ACEI or ARB combination users, and 473 076 CCB or THZ combination users) included in analyses, no association was observed between COVID-19 diagnosis and exposure to ACEI or ARB monotherapy versus CCB or THZ monotherapy (calibrated hazard ratio [HR] 0·98, 95% CI 0·84–1·14) or combination use exposure (1·01, 0·90–1·15). ACEIs alone similarly showed no relative risk difference when compared with CCB or THZ monotherapy (HR 0·91, 95% CI 0·68–1·21; with heterogeneity of >40%) or combination use (0·95, 0·83–1·07). Directly comparing ACEIs with ARBs demonstrated a moderately lower risk with ACEIs, which was significant with combination use (HR 0·88, 95% CI 0·79–0·99) and non-significant for monotherapy (0·85, 0·69–1·05). We observed no significant difference between drug classes for risk of hospital admission with COVID-19, hospital admission with pneumonia, or hospital admission with pneumonia, acute respiratory distress syndrome, acute kidney injury, or sepsis across all comparisons. Interpretation No clinically significant increased risk of COVID-19 diagnosis or hospital admission-related outcomes associated with ACEI or ARB use was observed, suggesting users should not discontinue or change their treatment to decrease their risk of COVID-19.

Introduction Despite improvements in electronic medical record capability to collect data on sexual orientation, not all healthcare systems have adopted this practice. This can limit the usability of systemwide electronic medical record data for sexual minority research. One viable resource might be the documentation of sexual orientation within clinical notes. The authors developed an approach to identify sexual orientation documentation and subsequently derived a cohort of sexual minority patients using clinical notes from the Veterans Health Administration electronic medical record. Methods A hybrid natural language processing approach was developed and used to identify and categorize instances of terms and phrases related to sexual orientation in Veterans Health Administration clinical notes from 2000 to 2019. System performance was assessed with positive predictive value and sensitivity. Data were analyzed in 2019. Results A total of 2,413,584 sexual minority terms/phrases were found within clinical notes, of which 439,039 (18%) were found to be related to patient sexual orientation with a positive predictive value of 85.9%. Documentation of sexual orientation was found for 115,312 patients. When compared with 2,262 patients with a record of administrative coding for homosexuality, the system found mentions of sexual orientation for 1,808 patients (79.9% sensitivity). Conclusions When systemwide structured data are unavailable or inconsistent, deriving a cohort of sexual minority patients in electronic medical records for research is possible and permits longitudinal analysis across multiple clinical domains. Although limitations and challenges to the approach were identified, this study makes an important step forward for the Veterans Health Administration sexual minority research, and the methodology can be applied in other healthcare organizations.

Alcohol use is a significant concern nationally and research now highlights higher rates of alcohol attributable death (AAD) and years of potential life lost (YPLL) among lesbian, gay, and bisexual (LGB) veterans compared to non-LGB veterans. In this study, we examined specific causes of AAD and associated YPLL between LGB and non-LGB veteran men and women to highlight needed outreach, prevention, and treatment strategies.Using data from the nationwide Veterans Health Administration electronic health record and National Death Index from 2014 to 2018, we examined the top ten ranked causes of AAD among LGB (n = 102,085) and non-LGB veteran (n = 5,300,521) men and women, as well as associated YPLL per AAD.We observed higher rates of AAD among men than women, but higher rates among LGB veterans relative to their same-sex non-LGB counterparts. We noted greater YPLL per AAD among LGB men and all women compared to non-LGB men, even when of similar or same rank in cause of death. Acute-cause AAD death (e.g., alcohol-related suicide, poisonings) was ranked higher among LGB men and all women. YPLL was greater for both acute- and chronic-cause AAD (e.g., liver disease) among LGB men and all women compared to non-LGB men.Causes of AAD differ between LGB and non-LGB men and women. The differences observed highlight disparities in acute- and chronic-cause AAD between groups help explain the higher number of YPLL per AAD that disfavor LGB men and women veterans, and essential next steps in primary and secondary prevention of hazardous drinking and mortality risk.

Unhealthy alcohol use is disproportionally experienced by individuals with minoritized sexual orientations. Unlike the general US population, for whom the burden of alcohol as it relates to mortality is consistently monitored across time with national survey data, the impact of unhealthy alcohol use among veterans with minoritized sexual orientations, for whom addressing substance use is a national priority, is largely unknown.Using Alcohol Use Disorders Identification Test Consumption data from the Department of Veterans Affairs electronic health record and underlying cause of death from National Death Index from 2014 to 2018 we quantified alcohol consumption and related mortality among veterans with (n = 102,085) and without minoritized sexual orientations (n = 5300,521). Age adjusted rates of alcohol attributed deaths (AAD) per 100,000 persons and years of potential life lost (YPLL) were estimated by sexual orientation, sex, and sexual orientation stratified by sex.Alcohol attributable deaths (n = 21,861) were higher among veterans with minoritized sexual orientations than veterans without after adjustment for age (486.5 deaths/100,000 versus 309.7 deaths/100,000, respectively). Veterans with minoritized sexual orientations also experienced more YPLL (13,772.8 years/100,000 versus 7618.9 years/100,000). Years of potential life lost per AAD was higher in women (33.2 years) than men (18.7 years).Alcohol consumption results in substantial disability and death among veterans, particularly veterans with minoritized sexual orientations. Findings suggest need for increased alcohol-related services for all VA patients, and potential targeted approaches to for veterans with minoritized sexual orientations and women to offset risk for, and years of potential life lost from, alcohol attributable death.

UNSTRUCTURED Sexual health is the state of well-being regarding one’s sexuality, not just the absence of disease or dysfunction. Sexual health is highly valued by most people and associated with overall health. Assessment of sexual health, including sexual orientation and gender identity, should be integrated into the whole health approach to care. Addressing sexual health will enhance preventive care, promote healthy sexual functioning, and optimize overall health and well-being. Unfortunately, sexual health is not routinely assessed in clinical practice. One of the primary barriers is a gap in communication between patients and providers. Providers cite beliefs that patients will bring up sexual concerns themselves, or that patients might be offended by discussing sexual health. By contrast, patients often report an expectation that providers will bring up sexual health, and be comfortable with sexual health discussions in the clinic setting. Within the Veterans Health Administration (VHA), the lack of a sexual health template within the electronic health record (EHR) adds an additional technological barrier. The VHA’s transition toward whole health and updates to its EHR will provide unique opportunities to integrate sexual health assessment into routine care. We highlight future system modifications to address this within the VHA. Given the multifaceted barriers to sexual health assessment, it will be vital for healthcare systems integrating a whole health approach to develop both practical and educational interventions to address the communication gap. VHA’s expertise in developing and implementing EHR-based quality improvements and health education interventions may help inform interventions beyond VHA.

SARS-CoV-2 infection prominently affects the respiratory system, and patients hospitalized with COVID-19 are at an increased risk of developing respiratory conditions. We examined the risk of new respiratory conditions of COVID-19 among hospitalized patients in the national Veterans Health Administration between 15 February 2020 and 16 June 2021. The study cohort included all COVID-19-tested, hospitalized individuals who survived the index admission and did not have any previously diagnosed chronic respiratory conditions (asthma, bronchitis, chronic lung disease, chronic obstructive pulmonary disease (COPD), emphysema, or venous thromboembolism) before SARS-CoV-2 testing. Of 373,048 patients hospitalized after SARS-CoV-2 testing, 18,686 positive and 37,372 negative patients met the inclusion/exclusion criteria and were matched by age, sex, and race using propensity score matching. The results showed that the SARS-CoV-2 positive group had a greater risk of developing asthma (adjusted odds ratio (aOR) = 1.37), bronchitis (aOR = 2.81), chronic lung disease (aOR = 2.14), COPD (aOR = 1.56), emphysema (aOR = 1.52), and venous thromboembolism (aOR = 1.92) within 60 days after the index COVID date of testing. These findings could inform that the clinical care team considers a risk of new respiratory conditions and address these conditions in the post-hospitalization management of the patient, which could potentially lead to reduce the risk of complications and optimize recovery.

Kristin Kostka,1,2 Talita Duarte-Salles,3 Albert Prats-Uribe,4 Anthony G Sena,5,6 Andrea Pistillo,3 Sara Khalid,4 Lana YH Lai,7 Asieh Golozar,8,9 Thamir M Alshammari,10 Dalia M Dawoud,11 Fredrik Nyberg,12 Adam B Wilcox,13,14 Alan Andryc,5 Andrew Williams,15 Anna Ostropolets,16 Carlos Areia,17 Chi Young Jung,18 Christopher A Harle,19 Christian G Reich,1,2 Clair Blacketer,5,6 Daniel R Morales,20 David A Dorr,21 Edward Burn,3,4 Elena Roel,3,22 Eng Hooi Tan,4 Evan Minty,23 Frank DeFalco,5 Gabriel de Maeztu,24 Gigi Lipori,19 Hiba Alghoul,25 Hong Zhu,26 Jason A Thomas,13 Jiang Bian,19 Jimyung Park,27 Jordi Martínez Roldán,28 Jose D Posada,29 Juan M Banda,30 Juan P Horcajada,31 Julianna Kohler,32 Karishma Shah,33 Karthik Natarajan,16,34 Kristine E Lynch,35,36 Li Liu,37 Lisa M Schilling,38 Martina Recalde,3,22 Matthew Spotnitz,14 Mengchun Gong,39 Michael E Matheny,40,41 Neus Valveny,42 Nicole G Weiskopf,21 Nigam Shah,29 Osaid Alser,43 Paula Casajust,42 Rae Woong Park,27,44 Robert Schuff,21 Sarah Seager,1 Scott L DuVall,35,36 Seng Chan You,45 Seokyoung Song,46 Sergio Fernández-Bertolín,3 Stephen Fortin,5 Tanja Magoc,19 Thomas Falconer,16 Vignesh Subbian,47 Vojtech Huser,48 Waheed-Ul-Rahman Ahmed,33,49 William Carter,38 Yin Guan,50 Yankuic Galvan,19 Xing He,19 Peter R Rijnbeek,6 George Hripcsak,16,34 Patrick B Ryan,5,16 Marc A Suchard,51 Daniel Prieto-Alhambra4 1IQVIA, Cambridge, MA, USA; 2OHDSI Center at The Roux Institute, Northeastern University, Portland, ME, USA; 3Fundació Institut Universitari per a la recerca a l’Atenció Primà ria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain; 4Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, UK; 5Janssen Research & Development, Titusville, NJ, USA; 6Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands; 7School of Medical Sciences, University of Manchester, Manchester, UK; 8Regeneron Pharmaceuticals, Tarrytown, NY, USA; 9Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; 10College of Pharmacy, Riyadh Elm University, Riyadh, Saudi Arabia; 11National Institute for Health and Care Excellence, London, UK; 12School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; 13Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA; 14Unviersity of Washington Medicine, Seattle, WA, USA; 15Tufts Institute for Clinical Research and Health Policy Studies, Boston, MA, USA; 16Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA; 17Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; 18Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Daegu Catholic University Medical Center, Daegu, South Korea; 19University of Florida Health, Gainesville, FL, USA; 20Division of Population Health and Genomics, University of Dundee, Dundee, UK; 21Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA; 22Universitat Autònoma de Barcelona, Barcelona, Spain; 23O’Brien Institute for Public Health, Faculty of Medicine, University of Calgary, Calgary, Canada; 24IOMED, Barcelona, Spain; 25Faculty of Medicine, Islamic University of Gaza, Gaza, Palestine; 26Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 27Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, South Korea; 28Director of Innovation and Digital Transformation, Hospital del Mar, Barcelona, Spain; 29Department of Medicine, School of Medicine, Stanford University, Redwood City, CA, USA; 30Georgia State University, Department of Computer Science, Atlanta, GA, USA; 31Department of Infectious Diseases, Hospital del Mar, Institut Hospital del Mar d’Investigació Mèdica (IMIM), Universitat Autònoma de Barcelona, Universitat Pompeu Fabra, Barcelona, Spain; 32United States Agency for International Development, Washington, DC, USA; 33Botnar Research Centre, NDORMS, University of Oxford, Oxford, UK; 34New York-Presbyterian Hospital, New York, NY, USA; 35VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA; 36Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA; 37Biomedical Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 38Data Science to Patient Value Program, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; 39Institute of Health Management, Southern Medical University, Guangzhou, People’s Republic of China; 40Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA; 41Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA; 42Real-World Evidence, TFS, Barcelona, Spain; 43Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; 44Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea; 45Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, South Korea; 46Department of Anesthesiology and Pain Medicine, Catholic University of Daegu, School of Medicine, Daegu, South Korea; 47College of Engineering, The University of Arizona, Tucson, AZ, USA; 48National Library of Medicine, National Institutes of Health, Bethesda, MD, USA; 49College of Medicine and Health, University of Exeter, St Luke’s Campus, Exeter, UK; 50DHC Technologies Co. Ltd., Beijing, People’s Republic of China; 51Departments of Biostatistics, Computational Medicine, and Human Genetics, University of California, Los Angeles, CA, USACorrespondence: Daniel Prieto-Alhambra, Botnar Research Centre, Windmill Road, Oxford, OX37LD, UK, Email daniel.prietoalhambra@ndorms.ox.ac.ukPurpose: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD.Patients and Methods: We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services.Results: We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed.Conclusion: We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.Keywords: OHDSI, OMOP CDM, descriptive epidemiology, real world data, real world evidence, open science

Objective: To characterise patients with and without prevalent hypertension and COVID-19 and to assess adverse outcomes in both inpatients and outpatients. Design and setting: This is a retrospective cohort study using 15 healthcare databases (primary and secondary electronic healthcare records, insurance and national claims data) from the USA, Europe and South Korea, standardised to the Observational Medical Outcomes Partnership common data model. Data were gathered from 1 March to 31 October 2020. Participants: Two non-mutually exclusive cohorts were defined: (1) individuals diagnosed with COVID-19 (diagnosed cohort) and (2) individuals hospitalised with COVID-19 (hospitalised cohort), and stratified by hypertension status. Follow-up was from COVID-19 diagnosis/hospitalisation to death, end of the study period or 30 days. Outcomes: Demographics, comorbidities and 30-day outcomes (hospitalisation and death for the 'diagnosed' cohort and adverse events and death for the 'hospitalised' cohort) were reported. Results: We identified 2 851 035 diagnosed and 563 708 hospitalised patients with COVID-19. Hypertension was more prevalent in the latter (ranging across databases from 17.4% (95% CI 17.2 to 17.6) to 61.4% (95% CI 61.0 to 61.8) and from 25.6% (95% CI 24.6 to 26.6) to 85.9% (95% CI 85.2 to 86.6)). Patients in both cohorts with hypertension were predominantly >50 years old and female. Patients with hypertension were frequently diagnosed with obesity, heart disease, dyslipidaemia and diabetes. Compared with patients without hypertension, patients with hypertension in the COVID-19 diagnosed cohort had more hospitalisations (ranging from 1.3% (95% CI 0.4 to 2.2) to 41.1% (95% CI 39.5 to 42.7) vs from 1.4% (95% CI 0.9 to 1.9) to 15.9% (95% CI 14.9 to 16.9)) and increased mortality (ranging from 0.3% (95% CI 0.1 to 0.5) to 18.5% (95% CI 15.7 to 21.3) vs from 0.2% (95% CI 0.2 to 0.2) to 11.8% (95% CI 10.8 to 12.8)). Patients in the COVID-19 hospitalised cohort with hypertension were more likely to have acute respiratory distress syndrome (ranging from 0.1% (95% CI 0.0 to 0.2) to 65.6% (95% CI 62.5 to 68.7) vs from 0.1% (95% CI 0.0 to 0.2) to 54.7% (95% CI 50.5 to 58.9)), arrhythmia (ranging from 0.5% (95% CI 0.3 to 0.7) to 45.8% (95% CI 42.6 to 49.0) vs from 0.4% (95% CI 0.3 to 0.5) to 36.8% (95% CI 32.7 to 40.9)) and increased mortality (ranging from 1.8% (95% CI 0.4 to 3.2) to 25.1% (95% CI 23.0 to 27.2) vs from 0.7% (95% CI 0.5 to 0.9) to 10.9% (95% CI 10.4 to 11.4)) than patients without hypertension. Conclusions: COVID-19 patients with hypertension were more likely to suffer severe outcomes, hospitalisations and deaths compared with those without hypertension. This work was supported by several funders as follows: the European Health Data and Evidence Network received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement number 806968. The JU received support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This research received partial support from the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), US National Institutes of Health (R01 LM006910), US Department of Veterans Affairs, the Health Department from the Generalitat de Catalunya with a grant for research projects on SARS-CoV-2 and COVID-19 disease organised by the Direcció General de Recerca i Innovació en Salut, Janssen Research and Development, TFS, IOMED and IQVIA. The University of Oxford received funding related to this work from the Bill and Melinda Gates Foundation (Investment ID INV-016201 and INV-019257). TFS received funding related to this work from the University of Oxford. This work was also supported with funding (resources and facilities) of the Department of Veterans Affairs (VA) Informatics and Computing Infrastructure (VINCI) (VA HSR RES 13-457).

Objective: Questionnaire studies show people with minoritized sexual orientations (MSOs) face increased risk for conditions including posttraumatic stress disorder (PTSD). This study replicated Harrington et al.'s (2019) electronic health record probabilistic algorithm to evaluate lifetime PTSD prevalence in Veterans Health Administration (VHA)-using veterans. Method: In 115,853 MSO veterans and a 1:3 matched (on sex assigned at birth, and age at and year of first VHA visit) sample of non-MSO veterans. Each veteran was given a probability of "likely PTSD" (0.0-1.0) and thresholds (e.g., 0.7) applied to minimize false positive classifications. Results: Veterans with MSO were 2.35 times, CI [2.33, 2.38], more likely to have "likely PTSD" than veterans with non-MSO. The prevalence of "likely PTSD" using the rule-based International Classification of Diseases (ICD) approach was 40.8% among the MSO group compared to 22.0% among the non-MSO group after excluding those with bipolar or schizophrenia diagnoses and those with limited VHA engagement. Without those exclusions, prevalence was slightly higher in both groups (46.1% vs. 24.3%, respectively; prevalence ratio: 1.90). Despite increased prevalence of exposure to military sexual trauma (MST; MSO = 20.7%; non-MSO = 8.3%) and double "likely PTSD" among MSO veterans, they were less likely to have a service-connected PTSD disability than their matched non-MSO (MSO = 78.1%; non-MSO = 87.6%) comparators. Conclusions: VHA-using veterans with MSO were twice as likely to have "likely PTSD" and exposure to MST than veterans with non-MSO. Veterans with MSO were less likely to be service connected for PTSD than non-MSO counterparts. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Patients with autoimmune diseases were advised to shield to avoid COVID-19, but information on their prognosis is lacking. We characterised 30-day outcomes and mortality after hospitalisation with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza.Multinational network cohort study.Electronic health records data from Columbia University Irving Medical Center (CUIMC) (NYC, United States [US]), Optum [US], Department of Veterans Affairs (VA) (US), Information System for Research in Primary Care-Hospitalisation Linked Data (SIDIAP-H) (Spain), and claims data from IQVIA Open Claims (US) and Health Insurance and Review Assessment (HIRA) (South Korea).All patients with prevalent autoimmune diseases, diagnosed and/or hospitalised between January and June 2020 with COVID-19, and similar patients hospitalised with influenza in 2017-2018 were included.30-day complications during hospitalisation and death.We studied 133,589 patients diagnosed and 48,418 hospitalised with COVID-19 with prevalent autoimmune diseases. The majority of participants were female (60.5% to 65.9%) and aged ≥50 years. The most prevalent autoimmune conditions were psoriasis (3.5 to 32.5%), rheumatoid arthritis (3.9 to 18.9%), and vasculitis (3.3 to 17.6%). Amongst hospitalised patients, Type 1 diabetes was the most common autoimmune condition (4.8% to 7.5%) in US databases, rheumatoid arthritis in HIRA (18.9%), and psoriasis in SIDIAP-H (26.4%).Compared to 70,660 hospitalised with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2% to 4.3% versus 6.3% to 24.6%).Patients with autoimmune diseases had high rates of respiratory complications and 30-day mortality following a hospitalization with COVID-19. Compared to influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality. Future studies should investigate predictors of poor outcomes in COVID-19 patients with autoimmune diseases.Patients with autoimmune conditions may be at increased risk of COVID-19 infection andcomplications.There is a paucity of evidence characterising the outcomes of hospitalised COVID-19 patients with prevalent autoimmune conditions.Most people with autoimmune diseases who required hospitalisation for COVID-19 were women, aged 50 years or older, and had substantial previous comorbidities.Patients who were hospitalised with COVID-19 and had prevalent autoimmune diseases had higher prevalence of hypertension, chronic kidney disease, heart disease, and Type 2 diabetes as compared to those with prevalent autoimmune diseases who were diagnosed with COVID-19.A variable proportion of 6% to 25% across data sources died within one month of hospitalisation with COVID-19 and prevalent autoimmune diseases.For people with autoimmune diseases, COVID-19 hospitalisation was associated with worse outcomes and 30-day mortality compared to admission with influenza in the 2017-2018 season.

RationaleA commonMUC5Bgene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis, but its role in the SARS-CoV-2 infection and disease severity is unclear.ObjectivesTo assess whether rs35705950-T confers differential risk for clinical outcomes associated with COVID-19 infection among participants in the Million Veteran Program (MVP) and COVID-19 Host Genetics Initiative (HGI).MethodsMVP participants were examined for an association between the incidence or severity of COVID-19 and the presence of aMUC5Brs35705950-T allele. Comorbidities and clinical events were extracted from the electronic health records (EHR). The analysis was performed within each ancestry group in the MVP, adjusting for sex, age, age2,and first twenty principal components followed by a trans-ethnic meta-analysis. We then pursued replication and performed a meta-analysis with the trans-ethnic summary statistics from the HGI. A phenome-wide association study (PheWAS) of the rs35705950-T was conducted to explore associated pathophysiologic conditions.Measurements and Main ResultsA COVID-19 severity scale was modified from the World Health Organization criteria, and phenotypes derived from the International Classification of Disease-9/10 were extracted from EHR. Presence of rs35705950-T was associated with fewer hospitalizations (Ncases=25353, Ncontrols=631,024; OR=0.86 [0.80-0.93], p=7.4 × 10−5) in trans-ethnic meta-analysis within MVP and joint meta-analyses with the HGI (N=1641311; OR=0.89 [0.85-0.93], p =1.9 × 10−6). Moreover, individuals of European Ancestry with at least one copy of rs35705950-T had fewer post-COVID-19 pneumonia events (OR=0.85 [0.76-0.96], p =0.008). PheWAS exclusively revealed pulmonary involvement.ConclusionsTheMUC5Bvariant rs35705950-T is protective in COVID-19 infection.

Minimally invasive hysterectomy for fibroids decreases recovery time and risk of postoperative complications compared with abdominal hysterectomy. Within Veterans Affair (VA), black women with uterine fibroids are less likely to receive a minimally invasive hysterectomy than white women.To quantify the contributions of patient, facility, temporal and geographic factors to VA black-white disparity in minimally invasive hysterectomy.A cross-sectional study.Veterans with fibroids and hysterectomy performed in VA between October 1, 2012 and September 30, 2015.Hysterectomy mode was defined using ICD-9 codes as minimally invasive (laparoscopic, vaginal, or robotic-assisted) versus abdominal. The authors estimated a logistic regression model with minimally invasive hysterectomy modeled as a function of 4 sets of factors: sociodemographic characteristics other than race, health risk factors, facility, and temporal and geographic factors. Using decomposition techniques, systematically substituting each white woman's characteristics for each black woman's characteristics, then recalculating the predicted probability of minimally invasive hysterectomy for black women for each possible combination of factors, we quantified the contribution of each set of factors to observed disparities in minimally invasive hysterectomy.Among 1255 veterans with fibroids who had a hysterectomy at a VA, 61% of black women and 39% of white women had an abdominal hysterectomy. Our models indicated there were 99 excess abdominal hysterectomies among black women. The majority (n=77) of excess abdominal hysterectomies were unexplained by measured sociodemographic factors beyond race, health risk factors, facility, and temporal or geographic trends.Closer examination of the equity of VA gynecology care and ways in which the VA can work to ensure equitable care for all women veterans is necessary.

BACKGROUND: Surveillance recommendations for patients with low-risk non-muscle-invasive bladder cancer (NMIBC) are based on limited evidence. Our objective was to add to the evidence by assessing outcomes after frequent versus recommended cystoscopic surveillance. METHODS: This is a retrospective cohort study of patients diagnosed with low-risk (low grade Ta) NMIBC from 2005 – 2011 with follow-up through 2014 from the Department of Veterans Affairs. Patients were classified as having undergone frequent versus recommended cystoscopic surveillance (>3 versus 1–3 cystoscopies in the first 2 years after diagnosis). Using propensity score adjusted models, we estimated the impact of frequent cystoscopy on the number of transurethral resections, the number of resections without cancer in the specimen, and on risk of progression to muscle-invasive cancer or bladder cancer death. RESULTS: Among 1,042 patients, 798 (77%) had more frequent cystoscopy than recommended. In adjusted analyses, the frequent cystoscopy group had twice as many transurethral resections (55 versus 26 per 100 person years; p

Purpose The Veterans Health Administration (VA) is the largest single integrated healthcare system in the US and is likely the largest healthcare provider for people with minoritized sexual orientations (e.g., gay, lesbian, bisexual). The purpose of this study was to use electronic health record (EHR) data to replicate self-reported survey findings from the general US population and assess whether sexual orientation is associated with diagnosed physical health conditions that may elevate risk of COVID-19 severity among veterans who utilize the VA. Methods A retrospective analysis of VA EHR data from 10/01/1999-07-01-2019 analyzed in 2021. Veterans with minoritized sexual orientations were included if they had documentation of a minoritized sexual orientation within clinical notes identified via natural language processing. Veterans without minoritized sexual orientation documentation comprised the comparison group. Adjusted prevalence and prevalence ratios (aPR) were calculated overall and by race/ethnicity while accounting for differences in distributions of sex assigned at birth, age, calendar year of first VA visit, volumes of healthcare utilization, and VA priority group. Results Data from 108,401 veterans with minoritized sexual orientation and 6,511,698 controls were analyzed. After adjustment, veterans with minoritized sexual orientations had a statistically significant elevated prevalence of 10 of the 11 conditions. Amongst the highest disparities observed were COPD (aPR:1.24 [95% confidence interval:1.23-1.26]), asthma (1.22 [1.20-1.24]), and stroke (1.26 [1.24-1.28]). Conclusions Findings largely corroborated patterns among the general US population. Further research is needed to determine if these disparities translate to poorer COVID-19 outcomes for individuals with minoritized sexual orientation.

Background A detailed characterization of patients with COVID-19 living with obesity has not yet been undertaken. We aimed to describe and compare the demographics, medical conditions, and outcomes of COVID-19 patients living with obesity (PLWO) to those of patients living without obesity. Methods We conducted a cohort study based on outpatient/inpatient care and claims data from January to June 2020 from Spain, the UK, and the US. We used six databases standardized to the OMOP common data model. We defined two non-mutually exclusive cohorts of patients diagnosed and/or hospitalized with COVID-19; patients were followed from index date to 30 days or death. We report the frequency of demographics, prior medical conditions, and 30-days outcomes (hospitalization, events, and death) by obesity status. Results We included 627 044 (Spain: 122 058, UK: 2336, and US: 502 650) diagnosed and 160 013 (Spain: 18 197, US: 141 816) hospitalized patients with COVID-19. The prevalence of obesity was higher among patients hospitalized (39.9%, 95%CI: 39.8−40.0) than among those diagnosed with COVID-19 (33.1%; 95%CI: 33.0−33.2). In both cohorts, PLWO were more often female. Hospitalized PLWO were younger than patients without obesity. Overall, COVID-19 PLWO were more likely to have prior medical conditions, present with cardiovascular and respiratory events during hospitalization, or require intensive services compared to COVID-19 patients without obesity. Conclusion We show that PLWO differ from patients without obesity in a wide range of medical conditions and present with more severe forms of COVID-19, with higher hospitalization rates and intensive services requirements. These findings can help guiding preventive strategies of COVID-19 infection and complications and generating hypotheses for causal inference studies.

ObjectivesConcern has been raised in the rheumatology community regarding recent regulatory warnings that HCQ used in the coronavirus disease 2019 pandemic could cause acute psychiatric events. We aimed to study whether there is risk of incident depression, suicidal ideation or psychosis associated with HCQ as used for RA.MethodsWe performed a new-user cohort study using claims and electronic medical records from 10 sources and 3 countries (Germany, UK and USA). RA patients ≥18 years of age and initiating HCQ were compared with those initiating SSZ (active comparator) and followed up in the short (30 days) and long term (on treatment). Study outcomes included depression, suicide/suicidal ideation and hospitalization for psychosis. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate database-specific calibrated hazard ratios (HRs), with estimates pooled where I2

Objective To investigate the use of repurposed and adjuvant drugs in patients admitted to hospital with covid-19 across three continents. Design Multinational network cohort study. Setting Hospital electronic health records from the United States, Spain, and China, and nationwide claims data from South Korea. Participants 303 264 patients admitted to hospital with covid-19 from January 2020 to December 2020. Main outcome measures Prescriptions or dispensations of any drug on or 30 days after the date of hospital admission for covid-19. Results Of the 303 264 patients included, 290 131 were from the US, 7599 from South Korea, 5230 from Spain, and 304 from China. 3455 drugs were identified. Common repurposed drugs were hydroxychloroquine (used in from Conclusions Multiple drugs were used in the first few months of the covid-19 pandemic, with substantial geographical and temporal variation. Hydroxychloroquine, azithromycin, lopinavir-ritonavir, and umifenovir (in China only) were the most prescribed repurposed drugs. Antithrombotics, antibiotics, H2 receptor antagonists, and corticosteroids were often used as adjunctive treatments. Research is needed on the comparative risk and benefit of these treatments in the management of covid-19.

Alpha-1 blockers, often used to treat benign prostate hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storms release. We conducted a prevalent-user active-comparator cohort study to assess association between alpha-1 blocker use and risks of three COVID-19 outcomes: diagnosis, hospitalization, and hospitalization requiring intensive services. Our study included 2.6 and 0.46 million users of alpha-1 blockers and of alternative BPH therapy during the period between November 2019 and January 2020, found in electronic health records from Spain (SIDIAP) and the United States (Department of Veterans Affairs, Columbia University Irving Medical Center, IQVIA OpenClaims, Optum DOD, Optum EHR). We estimated hazard ratios using state-of-the-art techniques to minimize potential confounding, including large-scale propensity score matching/stratification and negative control calibration. We found no differential risk for any of COVID-19 outcome, pointing to the need for further research on potential COVID-19 therapies.

Introduction:Sexual health is the state of well-being regarding one’s sexuality. Sexual health is highly valued by most people and associated with overall health. Overall health and well-being are more than the absence of disease or dysfunction. Healthcare systems adopting wholehealth models of care need to incorporate holistic assessment of sexual health. This includes assessing patients’ sexual orientation and gender identity (SOGI). If health systems, including but not limited to the Veterans Health Administration (VHA), incorporate sexual health into whole health models of care they could enhance preventive care, promote healthy sexual functioning, and optimize overall health and well-being.Benefits of Assessing Sexual Health:Assessing sexual health can give providers important information about a patient’s general health, well-being, and health goals. Sexual concerns or dysfunction may also signal undiagnosed health conditions. Additionally, collecting SOGI information as part of a sexual health assessment would allow providers to address problems that drive disparities for LGBTQ+ populations.Barriers to Assessing Sexual Health:Unfortunately, healthcare providers do not routinely assess sexual health in clinical practice. One barrier to assessing sexual health is a gap in communication between patients and providers. Providers cite beliefs that 1) patients will bring up sexual concerns themselves or 2) that patients might be offended by discussing sexual health. By contrast, patients often report 1) an expectation that providers will bring up sexual health and 2) being comfortable with discussing sexual health with their providers.Within the VHA, the lack of a sexual health template within the electronic health record (EHR) adds an additional technological barrier. The VHA’s transition toward whole health and updates to its EHR will provide unique opportunities to integrate sexual health assessment into routine care. We highlight future system modifications to address this within the VHA. These examples may be helpful for other healthcare systems interested in moving to a whole health model of care.Overcoming Barriers to Sexual Health Assessment:Given the multifaceted barriers to sexual health assessment, it will be vital for healthcare systems integrating a whole health approach to develop both practical and educational interventions to address the communication gap. These interventions will need to target both providers and patients in healthcare systems that transition to a whole health model of care, not just the VHA.Conclusions:Both the communication gap between providers and patients and the lack of support within some EHR systems for sexual health assessment are barriers to assessing sexual health in primary care clinics. Routine sexual health assessment would benefit patient well-being and present an opportunity to address health disparities for lesbian, gay, bisexual, transgender, queer and similar minority (LGBTQ+) populations. Healthcare systems (i.e., both the VHA and other systems) can overcome these barriers by implementing educational interventions and updating their EHRs and back-end data structures. VHA’s expertise in developing and implementing health education interventions and EHR-based quality improvements may help inform interventions beyond VHA.

The role of smoking in the risk of SARS-CoV-2 infection is unclear. We used a retrospective cohort design to study data from veterans’ Electronic Medical Record to assess the impact of smoking on the risk of SARS-CoV-2 infection. Veterans tested for the SARS-CoV-2 virus from 02/01/2020 to 02/28/2021 were classified as: Never Smokers (NS), Former Smokers (FS), and Current Smokers (CS). We report the adjusted odds ratios (aOR) for potential confounders obtained from a cascade machine learning algorithm. We found a 19.6% positivity rate among 1,176,306 veterans tested for SARS-CoV-2 infection. The positivity proportion among NS (22.0%) was higher compared with FS (19.2%) and CS (11.5%). The adjusted odds of testing positive for CS (aOR:0.51; 95%CI: 0.50, 0.52) and FS (aOR:0.89; 95%CI:0.88, 0.90) were significantly lower compared with NS. Four pre-existing conditions, including dementia, lower respiratory infections, pneumonia, and septic shock, were associated with a higher risk of testing positive, whereas the use of the decongestant drug phenylephrine or having a history of cancer were associated with a lower risk. CS and FS compared with NS had lower risks of testing positive for SARS-CoV-2. These findings highlight our evolving understanding of the role of smoking status on the risk of SARS-CoV-2 infection.

ObjectivesTo perform an international comparison of the trajectory of laboratory values among hospitalized patients with COVID-19 who develop severe disease and identify optimal timing of laboratory value collection to predict severity across hospitals and regions.DesignRetrospective cohort study.SettingThe Consortium for Clinical Characterization of COVID-19 by EHR (4CE), an international multi-site data-sharing collaborative of 342 hospitals in the US and in Europe.ParticipantsPatients hospitalized with COVID-19, admitted before or after PCR-confirmed result for SARS-CoV-2.Primary and secondary outcome measuresPatients were categorized as “ever-severe” or “never-severe” using the validated 4CE severity criteria. Eighteen laboratory tests associated with poor COVID-19-related outcomes were evaluated for predictive accuracy by area under the curve (AUC), compared between the severity categories. Subgroup analysis was performed to validate a subset of laboratory values as predictive of severity against a published algorithm. A subset of laboratory values (CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin) was compared between North American and European sites for severity prediction.ResultsOf 36,447 patients with COVID-19, 19,953 (43.7%) were categorized as ever-severe. Most patients (78.7%) were 50 years of age or older and male (60.5%). Longitudinal trajectories of CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin showed association with disease severity. Significant differences of laboratory values at admission were found between the two groups. With the exception of D-dimer, predictive discrimination of laboratory values did not improve after admission. Sub-group analysis using age, D-dimer, CRP, and lymphocyte count as predictive of severity at admission showed similar discrimination to a published algorithm (AUC=0.88 and 0.91, respectively). Both models deteriorated in predictive accuracy as the disease progressed. On average, no difference in severity prediction was found between North American and European sites.ConclusionsLaboratory test values at admission can be used to predict severity in patients with COVID-19. Prediction models show consistency across international sites highlighting the potential generalizability of these models.