The proposed training and research in this K01 application is designed to further my long-term career goal. My goal is to become a leading health services researcher with an expertise in mixed-methods in the area of reshaping physician incentives for more efficient and equitable health care delivery. For the next step in my career, I aim to strengthen my ability to conduct multidisciplinary research in a clinical care setting, with additional training with the following objectives: (1) learn how to conduct mixed-methods research, (2) identify strengths and weaknesses of data collected from clinical practice for research use, (3) understand primary care delivery and billing practices, and (4) comprehend multi-disciplinary explanations of physician incentive and practice variation. The proposed intensive training capitalizes on the wealth of intellectual resources and research support at the Palo Alto Medical Foundation Research Institute (PAMFRI), didactic courses and professional seminars at Stanford, communications with and feedback from Palo Alto Medical Foundation (PAMF) leaders and clinicians, and strong support from a multidisciplinary team of experienced mentors. With the rigorous training, including the planned research activities, I will acquire varied tools and perspectives to understand physician behavior so that my research will inform physicians and policy makers, and thus successfully impact policy and practice. The proposed research seeks to explore the sources of variation in coded billing level of primary care office visits, taking into account the comprehensive scope of primary care work beyond office visit that are currently not explicitly compensated. The goal of this study is to develop evidence on how primary care physician (PCP)'s patient care activities should be measured and compensated to better reflect PCPs'and their teams'effort. The research uses detailed and longitudinally linked EHR-based data to put the visit in the context of patient's clinical history, socioeconomic factors, prior experience with the PCP, and outside-of-visit contacts with clinicians and staff (Aim 1). Qualitative investigation of unexplained coding variation will further inform how physicians use the current system to bill for their effort (Aim 2). The overall findings will be discussed with PAMF physicians and leaders to formulate recommendations to modify internal physician payment schemes (Aim 3). The research takes advantage of the exceptional opportunities I have as a researcher at the Research Institute associated with PAMF, one of the nation's largest multi-specialty group practices. PAMF patients reflect great diversity in insurance and race/ethnicity, but PAMF uses a single billing and a uniform internal physician payment structure, eliminating the unmeasured inconsistencies in administrative practices across multiple practices and the variations in incentive structures across multiple payers. It is also exceptional to have strong support from PAMF leadership to facilitate the qualitative part of the study, obtain feedback on my study findings, and be involved in the discussions to modify physician payment schemes. By successfully integrating what I have learned through the proposed research and training with my existing base of knowledge, I will be able to apply myself as a competent researcher across disciplines in the area of reshaping physician incentives to appropriately reward high quality and efficient care, and will be well positioned to obtain R01 level funding to continue my long-term career with this focus.

Public Health Relevance

Findings of the study will contribute to improve the payment system of health care providers so that providers are encouraged to use innovative and efficient ways to deliver care, experience a higher quality of work life, and are more satisfied with their work. Patients will benefit from a health care system with efficient, high quality care.

National Institute of Health (NIH)
Agency for Healthcare Research and Quality (AHRQ)
Research Scientist Development Award - Research & Training (K01)
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Health Systems Research (HSR)
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Anderson, Kay
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Palo Alto Medical Foundation Research Institute
Palo Alto
United States
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