Brook I. Martin, MPH, PhD
- Departments: Orthopaedics - Research Associate Professor, Population Health Sciences - Adjunct Associate Professor
- Divisions: Health System Innovation and Research
Dr. Martin is a Research Associate Professor of Orthopaedics and Adjunct Associate Professor in Population Health Sciences (Health System Innovation and Research). His serves as a musculoskeletal outcomes health service researcher evaluating the effects of coverage and reimbursement policy on utilization and outcomes. He is a member of the International Society for the Study of the Lumbar Spine, and served on the Public Health, Service Delivery and Reimbursement working group of the Interagency Pain Research Coordinating Committee, part of the National Pain Strategy. As a previous co-investigator on two NIAMS-funded Multidisciplinary Clinical Research Centers on musculoskeletal disease, he has published peer-reviewed articles on the economic burden of back pain, trends in the use bone morphogenetic proteins in lumbar fusion, and provider variation in safety of spine surgery. He currently oversees the centralized longitudinal collection of patient-reported outcomes from 25 sites participating in the PCORI-funded Comparative Effectiveness of Pulmonary Embolism Prevention after Hip and Knee Replacement (PEPPER) trial.
My research focuses on evaluating the effects of coverage and reimbursement policies in orthopaedic surgery, including assessing the impact that evolving payment reform policies have on health care utilization, safety and ultimately patient well-being. For example, through an AHRQ-funded R01 I am examining the effects of the Center for Medicare and Medicaid Innovation’s (CMMI) Comprehensive Care for Joint Replacement program, a bundled payment program referencing regional-based pricing.
I’ve had a longstanding interest in research related to back pain, and more specifically on the safety of spine surgery, where I have broad expertise in the analysis of administrative health care databases (including Medicare, HCUP and MEPS), multi-level modelling in observational data, analysis of surveys involving complex sampling strategies, and applied Bayesian approaches to safety monitoring.
|Doctoral Training||University of Washington
|Graduate Training||University of Washington
|Undergraduate||University of Oregon