University of Michigan
Ann Arbor, MI, United States
My enthusiasm for combining technology, clinical practice and standardization has its roots in the work that I did for the Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative, working on both the brainstem and the optic nerve/optic chiasm papers. Over-coming the full scope of barriers to using the vast amount of potentially useful information in our electronic systems so that findings based on thousands instead of tens of patients could become routine became the driving force behind my research interests.
My primary research interest centers on constructing standardized large scale data bases from routine practice data for use in integrating artificial intelligence driven modeling into clinical care. As Director of Informatics and Analytics in the Department of Radiation Oncology I led our team in creation of our platform, named the Michigan Radiation Oncology Analytics Resource System (MROAR), that aggregates, integrates and harmonizes data from the several commercial data systems used to treat radiation oncology patients into a single, easy to use platform. My work with that system includes combining statistical and machine learning methods to construct outcomes models to detail actionable clinical thresholds for the purpose of reducing incidence of radiation dose related toxicities and other undesirable outcomes such as emergency room visits.
I have been fortunate in being able lead large, multi-disciplinary, multi-institutional stakeholder groups in developing standardizations supporting interoperable data exchange. These efforts include TG-263 and presently the Operational Ontology for Radiation Oncology developed in with ASTRO members in AAPMs Big Data Subcommittee.
Disclosures:
Sunday, September 29, 2024
4:55 PM – 5:05 PM ET