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Healthcare

See the latest research, articles and faculty on the Healthcare Area of Expertise at Columbia Business School.

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Latest on Healthcare

Healthcare
Date
January 20, 2026
CBS Photo Image
Healthcare

Spotlight: 3 Minutes with Laurence Coman ’20, Co-Founder AVO

At its core, AVO leverages AI to process patient data directly from the Electronic Health Record (EHR), maps that data against clinical best practices, and produces "copilots" that automate clinician workflows. 
  • Read more about Spotlight: 3 Minutes with Laurence Coman ’20, Co-Founder AVO about Spotlight: 3 Minutes with Laurence Coman ’20, Co-Founder AVO
Artificial Intelligence, Data and Business Analytics, Decisions, Healthcare, Practitioner Perspectives
Type
Columbia Business
Date
July 24, 2025
Artificial Intelligence, Data and Business Analytics, Decisions, Healthcare, Practitioner Perspectives

Artificial Intelligence in Healthcare: Insights from Columbia Business School Professor Carrie Chan

Step into the future of medicine, where artificial intelligence and data science are revolutionizing patient care. At Columbia Business School, Professor Carrie Chan is leading the charge, developing cutting-edge solutions that promise to enhance healthcare accessibility, improve quality, and significantly reduce costs. Explore how her groundbreaking work is transforming emergency room operations and setting new standards for efficiency in hospitals worldwide.
  • Read more about Artificial Intelligence in Healthcare: Insights from Columbia Business School Professor Carrie Chan about Artificial Intelligence in Healthcare: Insights from Columbia Business School Professor Carrie Chan
Artificial Intelligence, Decisions, Healthcare
Date
April 10, 2025
From left to right: Drago Plecko, Columbia Engineering; Carri Chan, Columbia Business School; Noémie Elhadad, VP&S; Moderator: Lena Mamykina, VP&S. Photo by Eileen M. Barroso. Photo from Columbia University Data Science Institute
Artificial Intelligence, Decisions, Healthcare

When the System Is the Patient: AI in Health Care

Columbia University's Data Science Institute explores AI's role in healthcare, focusing on supporting clinical judgment while prioritizing equity and human experience. The article highlights how AI can enhance data collection for chronic conditions, optimize fair staffing in emergency departments, and identify structural inequities in care access, emphasizing that AI models must align with real-world healthcare contexts.
  • Read more about When the System Is the Patient: AI in Health Care about When the System Is the Patient: AI in Health Care
Artificial Intelligence, Distinguished Speaker Series, Economics and Policy, Healthcare, Leadership
Date
March 06, 2025
Dan O'Day
Artificial Intelligence, Distinguished Speaker Series, Economics and Policy, Healthcare, Leadership

Leadership Lessons from Gilead Sciences CEO Daniel O’Day

Innovations in data and AI are reshaping the biopharma industry.
  • Read more about Leadership Lessons from Gilead Sciences CEO Daniel O’Day about Leadership Lessons from Gilead Sciences CEO Daniel O’Day
Economics and Policy, Elections, Healthcare, Social Impact
Date
October 25, 2024
An image of a hospital with a bed in the foreground
Economics and Policy, Elections, Healthcare, Social Impact

Health Care: The Winning Closing Argument in a Tight Election

With just days to go in the current presidential campaign, a greater focus on improving the nation’s health could be the deciding factor in a close election, argues Professor Michael Sparer.
  • Read more about Health Care: The Winning Closing Argument in a Tight Election about Health Care: The Winning Closing Argument in a Tight Election
Data and Business Analytics, Data/Big Data, Distinguished Speaker Series, Healthcare
Date
October 18, 2024
Emma Walmsley, CEO of British pharmaceutical giant GSK
Data and Business Analytics, Data/Big Data, Distinguished Speaker Series, Healthcare

Harnessing the Power of AI, Data — and People: Three Insights From GSK CEO Emma Walmsley

The pharmaceutical company leader praised AI for boosting productivity, but noted that it’s still “all about the people.”
  • Read more about Harnessing the Power of AI, Data — and People: Three Insights From GSK CEO Emma Walmsley about Harnessing the Power of AI, Data — and People: Three Insights From GSK CEO Emma Walmsley
Artificial Intelligence, Business and Society, Distinguished Speaker Series, Healthcare, Strategy
Date
October 17, 2024
Senator Bill Cassidy.
Artificial Intelligence, Business and Society, Distinguished Speaker Series, Healthcare, Strategy

Navigating AI’s Role in the Future of Healthcare

US Senator Bill Cassidy, MD, highlights the need to balance regulation and innovation when it comes to embracing AI in medicine.
  • Read more about Navigating AI’s Role in the Future of Healthcare about Navigating AI’s Role in the Future of Healthcare
Business Economics and Public Policy, Healthcare
Date
September 17, 2024
Stethoscope, fake money and calculator with notepad written Rising Healthcare Cost. Healthcare cost become more expensive after covid-19.
Business Economics and Public Policy, Healthcare
Press Release

New Study: Public Options Can Drastically Lower Healthcare Costs Due to Government Bargaining Power

Columbia Business School research is the first to find empirical evidence for how government intervention would shape the private healthcare market
  • Read more about New Study: Public Options Can Drastically Lower Healthcare Costs Due to Government Bargaining Power about New Study: Public Options Can Drastically Lower Healthcare Costs Due to Government Bargaining Power

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Faculty

CBS Faculty Research on Healthcare

Identifying Factors Predicting Kidney Graft Survival in Chile Using Elastic-Net-Regularized Cox Regression

Authors
Marcelo Olivares, L. Magga, S Maturana, M. Valdevenito, J. Cabezas, J. Chapochnick, F. González, A. Kompatzki, H. Muller, J. Pefaur, C. Ulloa, and R. Valjalo
Date
September 6, 2022
Format
Journal Article
Journal
Medicina

We developed a predictive statistical model to identify donor–recipient characteristics related to kidney graft survival in the Chilean population. Given the large number of potential predictors relative to the sample size, we implemented an automated variable selection mechanism that could be revised in future studies as more national data is collected. Materials and Methods: A retrospective multicenter study was conducted to analyze data from 822 adult kidney transplant recipients from adult donors between 1998 and 2018.

Read More about Identifying Factors Predicting Kidney Graft Survival in Chile Using Elastic-Net-Regularized Cox Regression

Utilizing Partial Flexibility to Improve Emergency Department Flow: Theory and Implementation

Authors
Carri Chan, Vahid Sarhangian, Prem Talwai, and Kriti Gogia
Date
August 5, 2022
Format
Journal Article
Journal
Naval Research Logistics

Emergency Departments (EDs) typically have multiple areas where patients of different acuity levels receive treatments. In practice, different areas often operate with fixed nurse staffing levels. When there are substantial imbalances in congestion among different areas, it could be beneficial to deviate from the original assignment and reassign nurses. However, reassignments typically are only feasible at the beginning of 8-12-hour shifts, providing partial flexibility in adjusting staffing levels.

Read More about Utilizing Partial Flexibility to Improve Emergency Department Flow: Theory and Implementation

Quantifying utilitarian outcomes to inform triage ethics: Simulated performance of a ventilator triage protocol under Sars-CoV-2 pandemic surge conditions

Authors
Elizabeth Chuang, Julien Grand-Clement, Jen-Ting Chen, Carri Chan, Vineet Goyal, and Michelle Ng Gong
Date
April 18, 2022
Format
Journal Article
Journal
AJOB Empirical Bioethics

Background

Equitable protocols to triage life-saving resources must be specified prior to shortages in order to promote transparency, trust and consistency. How well proposed utilitarian protocols perform to maximize lives saved is unknown. We aimed to estimate the survival rates that would be associated with implementation of the New York State 2015 guidelines for ventilator triage, and to compare them to a first-come-first-served triage method.

Methods

Read More about Quantifying utilitarian outcomes to inform triage ethics: Simulated performance of a ventilator triage protocol under Sars-CoV-2 pandemic surge conditions

Service design to balance waiting time and infection risk: An application for elections during the COVID-19 pandemic

Authors
Marcelo Olivares, S. Mondschein, F. Ordonez, D. Schwartz, A. Weintraub, I. Torres-Ulloa, C Aguayo, and G. Canessa
Date
March 18, 2022
Format
Journal Article
Journal
Service Science

The COVID-19 pandemic has caused great disruption to the service sector, and it has, in turn, adapted by implementing measures that reduce physical contact among employees and users; examples include home-office work and the setting of occupancy restrictions at indoor locations.

Read More about Service design to balance waiting time and infection risk: An application for elections during the COVID-19 pandemic

The social divide of social distancing: Shelter-in-place behavior in Santiago during the COVID-19 pandemic

Authors
Marcelo Olivares, A. Carranza, M. Goic, E. Lara, G.Y. Weintraub, J. Covarrubia, C. Escobedo, N. Jara, and L.J. Basso
Date
January 1, 2022
Format
Journal Article
Journal
Management Science
Read More about The social divide of social distancing: Shelter-in-place behavior in Santiago during the COVID-19 pandemic

Optimal Scheduling of Proactive Service with Customer Deterioration and Improvement

Authors
Yue Hu, Carri Chan, and Jing Dong
Date
December 21, 2021
Format
Journal Article
Journal
Management Science

Service systems are typically limited resource environments where scarce capacity is reserved for the most urgent customers. However, there has been a growing interest in the use of proactive service when a less urgent customer may become urgent while waiting. On one hand, providing service for customers when they are less urgent could mean that fewer resources are needed to fulfill their service requirement. On the other hand, using limited capacity for customers who may never need the service in the future takes the capacity away from other more urgent customers who need it now.

Read More about Optimal Scheduling of Proactive Service with Customer Deterioration and Improvement

Differences in Consumer-Benefiting Misconduct by Nonprofit, For-profit, and Public Organizations

Authors
Vanessa Burbano and J. Ostler
Date
October 1, 2021
Format
Journal Article
Journal
Organizational Behavior and Human Decision Processes

We examine how organizations of different types --public, non-profit and for-profit -- engage in consumer-benefiting misconduct (CBM) by examining which patients benefit from hospitals of the three types gaming the market for liver transplants. Consistent with our theory, we find that public firms are the least likely of the three organization types to engage in CBM.

Read More about Differences in Consumer-Benefiting Misconduct by Nonprofit, For-profit, and Public Organizations

Information Avoidance and Information Seeking Among Parents of Children with ASD

Authors
Kiely Law, Paul Lipkin, George Loewenstein, Alison Marvin, and Nachum Sicherman
Date
May 1, 2021
Format
Journal Article
Journal
American Journal on Intellectual and Developmental Disabilities

We estimated the effects of information avoidance and information seeking among parents of children diagnosed with ASD on age of diagnosis. An online survey was completed by 1,815 parents of children with ASD. Children of parents who self-reported that they had preferred "not to know," reported diagnoses around 3 months later than other children.

Read More about Information Avoidance and Information Seeking Among Parents of Children with ASD

Dynamic Server Assignment in Multiclass Queues with Shifts, with Applications to Nurse Staffing in Emergency Departments

Authors
Carri Chan, Michael Huang, and Vahid Sarhangian
Date
January 27, 2021
Format
Journal Article
Journal
Operations Research

Many service systems are staffed by workers who work in shifts. In this work, we study the dynamic assignment of servers to different areas of a service system at the beginning of discrete time-intervals, i.e., shifts. The ability to reassign servers at discrete intervals, rather than continuously, introduces a partial flexibility that provides an opportunity for reducing the expected waiting time of customers.

Read More about Dynamic Server Assignment in Multiclass Queues with Shifts, with Applications to Nurse Staffing in Emergency Departments

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