Bayesian Procedures for File Linking with Application to Health Services Research – Roee Gutman
On April 1, 2022, Roee Gutman presented work that views record linkage as a missing data problem and he described Bayesian procedures that utilize data features that are frequently encountered in public health applications. These procedures improve the linkage, and result in more accurate and precise estimates of scientifically important associations. The first procedure incorporates associations between variables exclusive to one of the datasets in the linkage process. The second procedure ensures that individuals receiving care from the same provider in one file are linked to individuals receiving care from a similar provider in the other file. Roee demonstrated these procedures using two applications: one combines Medicare claims records and Vital Statistics Mortality records to study the association between end-of-life medical expenses and causes of death. A second application combines records from the National Trauma Databank with Medicare claims data to study the relationship between injury characteristics and successful discharge to the community among patients with traumatic brain injury.
Roee Gutman: Roee Gutman is an Associate Professor in the Department of Biostatistics at Brown University. His areas of expertise are causal inference, file linkage, missing data, Bayesian analysis and their application to health services research. He has been the lead statistician on multiple NIH and VA grants, and he has received two PCORI methods award. Roee has developed multiple procedures to link and analyze healthcare data.