Ranak Trivedi, PhD, Core Investigator, Ci2i, Veterans Affairs Palo Alto Health Care System, Assistant Professor (Psychiatry and Behavioral Sciences), and Affiliate, Center for Health Policy/Center for Primary Care and Outcomes Research, Stanford University
Steve Asch, MD, MPH, Director, Ci2i, Veterans Affairs Palo Alto Health Care System, Professor of Medicine (General Medical Disciplines), and Affiliate, Center for Health Policy/Center for Primary Care and Outcomes Research, Stanford University
Program Associate Director:
Mary K. Goldstein, MD, MS, Director, Geriatrics Research Education and Clinical Center (GRECC), Veterans Affairs Palo Alto Health Care System, and Professor of Medicine (Center for Primary Care and Outcomes Research) and Professor of Health Research and Policy, Stanford University School of Medicine
CENTER FOR HEATH CARE EVALUATION
VETERANS AFFAIRS PALO ALTO HEALTH CARE SYSTEM
AND STANFORD UNIVERSITY
Fellows are offered an opportunity to combine formal training in Medical Informatics with research applying Medical Informatics to areas of relevance to the VA health care system.
- Acquire skills in state-of-the-art Medical Informatics;
- Gain insight into major current issues in Medical Informatics that are relevant to VA clinical, educational, and research programs;
- Develop expertise in conducting collaborative and interdisciplinary Medical Informatics research;
- Acquire further training in such areas as medical decision-making, information technologies, communications tasks of medical practice, and information systems through seminars and formal coursework.
Fellows will obtain focused training in medical informatics while also having the opportunity to complete foundational coursework in (1) essential health services research methods, (2) implementation sciences and systems redesign, and (3) research in collaboration with operational partners.
Fellows can pursue more advanced work in the context of medical informatics through concentrations:
Health Informatics Concentration: Clinical decision support; computerized order entry and alerts; healthcare information exchange; population health; big data and learning healthcare systems.
Health System Redesign/Implementation Science Concentration: Organizational innovation for value production; implementation design and evaluation.
High-Value Health Care Concentration: Health economics; outcomes research; clinical decision making; health policy.
Fellows will develop an individualized training plan through the guidance of a mentoring committee that will include a career mentor, faculty mentor(s) and implementation/operational partner mentor.
Medical Informatics Research
Research opportunities in medical informatics are aligned with the broader research goals of (1) fostering high value mental health care, (2) fostering high value specialty care for chronic disease, and (3) advancing methods to assess and improve value.
Medical Decision-Making, Clinical Decision Support Systems and Knowledge Acquisition.
- Using analytic approaches to aid development of screening and treatment strategies.
- Designing clinical decision support systems for different medical conditions.
Enhanced User Interface Projects and Related Research.
Quality of Care and Program Evaluation.
- Developing a prototype for manipulation and transfer of electronic medical record data for evaluation of process/quality of care and health outcomes.
- Accounting for quality of life and patient preferences in guiding treatment decisions.
Current Funded Research: Decision Support Systems for Hypertension and Chronic Pain.
Postdoc fellows would work on two currently funded projects: Decision support for hypertension and decision support for chronic pain. These projects focus on methods by which information can be retrieved and utilized more selectively and effectively via processes that: (1) facilitate access to and use of the most relevant patient information for a given need, (2) enhance the electronic exchange, organization and presentation of information in clinical, research and educational settings, (3) use medical ontologies and knowledge bases for storing evidenced based medicine information.
Applicants must be U.S. citizens who have completed an MD and accredited residency or a PhD in computer sciences, medical informatics, decision sciences, economics, or related fields. Applicants with strong quantitative and computer science backgrounds will be given priority. The VA is an equal opportunity employer.
Applicants will be evaluated on their professional training and development to date, professional statement, demonstrated productivity and recommendations. Final selection of fellows will be based on a personal interview.
Professional statement. Applicants should submit a brief statement (not to exceed one single-spaced page) of their research activities and career goals and objectives, how they can contribute to the objectives of the training program, and how the program can contribute to the applicant’s professional development.
Demonstrated productivity. Applicants should provide details on education, professional activities and relevant achievements. In addition, applicants are asked to supply two examples of their work.
Recommendations. Three written letters describing the applicant’s competence, an estimate of how the applicant's performance ranks in relation to that of their peers, and the likelihood of the applicant making a contribution to the field of Medical Informatics.
Interview. After an initial screening phase, top candidates will be interviewed.
VA Contact: Ranak Trivedi, PhD
Center for Innovation to Implementation
VA Palo Alto Health Care System
Menlo Park Division (152)
795 Willow Road, Menlo Park, CA 94025
Fax: (650) 617-2736 / Email: Ranak.Trivedi@va.gov
Stanford Contact: SHP-Fellowship
Center for Health Policy / Center for Primary Care and Outcomes Research
615 Crothers Way, MC 6019, Stanford, CA 94305
Please be prepared to upload a CV, statement of career objectives and the names of three professional references.