Using data analytics to overcome challenges with clinical data and to improve patient engagement and experience

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Cunz 160 and Zoom

Jay Mandrekar, PhD, Professor

Mayo Clinic Department of Quantitative Health Sciences 
https://www.mayo.edu/research/faculty/mandrekar-jay-ph-d/bio-00027572

Jay Mandrekar

Research in academic medical centers, such as Mayo Clinic, offer opportunities to collaborate on clinical research that require novel application of both common and uncommon statistical methods. In this presentation, I will review a few examples to illustrate the use of novel or simple data analytic techniques such as exploratory factor analysis and logistic regression for improving patient participation, engagement and experience in clinical research studies. Specifically, statistical approaches including; 1) use of factor analysis in the development of an abbreviated questionnaire to be used in Multiple Systems Atrophy research 2) development, prediction and validation of a simple risk score for prediction of death for organ donation, and 3) use of Graeco Latin Square design to compare the performance of four liquid crystal displays under typical medical center lighting conditions will be discussed. Findings from these and other studies like these have had a direct impact on patient engagement, patient care, cost savings and improved efficiency.