DOM In the News
Read about how the Department of Medicine is responding to the outbreak of the coronavirus respiratory illness COVID-19. See related COVID-19 publications.
Medicine Grand Rounds: Amol Navathe, MD
Amol Navathe, MD, PhD, is a physician and core investigator at the Philadelphia VA Medical Center. He is also an Assistant Professor of Health Policy and Medicine and Director of the Payment Insights Team at the University of Pennsylvania. He is a Commissioner of the Medicare Payment Advisory Commission (MedPAC), a non-partisan agency that advises the US Congress on Medicare policy, and co-founder of Embedded Healthcare, a healthcare technology company that uses behavioral economic tools to improve the value of clinical decisions.
Dr. Navathe is a leading scholar on payment model design and evaluation, particularly bundled payments. 
His scholarship is unique because of its bi-directional translation between scientific discovery and real-world practice, including focus on: (1) the impact of value based care and payment models on health care value; (2) financial and non-financial incentive design, including applications of behavioral economics, to drive clinician practice change; and (3) a mix of pragmatic clinical trials and observational data analyses. His work has been published in Science, The New England Journal of Medicine, The Journal of the American Medical Association (JAMA), Health Affairs, and other leading journals, as well as The New York Times and other news outlets.
Dr. Navathe completed medical school at the University of Pennsylvania School of Medicine and internal medicine residency at the Brigham and Women’s Hospital at Harvard Medical School. He obtained his PhD in Health Care Management and Economics from The Wharton School at the University of Pennsylvania.
Please click the link below to join the webinar:
https://ucsf.zoom.us/j/95020584487?pwd=WkRpRnlPY2c2dDUyRElGUmV6eUdhdz09
Webinar ID: 950 2058 4487
Passcode: 081989
Or join by phone by dialing (for higher quality, dial a number based on your current location):
US: +1 669 900 6833 or +1 213 338 8477 or +1 669 219 2599
International numbers available: https://ucsf.zoom.us/u/abh5BG9VS
Ben Rosner Receives UCSF RAP Grant
Congrats to Ben Rosner for receiving the UCSF RAP grant for a project entitled: "Leveraging Patient Generated Health Data to Close the Hospital Readmission Information Gap."
Patient generated health data (PGHD) are central to our national health information technology roadmap,1 and their use in clinical care is expected to improve health outcomes and reduce costs. Knowledge gaps about the accuracy and completeness of PGHD, however, remain critical barriers to their adoption in clinical decision making. Addressing these gaps for patient-reported readmissions is a compelling use case, both methodologically (PGHD for readmissions have objective external sources of validity, whereas subjective PGHD do not), and from an outcomes perspective (readmissions are costly and actionable). It is estimated, for example, that 34% of Medicare patients are readmitted within 90 days of discharge, and that 31%-65% of readmissions occur at secondary facilities unbeknownst to the index institutions,6,7 resulting in $17B-$25B in annual costs.8,9 Under value-based reimbursement, index hospitals are bearing new financial risk, incurring penalties in some cases for all excess cost-drivers in the 90-days post-discharge, wherever they occur. This has driven intense interest in identifying any readmissions, and designing interventions prior to discharge to mitigate them. One academic medical center, for example, was able to identify previously unrecognized readmission “hot spots,” re-design its processes pre-discharge, and reduce its readmission rate by 25% within one year of implementing a claims-based near-real-time readmission feedback system. Such closed loop feedback is central to organizational learning and quality improvement, but healthcare has been slow to adopt such approaches post-discharge. PGHD-based sources of near-real-time readmission feedback are promising means to close this knowledge gap, but their accuracy and completeness are not known.
In this study, we will assess the extent to which: 1. Patients are active, accurate, and complete self-reporters of 90-day readmissions through post-discharge electronic surveys, and 2. Smartphone-based geofencing, a location-based technology that detects when the phone crosses a hospital boundary, offers an accurate and acceptable passive means to supplement any gaps in active patient self-reporting. The central hypothesis is that active patient self-report offers accurate feedback on readmissions for a portion of patients, but that a complete picture on readmissions may only be possible when passive sensing technology fills the remaining gap. The objective of this proposal is to assess the accuracy and completeness of two novel sources of post-discharge readmission PGHD: 1. The patient him/herself, and 2. Smartphone-based geofencing technology. The REDCap survey platform and UCSF’s Eureka Research Platform will be used to gather active (survey based) and passive (geofencing-based) data for adult patients following UCSF hospital discharge respectively. Subgroup analyses based on demographics and disease burden will be conducted to understand potential limitations of these approaches and opportunities for future implementation.