Mar
26
Thu
Center for Population Health Sciences Seminar Series: John W. Rowe, Columbia University @ Li Ka Shing Learning and Knowledge Center, Room 320
Mar 26 @ 2:00 pm – 3:00 pm
Center for Population Health Sciences Seminar Series: John W. Rowe, Columbia University @ Li Ka Shing Learning and Knowledge Center, Room 320

Aging in America: National and State Trends in Well-Being of Older Persons

This presentation will include findings from two recent studies. The first is an analysis of trends in mental and physical well-being in a national sample of older individuals between 2003-2017. Results show stable to slightly increasing physical health and a decline in mental health, especially amongst the young old (aged 65-69) and those with low education and wealth. The second study traces trends in the status of older persons, as reflected in the Aging Society Index, in individual States between 2003-2017. Findings indicate substantial variability between States in the baseline status of older persons and the trends over time.  The impact of potential drivers of these trends are evaluated.

Register here

Apr
17
Fri
Stanford Medicine COVID-19 Modeling Town Hall – Understanding Modeling Limitations and Current Data at Institutional, County and State Levels @ Online only
Apr 17 @ 1:00 pm – 2:00 pm
Stanford Medicine COVID-19 Modeling Town Hall - Understanding Modeling Limitations and Current Data at Institutional, County and State Levels @ Online only

Stanford Medicine COVID-19 Modeling Town Hall – Understanding Modeling Limitations and Current Data at Institutional, County and State Levels

This Friday at 1pm – (4/17/2020)

https://stanford.zoom.us/j/96128817827

Or Telephone:

Dial 1 650 724 9799

Webinar ID: 961 2881 7827

There is a lot of excitement for using data science and modeling to forecast how COVID-19 will spread and affect their communities. Multiple data scientists, epidemiologists and computer scientists are building models that range from simple trendline plots, to growth projections to complex epidemic simulations. The geographic resolution of such models varies greatly, ranging from a single institution, to a city, to a county, to a state and the country.  In order to use the output of such a broad variety of models for decision making, it is necessary to understand the model’s inputs, the underlying assumptions, the form of the model, and the degree of uncertainty in its output.

Members of the Department of Medicine have partnered with the operational planning team at SHC, with faculty in the School of Engineering and with public health officials of our local county as well as the State of CA to create a suite of models for different decision needs. For example, projecting beds needed based on counts of hospitalized patients can serve as the foundation for regional planning.

In this town hall session we will discuss the full range of the modeling efforts at Stanford Medicine, describe how their results are being used, and what needs to be done to improve the accuracy of the inputs to the models.

The town hall will feature presentations by:

  • Nigam Shah, MBBS, PhD – Associate Professor of Medicine, Associate CIO for Data Science, Stanford Health Care.
  • Kevin Schulman, MD – Professor of Medicine, Associate Chair of Business Development and Strategy in the Department of Medicine
  • Joshua Salomon, MD – Professor of Medicine and a core faculty member in the Center for Health Policy and the Center for Primary Care and Outcomes Research
  • Kristan Staudenmayer, MD, MS, FACS – Associate Professor, Department of Surgery
  • David Scheinker, PhD – Founder and Director, SURF Stanford Medicine & Director of Systems Design and Collaborative Research, LPCH

Followed by Q&A with above and following:

  • Robert Harrington, MD – Arthur L. Bloomfield Professor and Chair, Department of Medicine
  • Neera Ahuja, MD – Division Chief, Hospital Medicine & Medical Director, General Medicine Inpatient Wards

It will be moderated by Errol Ozdalga, MD – Director of Communications, Department of Medicine.


https://stanford.zoom.us/j/96128817827

Or Telephone:

Dial 1 650 724 9799

Webinar ID: 961 2881 7827