Stanford Health Policy is a joint effort of the Freeman Spogli Institute for International Studies and the Stanford School of Medicine
117 Encina Commons - Second Floor Conference Room
VA Palo Alto Health Care System Medical Service (111) 3801 Miranda Avenue Palo Alto, CA 94304;
Encina Commons, 615 Crothers Way Room 210, Stanford, CA 94305-6006
Mary K. Goldstein is a Professor of Health Policy and a core faculty member at the Department of Health Policy and the Center for Health Policy, and the Director of the Geriatrics Research Education and Clinical Center (GRECC) at the VA Palo Alto Health Care System. She directs the Primary Care Policy and Practice Advancement program at PCOR, the Stanford/VA Palo Alto Geriatric Medicine Fellowship Program, and the Special Fellowship Program in Advanced Geriatrics at VA Palo Alto. She also serves as associate director for the Physician Post-Residency Fellowship Program in Health Services Research and Development, and for the Postdoctoral Fellowship in Medical Informatics, both at VA Palo Alto Health Care System.
Goldstein studies innovative methods of implementing evidence-based clinical practice guidelines for quality improvement. She leads the ATHENA Decision Support System project that has developed and implemented an automated clinical decision support system for primary care clinicians, using hypertension as a model, and now extended into several other clinical domains. Goldstein's research also explores older adults' health preferences (health utility) for application to cost-effectiveness analysis.
Goldstein is a fellow of the American Geriatrics Society, and an emerita of the Society's board of directors. Goldstein has received a number of honors and awards including an Advanced Career Development award from the Department of Veterans Affairs Health Services Research and Development (HSR&D) program. She received a BA in philosophy and an MD, both from Columbia University, and completed her residency in family medicine at Duke University Medical Center. At the Stanford School of Medicine she completed an AHRQ-funded fellowship and an MS in health services research.
This project aims to develop a standardized computational framework for clinical practice guideline specification that will allow text guidelines to be easily translated into computable formats by clinical domain experts. These computable guidelines will then be directly applicable to real-time clinical decision support and to retrospective quality assessment of electronic medical records.
Encina Commons, Room 201
615 Crothers Way Stanford, CA 94305-6006
Executive Assistant: Soomin Li, soominli@stanford.edu
Phone: (650) 725-9911
Douglas K. Owens is the Henry J. Kaiser, Jr. Professor, Chair of the Department of Health Policy in the Stanford University School of Medicine and Director of the Center for Health Policy (CHP) in the Freeman Spogli Institute for International Studies (FSI). He is a general internist, a Professor of Management Science and Engineering (by courtesy), at Stanford University; and a Senior Fellow at the Freeman Spogli Institute for International Studies.
Owens' research includes the application of decision theory to clinical and health policy problems; clinical decision making; methods for developing clinical guidelines; decision support; comparative effectiveness; modeling substance use and infectious diseases; cardiovascular disease; patient-centered decision making; assessing the value of health care services, including cost-effectiveness analysis; quality of care; and evidence synthesis.
Owens chaired the Clinical Guidelines Committee of the American College of Physicians for four years. The guideline committee develops clinical guidelines that are used widely and are published regularly in the Annals of Internal Medicine. He was a member and then Vice-Chair and Chair of the U.S. Preventive Services Task Force, which develops national guidelines on preventive care, including guidelines for screening for breast, colorectal, prostate, and lung cancer. He has helped lead the development of more than 50 national guidelines on treatment and prevention. He also was a member of the Second Panel on Cost Effectiveness in Health and Medicine, which developed guidelines for the conduct of cost-effectiveness analyses.
Owens also directed the Stanford-UCSF Evidence-based Practice Center. He co-directs the Stanford Health Services Research Program, and previously directed the VA Physician Fellowship in Health Services Research, and the VA Postdoctoral Informatics Fellowship Program.
Owens received a BS and an MS from Stanford University, and an MD from the University of California-San Francisco. He completed a residency in internal medicine at the University of Pennsylvania and a fellowship in health research and policy at Stanford. Owens is a past-President of the Society for Medical Decision Making. He received the VA Undersecretary’s Award for Outstanding Achievement in Health Services Research, and the Eisenberg Award for Leadership in Medical Decision Making from the Society for Medical Decision Making. Owens also received a MERIT award from the National Institutes on Drug Abuse to study HIV, HCV, and the opioid epidemic. He was elected to the American Society for Clinical Investigation (ASCI) and the Association of American Physicians (AAP.)
Stanford Prevention Research Center
Stanford University
1000 Welch Road
Palo Alto, CA 94304-1825
Randall Stafford is an associate professor of medicine at the Stanford Prevention Research Center and a fellow at CHP/PCOR. He is an epidemiologist, health services researcher and primary-care internist. His research focuses on patient and physician interventions to improve chronic disease prevention, and the mechanisms by which physicians adopt new prevention practices. Many of his published studies have documented and raised concerns about the so-called "quality gap" -- the healthcare system's failure to consistently implement clinically proven therapies -- and have helped shape policy initiatives aimed at improving medical care. His research has also focused on drug costs and patterns of medication prescribing. At the Stanford Prevention Research Center, he directs the Program on Prevention and Outcomes Practices. He maintains clinical responsibilities at Stanford's Preventive Cardiology and Internal Medicine clinics, and serves on Stanford Medical School's faculty Senate.
From 1994 to 2001 he served on the faculty at Harvard University Medical School and at Massachusetts General Hospital's Institute for Health Policy, where he was principal investigator on several federally funded projects that assessed and sought to improve physician practices. As assistant director of primary care operations improvement at Massachusetts General, he led several projects aimed at improving the quality of outpatient care at the hospital. He joined the Stanford faculty in 2001.
Stafford earned a BA in sociology from Reed College, an MS in health administration from Johns Hopkins University, an MD from UC-San Francisco and a PhD in epidemiology from UC-Berkeley. He completed an internal medicine residency at Massachusetts General Hospital and a fellowship in epidemiology at the federal Centers for Disease Control and Prevention.
BACKGROUND: Electronically available data, both administrative, such as outpatient encounter diagnostic data, and clinical, such as problem lists, are being used increasingly for outcome and quality assessment, risk adjustment, and clinical reminder systems. OBJECTIVE: To determine the accuracy of outpatient primary care diagnostic information recorded in administrative and clinical files in a Veterans Affairs VISTA (Veterans Health Information Systems and Technology Architecture) database compared with medical chart notes. STUDY DESIGN: Cross-sectional medical chart review of 148 patients attending a general medicine clinic at a university-affiliated Veterans Affairs hospital for 9 diagnoses relevant to the choice of drug therapy for hypertension. PATIENTS AND METHODS: An administrative file of encounter diagnoses, for a 2-year period, and a clinical file of the problem list maintained by the clinician were the sources of electronic diagnoses. We compared these sources with diagnoses abstracted by medical chart review. We estimated the sensitivity and specificity of each electronic data source for detecting medical chart note diagnoses. RESULTS: The sensitivity for 8 of the 9 study diagnoses was greater than 80% in the administrative file and 49% in the clinical problem list. The specificity was good for the administrative file (91% to 100%) and even better for the clinical file (98% to 100%). CONCLUSIONS: Outpatient encounter diagnoses relevant to hypertension recorded as electronic data had high specificity, and some codes had high sensitivity when collected over multiple visits. The administrative file was more sensitive but less specific than the clinical file. Administrative vs clinical files can be selected to minimize either the false-negative or the false-positive designations, respectively, as dictated by the needs of the quality assessment review.