Research Grants
Funding For:
Improving the Effectiveness and Efficiency of High-Risk Care Management through Machine Learning
Cost & Quality / Health Equity
Recipient:
Ziad Obermeyer, Brigham and Women's Hospital
Grant Period:
Jan 01, 2016 - Dec 31, 2016
AMOUNT:
$54,432.00
Summary of the Project:
This NIHCM-funded study will apply state-of-the-art machine learning techniques to electronic health record data to develop predictive models that: (1) identify patients at high risk of becoming high users, and (2) predict which patients are likely to achieve better health outcomes and/or lower health care utilization in response to high-risk care management (HRCM). Results will contribute to more effective and efficient HRCM programs, helping to provide better care at lower cost.
Media Coverage
October 24, 2019
"Dissecting racial bias in an algorithm used to manage the health of populations"
Learn MoreAuthor: Obermeyer Z, Powers B, Vogeli C, Mullainathan S, Science
November 06, 2019
Racial bias found in widely used health care algorithm
Learn MoreAuthor: Quinn Gawronski, NBC News
October 24, 2019
Researchers Find Racial Bias in Hospital Algorithm
Learn MoreAuthor: Melanie Evans & Anna Wilde Matthews, The Wall Street Journal
October 24, 2019
Racial bias in a medical algorithm favors white patients over sicker black patients
Learn MoreAuthor: Carolyn Y. Johnson, The Washington Post
October 24, 2019
A Major Healthcare A.I. Has a Serious Racial Bias: Brainstorm Health
Learn MoreAuthor: Sy Mukherjee, Fortune
October 24, 2019
How computer algorithms help spread racial bias in U.S. healthcare, and how they can help fix it
Learn MoreAuthor: Amina Khan, Los Angeles Times
October 24, 2019
Widely used algorithm for follow-up care in hospitals is racially biased, study finds
Learn MoreAuthor: Shradda Chakradhar, STAT
October 29, 2019
Biased Algorithms Affect Healthcare for Millions
Learn MoreAuthor: Nicola M. Perry, Medscape
October 28, 2019
Healthcare Prediction Algorithm Found to be Biased Against Blacks
Learn MoreAuthor: Managed Healthcare Executive Staff
Health Highlights: Oct. 28, 2019 October 28, 2019
Health Highlights: Oct. 28, 2019
Learn MoreAuthor: U.S. News & World Report
October 28, 2019
UC Berkeley researchers find widely used health care algorithm is biased
Learn MoreAuthor: Marc Escobar, The Daily Californian
October 30, 2019
Widely used health care prediction algorithm biased against black people
Learn MoreAuthor: Kara Manke, University of California
October 28, 2019
Health care prediction algorithm biased against black patients, study finds
Learn MoreAuthor: Sam Jemielity, UChicago News
October 29, 2019
Healthcare algorithms may be racially biased
Learn MoreAuthor: John R. Fischer, HealthCareBusiness
November 05, 2019
Algorithms can spread racial bias in health care
Learn MoreAuthor: Amina Khan, The Sentinel
June 01, 2018
"Predictive Modeling of U.S. Health Care Spending in Late Life"
Learn MoreAuthor: Einav L, Finkelstein A, Mullainathan S, Obermeyer Z, Science
May 01, 2017
"A Machine Learning Approach to Predicting Short-term Mortality Risk for Patients Starting Chemotherapy"
Learn MoreAuthor: Parikh RB, Elfiky A, Pany MJ, Obermeyer Z, Journal of Clinical Oncology
December 01, 2016
"Estimating 1-Year Mortality for High-Risk Primary Care Patients Using the “Surprise” Question"
Learn MoreAuthor: Lakin JR, Robinson RG, Bernacki RE, Powers BW, et al., JAMA Internal Medicine
