Encouraging Flu Vaccination Among High-Risk Patients Identified by a Machine-Learning Model of Flu Complication Risk

DATE: July 22, 2020 to May 31, 2021
Trials: ClinicalTrials.gov NCT04323137

The purpose of the current study is to test different interventions to determine the most effective way to promote flu vaccine uptake in a high-risk population identified by an "artificial intelligence" (AI) or machine learning (ML) algorithm. The specific aims are:

Evaluate the effect on flu vaccination rates of informing health-system patients who are identified by an ML analysis of EHR data to be at high risk for flu complications that they are at high risk with either (a) no additional explanation, (b) an explanation that this determination comes from an analysis of their medical records, and (c) the additional explanation that an AI or ML algorithm made this determination.

Evaluate the effects of the same three interventions on diagnoses of flu in the same patients.

Investigators

Christopher F. Chabris
Christopher F. Chabris, Project Co-Leader

Christopher F. Chabris is a psychologist who codirects both the Behavioral and Decision Sciences Program and the Behavioral Insights Team at Geisinger, an integrated healthcare system in Pennsylvania. His research focuses on attention, intelligence, decision-making, and behavior genetics.

Michelle Meyer
Michelle N. Meyer, Project Co-Leader

Michelle N. Meyer is the Chief Bioethics Officer at Geisinger, and Associate Professor and Chair of the Department of Bioethics and Decision Sciences. In addition to conducting normative ethics scholarship and empirical legal research, she uses survey experiments and qualitative methods to investigate judgments and decision-making related to science, innovation, and health.

Headshot of Amir Goren
Amir Goren, Co-Investigator

Amir Goren is the Program Director of the Behavioral Insights Team at Geisinger College of Health Sciences. His research interests include social psychology, judgment and decision making, behavioral economics, and health outcomes.

Maheen Shermohammed, Co-Investigator
Joseph Doyle Profile
Joseph J. Doyle, Other Significant Contributor

Joseph J. Doyle is the Erwin H. Schell Professor of Management and Applied Economics at the MIT Sloan School of Management. His research ranges widely in the field of health economics, addressing both the delivery of health care services and the operation of health insurance markets.

Donna Wolk, Other Significant Contributor

Supported by the National Institute on Aging grant #P30AG034532

Related

Topics

Health

Programs

Economics of Aging

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