The American Statistical Association (ASA) Statistics and Data Science in Aging (SDSA) Interest Group is pleased to announce the launch of a new webinar series!
SDSA thanks the ASA and SDSA sponsors:
The University of Maryland Claude D. Pepper Older Americans Independence Center (UM-OAIC)
The University of Maryland School of Medicine Center for Research on Aging
Inaugural webinar details:
Speaker: Wenbo Wu, PhD, Assistant Professor, Division of Biostatistics of the Department of Population Health and the Division of Nephrology of the Department of Medicine at the New York University (NYU) Grossman School of Medicine
Title: Data Science-Powered Provider Profiling for Equitable Quality Care in Alzheimer's and Dementia
When: September 30 2024, 1-2pm ET/12-1pm CT/11am-12pm MT/10-11am PT
Where: Zoom; Register here - https://amstat.zoom.us/webinar/register/WN_MNQDqklRRpWLSq7nDzs8xg
Abstract: As the number and diversity of Americans affected by Alzheimer's disease and related dementias (ADRD) continue to rise, minority ADRD patients face ongoing racial/ethnic disparities in the quality of care, leading to increased adverse health events. Care discrimination has been attributed to issues with health care providers, e.g., implicit bias and lack of cultural competence. Preventing these issues from perpetuating disparities not only calls for preparing providers for a diverse patient population. More importantly, it warrants provider monitoring (profiling) to enhance evidence-based accountability for inequitable quality of care. Provider profiling is a widely used comparative evaluation tool to inform patients' care decision making and to improve the quality of care delivered by health care providers. Based on standardized quality measures of patient outcomes, this process entails quantifying provider performance and pinpointing providers with subpar performance. Current methods for profiling activities rely on risk adjustment models with the linearity assumption, often too restrictive to characterize complex associations between risk factors and outcomes. Moreover, these methods, having been historically driven by the demand for controlling care expenditures, tend to pool all racial/ethnic groups without accounting for their socioeconomic heterogeneity. Despite the importance of distinguishing between cost-driven and equity-driven profiling, a theoretical framework capable of addressing these different but related profiling objectives is still lacking, due in part to the absence of a unifying approach that defines context-specific performance benchmarks. To address these issues, we propose a versatile probability framework based on hypothetical reference providers corresponding to specific profiling objectives. Furthermore, we develop flexible machine learning approaches that relax the linearity assumption. These methods will advance the methodology of provider profiling, thereby triggering improved care-seeking decision-making by patients and stakeholders and evidence-based accountability of providers.
Speaker Bio: Wenbo Wu is a tenure-track Assistant Professor in the Division of Biostatistics of the Department of Population Health and the Division of Nephrology of the Department of Medicine at the New York University (NYU) Grossman School of Medicine. He is also an affiliated faculty member of the NYU Center for Data Science. His current research synthesizes methods from statistics, machine learning, causal inference, and computational science to address significant issues of health equity, outcomes, services, and clinical practice in aging and nephrology, leveraging disease registries, administrative claims, electronic health records, and randomized controlled trials. He was recently selected as a Butler-Williams Scholar by the National Institute on Aging. Dr. Wu received his PhD in Biostatistics and Scientific Computing from the University of Michigan in 2022.
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Michelle Shardell
Professor
Institute for Genome Sciences, University of Maryland School of Medicine
Inaugural Program Chair, Statistics and Data Science in Aging Interest Group
Co-Director, Biostatistics Core, The University of Maryland Claude D. Pepper Older Americans Independence Center (UM-OAIC)
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