Health Insurance Claims Analysis

Several CRHC faculty have expertise in conducting health insurance claims analyses and apply innovative methods like latent class analysis to study the dual use of VA and non-VA care. Dr. Radomski, for example, is developing, validating, and applying a patient-centered metric of low-value prescribing (LVP) using administrative data in order to measure and reduce low-value care. Dr. Gellad is applying novel machine learning approaches to administrative claims data to predict who is at risk of problematic prescription opioid use and overdose.


Faculty

Yi-Fan Chen, PhD

Dr. Chen has been a biostatistician with extensive experience in collaborative research and hands-on data analysis since 2013. She is also interested in machine learning, particularly tree-based modeling for subgroup identification, the design and analysis of clinical trials, and meta-analysis.

Walid F. Gellad, MD, MPH

Director, Center for Pharmaceutical Policy and Prescribing

Dr. Gellad’s research focuses on physician prescribing practices and policy issues affecting access and adherence to medications for patients. Two of his current projects use novel machine learning approaches to determine risk of adverse events among patients who are prescribed opioids. Data for these studies include Medicare, Pennsylvania Medicaid, and Allegheny County service use claims.

Aimee Pickering, MD, MS

Dr. Pickering provides clinical care as a primary cary phsycian and teaching attending, while also conducting research on characterizing and reducing low-value care and subsequent care cascades and deprescribing low-value medications in older adults. She is particularly interested in applying implementation science principles to develop strategies to support deprescribing and in the de-implementation of other low-value practices.

Thomas R. Radomski, MD, MS

Dr. Radomski conducts research on health care delivery, financing, and utilization. He has adapted a medication-based risk adjustment method in order to overcome limitations of claims-based risk adjustment using ICD-9 codes. His current work involves studying the prevalence and determinants of low-value test and procedure use among Veterans with a focus on the dual use of VA and Medicare services.

Katie J. Suda, PharmD, MS, FCCP

Dr. Suda’s area of research is pharmacoepidemiology, especially in the area of antimicrobials, and dual use of VA and non-VA health care. Currently, she is researching antibiotics and opioids in dental prescribing, including a focus on Veteran health.