Models of Care for High-Need Patients: Workshop 2

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A meeting, sponsored by the Peterson Center on Healthcare and convened by the National Academy of Medicine, will engaged stakeholders in a discussion of the issues, challenges, and approaches that present the greatest opportunity creating models of care for high-need patients.

The second in a series of three meetings, this workshop aimed at advancing approaches to classifying patient populations and considering policies to enhance the spread of successful models of care. (Information about the first workshop in the series is available here.) The discussion was intended to explore how we can better serve high-need patients, and improve their health outcomes and reduce costs.

Objectives of the January 19 meeting:

  1. Review the existing data sources on care delivery to high-need patients, and consider how the population may be classified to better characterize high-need patients.
  2. Explore successes learned from designing various models of care.
  3. Consider policies particularly important to spreading the most successful models.

Following the meeting, we will hold a public comment period for 14 days. A live webcast will be available, and archived video from the webcast will be posted on this page after the meeting.


Feedback on Models of Care Workshop 2 >>


In order of the Agenda:

Patient and Family Perspective, Darcel Jackson
Framing the Strategy: Value of Segmentation and Stratification in Primary Care, David Dorr 
21st Century Care: Redesigning Care at Denver Health, Simon Hambidge
Identifying High Need High Cost Individuals, Gerard Anderson
Targeting High Cost Patients and their Needs, Ashish Jha
Linked EHR/Claims Data in the High Cost/High Needs Population, Paul Bleicher
Overview of Segmentation of High-Need, High-Cost Patient Population, Melinda Abrams
Identifying the Design Elements of Successful Models, Molly Coye
What Really Works for High-Risk, High-Cost Patients? Randall Brown
Replicating Successful Models through Spread and Scale, Katherine Hayes


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