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[theory-seminar] Friday March 25th, 1pm: quantitative models in a fully integrated healthcare system

Omer Reingold reingold at stanford.edu
Tue Mar 8 18:57:43 PST 2022


Noa and Noam (bios below) will give a talk on Friday March 25th at 1pm in
the Fujitsu conference room (on the 4th floor in Gates). Details on the
talk are below and (based on their past talks) I highly recommend
attending. The speakers are experts in public health care with a very wide
and deep education and a tremendous openness to adopting advanced CS
research in real-life health care systems (through one of the largest
health-care providers in the world). They have been involved in some of the
highest profile COVID research publications (e.g., on the effectiveness of
vaccines) and I was lucky to have them apply some of our
algorithmic-fairness work. Feel free to discriminate this invitation to
anybody who may be interested.

Best wishes
Omer

*Title*: Opportunities for the application of quantitative models in a
fully integrated healthcare system

*Abstract*

Health insurance in Israel is mandatory, comprehensive in its list of
services, and provided by four
integrated payer-provider organizations. Clalit Health Services is the
largest of these organizations –
responsible for the care of over half of the Israeli population. Most of
this care (outpatient and
inpatient) is directly provided by Clalit, and the rest is purchased by
Clalit. All services provided or
purchased are stored in a single comprehensive analytic data warehouse. Our
talk will focus on the
opportunities that such an integrated system and its data offers in using
quantitative models for
state-of-the-art research and digital healthcare interventions.
We will discuss the two main quantitative tools used for digital healthcare
– causal inference and
prediction models. We will show how the depth and immediacy of the data
allowed the conduct of
causal research that provided necessary and timely information regarding
the effectiveness and
safety of mRNA Covid-19 vaccines. We will also show how such unique data
enabled us to study an
often-overlooked aspect of the vaccination – indirect protective effects.
We will also demonstrate
how this data can be used for promoting predictive, proactive, and
personalized care. We will
demonstrate how prediction models are created and how they are integrated
into the point of care.

Noam Barda holds an MD from Tel-Aviv University, a PhD co-advised in public
health and computer
science from Ben-Gurion University and a BSc in computer science from the
Open University. He
completed his post-doctorate in the Department of Biomedical Informatics
(DBMI) at Harvard
Medical School. He is the head of the Real-World Evidence Research and
Innovation Lab at Tel-
HaShomer medical center, Israel’s largest hospital, and co-heads the
Digital Healthcare Laboratory in
the department of Software and Information Systems Engineering at
Ben-Gurion University.
Noa Dagan holds an MD and an MPH from the Hebrew University, and a PhD in
Computer Science
from Ben-Gurion University. She completed her post-doctorate in the
Department of Biomedical
Informatics (DBMI) at Harvard Medical School. Dr. Dagan is currently the
director of the AI-driven
Medicine Department in Clalit Innovation and the Clalit Research Institute,
and co-heads the Digital
Healthcare Laboratory in the department of Software and Information Systems
Engineering at Ben-
Gurion University.
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