Sylvia Sudat, Ph.D.

Dr. Sudat is a Sr. Biostatistician and Scientist at the Center for Health Systems Research (CHSR). She is also a core member of the Sutter Health Institute for Advancing Health Equity (IAHE) and the Data Science team.

Over her 17-year career at Sutter Health, she has developed methods for accessing, extracting, and analyzing complex health data from multi-source electronic health records (EHRs) for clinical and observational research.

Dr. Sudat provides statistical consultation and support to Sutter researchers, and leads projects using large EHR datasets to address questions and challenges facing healthcare delivery, patient experience, and health equity.

She has 13 years’ experience in palliative care, and led the evaluation of the Sutter Health Advanced Illness Management® (AIM) program. Using findings from AIM and with EHR data, Dr. Sudat developed an algorithm to prospectively identify patients potentially eligible for palliative care, which has been implemented across Sutter Health. Her other recent work includes identification of natural subgroups of migraine using latent class analysis, and estimation of the impact of pulse oximeter inaccuracy on treatment course for Black patients with COVID-19.

Dr. Sudat currently leads projects characterizing COVID-19 treatment trajectories, evaluating practical implementation of predictive models, and improving Sutter Health’s palliative and advanced illness care identification algorithm. She is also a co-Investigator, biostatistician, and consultant on various other projects.

Dr. Sudat completed graduate training in Biostatistics at the University of California at Berkeley, where she focused on risk prediction and semi-parametric methods for estimation in the context of causal inference and observational health data.