Two of a series of in-person workshops in 2020-2022 will be hosted at Duke to provide new knowledge on how existing and recently developed analytic methods can be used for detailed population and clinical data analysis in order to make progress in understanding the causes and mechanisms of health-related disparities in Alzheimer?s disease (AD), related dementias (ADRD), and other prominent age-related diseases. The long- term goal of the series is to provide a resource focused on diffusing methodological know-how in terms of demonstrating the capabilities of newly developed methodologies, expanding on the rigor and range of application of well-established and familiar methods, promoting correct use of big health data both from a methodological and ethical prospective as well as providing a forum for experts and newcomers interested in health disparities and age-related diseases to discuss their ideas and promote their research. The pilot Duke- NIA workshop of the series held in February 2019 at Duke University was successful in drawing broad scientific interest to the topic and generated the background for the current proposal. The focus of the first workshop (planned in Winter 2020/2021) will be on demonstrating how studies using established administrative health data resources such as the Medicare claims database combined with innovative analytic approaches such as partitioning analyses, time-series based methods of projection/forecasting, and stochastic process models can be used to uncover previously overlooked and/or understudied aspects in this area of research. Specific topics to be discussed will include: i) disparities in risks and survival of AD/ADRD and other age- related diseases; ii) forecasting approaches for prevalence and mortality of AD/ADRD and other age-related diseases; iii) analysis of Medicare and other administrative claim-based data. The focus of the second workshop (planned in Winter 2021/2022) will extend this to include the health records data routinely collected in hospitals or University medical centers (e.g., the Duke Clinical Data Warehouse) and demonstrate how well- established and new analytic methods can be rigorously applied to such data to contribute to identifying the causes of persistent health disparities between specific groups of the U.S. population and narrowly defined patient strata. Specific topics will be expanded to include: i) analytic approaches to identify and quantify the contribution of treatment-related and medical care access-related factors to disparities in outcomes of AD/ADRD and other age-related diseases; ii) comorbidity, multimorbidity, treatment-related, social and genetic factors as sources of disparities in health outcomes of AD/ADRD and other age-related diseases; iii) forecasting of health outcomes and approaches for analyses of potential health interventions. The proceedings will be streamed live on the workshop website and presentations will be freely available in text and video form after the fact.
Our objective is to host two in-person workshops in 2020-2021, in which research findings and evidence-based information and analytic tools for analyses of health-related disparities in Alzheimer?s disease, related dementias and other prominent age-related diseases are discussed. Specific Aims to be addressed in this project will be focused on increased collaboration and partnership in an interdisciplinary research community focused on analytic methods for large-scale population and clinic-related data, constructing a bridge between independent research subgroups, and the identification of ways to achieve synergistic effects in multidisciplinary research by combining innovative approaches developed across different research groups. Ultimately, our long-term goal is to diffuse the active use of advanced analytic methods for analyses of existing big health population datasets in health disparity research.
