Theoretically Speaking — Opportunities for the Application of Quantitative Models in a Fully Integrated Healthcare System

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. This talk will focus on the opportunities that such an integrated system and its data offer in using quantitative models for state-of-the-art research and digital health care interventions.

Noam Barda and Noa Dagan will discuss the two main quantitative tools used for digital health care — causal inference and prediction models. They will show how the depth and immediacy of the data allowed for causal research that provided necessary and timely information regarding the effectiveness and safety of mRNA COVID-19 vaccines. They will also show how such unique data enabled them to study an often-overlooked aspect of vaccination — indirect protective effects. They will also demonstrate how this data can be used for promoting predictive, proactive, and personalized care. They 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 in public health and computer science from Ben-Gurion University, and a BSc in computer science from the Open University. He completed his postdoctorate 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 postdoctorate in the Department of Biomedical Informatics (DBMI) at Harvard Medical School. She is the director of the AI-Driven Medicine Department at 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.

If you require accommodation for communication, please contact our Access Coordinator at simonsevents@berkeley.edu with as much advance notice as possible.

This event will be held in person and virtually. Zoom link to Join [here].

Please read on for important information regarding logistics for those planning to register to attend the workshop in-person at Calvin Lab.

Proof of Vaccination
Given current public health directives from state, local, and university authorities, all participants in Simons Institute events must be prepared to demonstrate proof of full vaccination: a vaccination card or photo of the card along with a valid photo ID, or a green or blue Campus Access Badge via the UC Berkeley Mobile app (additional details regarding proof of vaccination can be found here).

Masks
Masks are required indoors for all participants who are not fully vaccinated, and strongly encouraged for those who are fully vaccinated. 

Refreshments
Light refreshments will be provided before the lecture. Please note due to current health conditions, we will set up just outside the building. There will be signs to direct you. Please note there is no food or drink allowed in the auditorium. Thank you for helping us to keep the auditorium clean.

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