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Browsing by Subject "United States Department of Veterans Affairs"
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Item Racial and Ethnic Differences in Total Knee Arthroplasty in the Veterans Affairs Health Care System, 2001-2013(Wiley, 2017-08) Hausmann, Leslie R.M.; Brandt, Cynthia A.; Carroll, Constance M.; Fenton, Brenda T.; Ibrahim, Said A.; Becker, William C.; Burgess, Diana J.; Wandner, Laura D.; Bair, Matthew J.; Goulet, Joseph L.; Medicine, School of MedicineOBJECTIVE: To examine black-white and Hispanic-white differences in total knee arthroplasty from 2001 to 2013 in a large cohort of patients diagnosed with osteoarthritis (OA) in the Veterans Affairs (VA) health care system. METHODS: Data were from the VA Musculoskeletal Disorders cohort, which includes data from electronic health records of more than 5.4 million veterans with musculoskeletal disorders diagnoses. We included white (non-Hispanic), black (non-Hispanic), and Hispanic (any race) veterans, age ≥50 years, with an OA diagnosis from 2001-2011 (n = 539,841). Veterans were followed from their first OA diagnosis until September 30, 2013. As a proxy for increased clinical severity, analyses were also conducted for a subsample restricted to those who saw an orthopedic or rheumatology specialist (n = 148,844). We used Cox proportional hazards regression to examine racial and ethnic differences in total knee arthroplasty by year of OA diagnosis, adjusting for age, sex, body mass index, physical and mental diagnoses, and pain intensity scores. RESULTS: We identified 12,087 total knee arthroplasty procedures in a sample of 473,170 white, 50,172 black, and 16,499 Hispanic veterans. In adjusted models examining black-white and Hispanic-white differences by year of OA diagnosis, total knee arthroplasty rates were lower for black than for white veterans diagnosed in all but 2 years. There were no Hispanic-white differences regardless of when diagnosis occurred. These patterns held in the specialty clinic subsample. CONCLUSION: Black-white differences in total knee arthroplasty appear to be persistent in the VA, even after controlling for potential clinical confounders.Item A Telehealth-Based Randomized Controlled Trial: A Model for Outpatients Trials of Off-Label Medications During the COVID-19 Pandemic(Sage, 2021-08) Keyhani, Salomeh; Kelly, J. Daniel; Bent, Stephen; Boscardin, W. John; Shlipak, Michael G.; Leonard, Sam; Abraham, Ann; Lum, Emily; Lau, Nicholas; Austin, Charles; Oldenburg, Catherine E.; Zillich, Allan; Lopez, Lenny; Zhang, Ying; Lietman, Tom; Bravata, Dawn M.; Medicine, School of MedicineThe study was registered at clinicaltrials.gov: NCT04363203Item Using Research to Transform Electronic Health Record Modernization: Advancing a VA Partnered Research Agenda to Increase Research Impacts(Springer, 2023) Cogan, Alison M.; Rinne, Seppo T.; Weiner, Michael; Simon, Steven; Davila, Jessica; Yano, Elizabeth M.; Medicine, School of MedicineBackground: The U.S. Department of Veterans Affairs (VA) is undergoing an enterprise-wide transition from a homegrown electronic health record (EHR) system to a commercial off-the-shelf product. Because of the far-reaching effects of the EHR transformation through all aspects of the healthcare system, VA Health Services Research and Development identified a need to develop a research agenda that aligned with health system priorities so that work may inform evidence-based improvements in implementation processes and outcomes. Objective: The purpose of this paper is to report on the development of a research agenda designed to optimize the EHR transition processes and implementation outcomes in a large, national integrated delivery system. Design: We used a sequential mixed-methods approach (portfolio assessment, literature review) combined with multi-level stakeholder engagement approach that included research, informatics, and healthcare operations experts in EHR transitions in and outside the VA. Data from each stage were integrated iteratively to identify and prioritize key research areas within and across all stakeholder groups. Participants: VA informatics researchers, regional VA health system leaders, national VA program office leaders, and external informatics experts with EHR transition experience. Key results: Through three rounds of stakeholder engagement, priority research topics were identified that focused on operations, user experience, patient safety, clinical outcomes, value realization, and informatics innovations. Conclusions: The resulting EHR-focused research agenda was designed to guide development and conduct of rigorous research evidence aimed at providing actionable results to address the needs of operations partners, clinicians, clinical staff, patients, and other stakeholders. Continued investment in research and evaluation from both research and operations divisions of VA will be critical to executing the research agenda, ensuring its salience and value to the health system and its end users, and ultimately realizing the promise of this EHR transition.Item Validation of Stroke Meaningful Use Measures in a National Electronic Health Record System(Springer-Verlag, 2016-04) Phipps, Michael S.; Fahner, Jeff; Sager, Danielle; Coffing, Jessica; Maryfield, Bailey; Williams, Linda S.; Department of Neurology, School of MedicineBACKGROUND: The Meaningful Use (MU) program has increased the national emphasis on electronic measurement of hospital quality. OBJECTIVE: To evaluate stroke MU and one VHA stroke electronic clinical quality measure (eCQM) in national VHA data and determine sources of error in using centralized electronic health record (EHR) data. DESIGN: Our study is a retrospective cross-sectional study of stroke quality measure eCQMs vs. chart review in a national EHR. We developed local SQL algorithms to generate the eCQMs, then modified them to run on VHA Central Data Warehouse (CDW) data. eCQM results were generated from CDW data in 2130 ischemic stroke admissions in 11 VHA hospitals. Local and CDW results were compared to chart review. MAIN MEASURES: We calculated the raw proportion of matching cases, sensitivity/specificity, and positive/negative predictive values (PPV/NPV) for the numerators and denominators of each eCQM. To assess overall agreement for each eCQM, we calculated a weighted kappa and prevalence-adjusted bias-adjusted kappa statistic for a three-level outcome: ineligible, eligible-passed, or eligible-failed. KEY RESULTS: In five eCQMs, the proportion of matched cases between CDW and chart ranged from 95.4 %-99.7 % (denominators) and 87.7 %-97.9 % (numerators). PPVs tended to be higher (range 96.8 %-100 % in CDW) with NPVs less stable and lower. Prevalence-adjusted bias-adjusted kappas for overall agreement ranged from 0.73-0.95. Common errors included difficulty in identifying: (1) mechanical VTE prophylaxis devices, (2) hospice and other specific discharge disposition, and (3) contraindications to receiving care processes. CONCLUSIONS: Stroke MU indicators can be relatively accurately generated from existing EHR systems (nearly 90 % match to chart review), but accuracy decreases slightly in central compared to local data sources. To improve stroke MU measure accuracy, EHRs should include standardized data elements for devices, discharge disposition (including hospice and comfort care status), and recording contraindications.