Create a solution
to predict health outcomes.
Win $1,000,000.

The CMS Artificial Intelligence (AI) Health Outcomes Challenge is an opportunity for innovators to demonstrate how AI tools – such as deep learning and neural networks – can be used to predict unplanned hospital and skilled nursing facility admissions and adverse events.

Partnering with the American Academy of Family Physicians and Arnold Ventures, the CMS AI Health Outcomes Challenge will engage with innovators from all sectors – not just from healthcare – to harness AI solutions to predict health outcomes for potential use in CMS Innovation Center innovative payment and service delivery models.

ADDITIONAL INFORMATION

FACT SHEET

For additional information on the challenge, please reference the Fact Sheet.

PRESS RELEASE 10/30/19

For additional information on the challenge, please reference the 10/30/19 Press Release.

PUBLIC NOTICE

For additional information on the challenge, please reference the Public Notice.

Informational webinar

Missed the webinar? Download the presentation here.

View the recorded webinar here.

CONTACT

Email cmsaichallenge@sensisagency.com for more information

CHALLENGE OBJECTIVES

  1. Use AI/deep learning methodologies to predict unplanned hospital and SNF admissions and adverse events within 30 days for Medicare beneficiaries, based on a data set of Medicare administrative claims data, including Medicare Part A (hospital) and Medicare Part B (professional services).

  2. Develop innovative strategies and methodologies to: explain the AI-derived predictions to front-line clinicians and patients to aid in providing appropriate clinical resources to model participants; and increase use of AI-enhanced data feedback for quality improvement activities among model participants.

Timeline

Wednesday, March 27, 2019
LAUNCH STAGE

Opened on March 27, 2019, to the general public. Entrants each completed an online application and submitted a brief slide deck providing information about the submitting entity and their proposed solution.

Wednesday, March 27, 2019
June 19, 2019, 4:00pm EDT
LAUNCH STAGE APPLICATION PERIOD CLOSED
June 19, 2019, 4:00PM EDT 

The Launch Stage application period closed June 19, 2019.

June 19, 2019, 4:00pm EDT
October 30, 2019
STAGE 1 
October 30, 2019

CMS announced 25 Participants to advance to Stage 1 on October 30, 2019. The 25 Participants, titles of proposed solutions and geographic locations are listed below:

Participant: Accenture Federal Services
Proposed Solution: Accenture Federal Services AI Challenge
Geographic Location: Arlington, Virginia

Participant: Ann Arbor Algorithms Inc.
Proposed Solution: Generalizing Time-to-event Algorithms to Deep Learning-based Prediction for CMS Data
Geographic Location: Sterling Heights, Michigan

Participant: Booz Allen Hamilton
Proposed Solution: Booz Allen Launch Stage Submission
Geographic Location: McLean, Virginia

Participant: ClosedLoop.ai
Proposed Solution: Healthcare’s Data Science Platform
Geographic Location: Austin, Texas

Participant: Columbia University Department of Biomedical Informatics
Proposed Solution: The CLinically Explainable Actionable Risk (CLEAR) Model from Columbia University Department of Biomedical Informatics
Geographic Location: New York, New York

Participant: CORMAC
Proposed Solution: CORMAC Response to Challenge Questions
Geographic Location: Columbia, Maryland

Participant: Deloitte Consulting LLP
Proposed Solution: Further, Faster: The Deloitte Team’s Approach to Harnessing the Power of AI to Improve Health Outcomes
Geographic Location: Arlington, Virginia

Participant: Geisinger
Proposed Solution: Reducing Adverse Events and Avoidable Hospital Readmissions by Empowering Clinicians and Patients
Geographic Location: Danville, Pennsylvania

Participant: Health Data Analytics Institute
Proposed Solution: HDAI’s Analytic Platform Technology for Healthcare Improvement
Geographic Location: Dedham, Massachusetts

Participant: HealthEC, LLC
Proposed Solution: Leveraging Artificial Intelligence to Predict and Improve Health Outcomes, Maximize Quality Improvement, and Reduce Costs
Geographic Location: Edison, New Jersey

Participant: Hospital of the University of Pennsylvania
Proposed Solution: The Intelligent Risk Project
Geographic Location: Philadelphia, Pennsylvania

Participant: IBM Corporation
Proposed Solution: AI for Explainable Adverse Event Prediction: Empowering Beneficiaries and Providers to Improve Health Outcomes
Geographic Location: Yorktown, New York

Participant: Innovative Decisions Inc. (IDI)
Proposed Solution: Multi-Modeling with Augmented Datasets for Positive Health Outcomes (MADPHO)
Geographic Location: Vienna, Virginia

Participant: Jefferson Health
Proposed Solution: Using AI to Improve Medicare Population Health, Optimize Ambulatory Scheduling, and Reduce Adverse Events at Hospitals
Geographic Location: Philadelphia, Pennsylvania

Participant: KenSci Inc.
Proposed Solution: Assistive Intelligence for Unplanned Admissions and Adverse Events Prediction
Geographic Location: Seattle, Washington

Participant: Lightbeam Health Solutions, LLC
Proposed Solution: AI Risk Predictions- preventing hospital, ER and SNF admissions
Geographic Location: Irving, Texas

Participant: Mathematica Policy Research, Inc.
Proposed Solution: The CPC+ AI Model by Mathematica
Geographic Location: Princeton, New Jersey

Participant: Mayo Clinic
Proposed Solution: Claims-based Learning Framework (CBLF)
Geographic Location: Rochester, Minnesota

Participant: Mederrata
Proposed Solution: Boosting medical error and readmission prediction by leveraging Deep Learning, Topological Data Analysis, and Bayesian modeling
Geographic Location: Columbus, Ohio

Participant: Merck & Co., Inc.
Proposed Solution: Actionable AI to Prevent Unplanned Admissions and Adverse Events
Geographic Location: Kenilworth, New Jersey

Participant: North Carolina State University (NCSU)
Proposed Solution: Multi-Layered Feature Selection and Dynamic Personalized Scoring
Geographic Location: Raleigh, North Carolina

Participant: Northrop Grumman Systems Corporation (NGSC)
Proposed Solution: Reducing Patient Risk through Actionable Artificial Intelligence: AI Risk Avoidance System (ARAS)
Geographic Location: Herndon, Virginia

Participant: Northwestern Medicine
Proposed Solution: A human-machine solution to enhance delivery of relationship-oriented care
Geographic Location: Chicago, Illinois

Participant: Observational Health Data Sciences and Informatics (OHDSI)
Proposed Solution: OHDSI Submission
Geographic Location: New York, New York

Participant: University of Virginia Health System
Proposed Solution: Actionable AI
Geographic Location: Charlottesville, Virginia

More information about Stage 1 submission requirements and evaluation criteria will be provided at a later date. Up to 7 finalists from Stage 1 will be announced April 2020.

October 30, 2019
STAGE 2 

CMS will announce more information about Stage 2 at a later date.

*Dates Subject to Change*

PRIZES

$1,650,000

Total Prize Purse

LAUNCH STAGE

25 participants
continue to Stage 1

STAGE 1

Seven finalists progress to Stage 2
and receive awards of $60,000

STAGE 2

One winner will receive $1,000,000
and the runner-up will receive $230,000

*Prize Amounts Subject to Change*

HOW TO ENTER

Enter the CMS AI Health Outcomes Challenge in Four Easy Steps:

1

GET SMART
on the problem, the submission requirements, and the judging criteria

2

REGISTER
for the challenge on the register page

3

WATCH
the informational webinar held on April 18, 2019.

4

SUBMIT
your application by
June 19, 2019 at 4:00PM EDT.

JUDGING CRITERIA

Learn about the criteria used to evaluate applications. 

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IMPACT

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INNOVATION

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HUMAN-AI COLLABORATION

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