Private: Speakers: Keith Feldman, PhD
Keith Feldman, PhD
Health Informatics Researcher
Dr. Feldman is a health informatics researcher whose work explores the ways in which data mining, machine learning, and statistical techniques can aid practitioners and researchers in understanding, analyzing, evaluating, and synthesizing the wealth of health and wellness data now digitally available. Embedded at the core of this work lies the notion of “augmentation, not automation”. Where I aim to enhance the effectiveness of those engaged in the healthcare system, augmenting existing skill sets rather than replacing the individual.
The Healthcare Data Spectrum – Utilizing Multiple Data Sources to Address Novel Healthcare Questions
Coupled with the rise of data science and machine learning, the increasing availability of digitized health and wellness data has provided an exciting opportunity for complex analyses of problems throughout the healthcare domain. Whereas many early works focused on a particular aspect of care, often drawing on data from a specific clinical or administrative data source, it has become clear such a narrow approach is insufficient to capture the complexity of the human condition. Instead, adequately modeling health and wellness problems requires the ability to draw upon data spanning multiple facets of an individual’s biology, their care, and the broader world in which they live.
Accordingly, this talk will present the Healthcare Data Spectrum – a novel conceptual framework designed to provide a comprehensive perspective of health and wellness data as it pertains to an individual. In doing so, it will highlight a few benefits, and challenges, associated with integrating various data sources with regards to both clinical and population health analyses.