Candidate: David Kao MD is an Assistant Professor of Medicine in the Division of Cardiology at the University of Colorado Denver (UCD). In addition to clinical training in internal medicine and cardiology, he has completed 1 year of postdoctoral training in biomedical informatics (T15 LM007033, PI: Altman) and 2 years in cardiovascular research (T32 HL007822, PI: Buttrick). He uses bioinformatics methods applied to data ranging from regional administrative data to patient-level data from clinical trials to longitudinal gene expression data in order to develop multi-tiered strategies for personalizing of heart failure (HF) management. Training: The proposed career development plan will apply Dr. Kao's prior research experiences, which have exclusively used publicly available and clinical trial data, to real-world clinical data in three focus areas: 1) management and governance of disease-specific institutional data warehouse construction, 2) high-throughput analysis methods using real-world clinical data, and 3) dissemination and implementation of evidence-based practice recommendations for HF patients. Additional training in these focus areas will enable Dr. Kao to apply his clinical and informatics knowledge to real-world clinical data, preparing him to be an independent, funded investigator in research studying development and prospective implementation of personalized, patient- centered heart failure management strategies using electronic health record data. Accordingly, Dr. Kao's mentorship team consists of experts in cardiovascular disease registries and personalized HF management and experts in data warehouses, bioinformatics, and decision support. Mentors/Environment: Michael Kahn MD PhD (co-Primary Mentor) is a Professor at UCD, Director of the UCD's institutional clinical data warehouse, and Co-Director of the Colorado Clinical and Translational Sciences Institute; he will provide mentorship regarding data warehouse construction and governance, and decision support. Michael Bristow MD PhD (co-Primary Mentor) is a Professor at UCD with over 30 years of experience in clinical and translational HF research; he will provide mentorship for translational of clinical phenotype analyses to prospective clinical trials investigating personalized HF management. John Rumsfeld MD PhD is a Professor at UCD, Chief Innovation Officer for the American College of Cardiology, Chairman of the National Cardiovascular Data Registries (NCDR) Management Board (formerly Chief Science Officer), and Chairman of the AHA Scientific Council on Quality of Care and Outcomes Research. He will provide mentorship on cardiovascular registry development and dissemination via electronic health record. Larry Hunter, PhD is a Professor at UCD is Director of the Center for Computational Biology; he will oversee didactic activities, and provide guidance regarding management of large, complex datasets, and high-throughput analytic methods. Peter Buttrick MD is Senior Associated Dean of Academic Affairs for the University of Colorado School of Medicine, Division Head of Cardiology at UCD and primary investigator for the T32 Cardiovascular Research Training Grant. Dr. Buttrick will provide mentorship regarding coordination of multidisciplinary research, publications, and funding opportunities. Research: Because of the heterogeneity among HF patients with respect to prognosis and treatment response, there is a pressing need to improve the precision of HF risk prediction and management strategies. This study will 1) integrate real-world clinical and experimental data relevant to the diagnosis and management of HF, 2) discover and validate personalized risk models and potential treatment strategies and 3) use real- time decision support technology to study implementation and efficacy of evidence-based HF treatment strategies in clinical practice and assess their effect in real-world settings. Summary: Upon completion of this training proposal, Dr. Kao will have sufficient knowledge and experience to transition to an independent investigator in funded research focused on formulation and dissemination of strategies for personalized management of HF and large-scale data coordination centers for cardiovascular disease.
Heart failure is a major cause of morbidity and mortality, and our ability to identify high-risk patients likely to die or be hospitalized versus those likely to get better over time with treatment remains limited. The potential of electronic health records to optimize heart failure therapy and personalize medical care has not been unrealized because of fragmented computer systems, lack of techniques to analyze complex clinical data comprehensively, and limited application of research methods that determine effectiveness of electronic health record-based treatment recommendations. The objective of this project is to gain the additional training and experience and mentorship to create and evaluate a system for collecting and analyzing electronic health data important for managing heart failure patients, use those data to discover ways of improving management of heart failure, send personalized treatment suggestions directly to a patient's doctor while the patient is being seen, and determine how effective those suggestions are in improving quality of patient care. Once built, this system can then be adapted for management of other chronic cardiovascular conditions.
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