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Points of Light 2023 Case Study 17 Points of Light 2023 Case Study 17
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Points of Light 2023 Case Study 17
Improving Medication Adherence among High-Risk Populations

author - Boyd Stewart
Boyd Stewart
author - Aurene Wilford
Aurene Wilford
April 14, 2023 | Read Time: 1  minute

Vulnerable and underserved populations face a variety of barriers that can make it difficult for them to adhere to their prescribed medication regimens, and the impacts of non-adherence—in terms of health outcomes and costs—can be severe. Low medication adherence was a particular problem for the healthcare organization in this case study, whose patient population covers one of the most vulnerable and underserved zip codes in the country. To encourage better adherence among high-risk individuals, this organization collaborated with a payer organization and value-based care partner to identify patients in need of additional support and help resolve their barriers to adherence. Results include better health outcomes and higher CMS Star ratings.

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Key Findings:

  1. Executive Summary
  2. The Collaborators
  3. Points of Friction—Challenges to Be Solved
  4. Action Plan—How the Collaborators Worked Together to Reduce Friction
  5. Points of Light—Outcomes Achieved through Collaboration
  6. Lessons Learned—What Best Practices Can Other Organizations Replicate?
  7. What's Next?—Vision for the Future
author - Elizabeth Pew
Elizabeth Pew
author - Jess Wallace-Simpson
Jess Wallace-Simpson
author - Joel Sanchez
Project Manager
Joel Sanchez
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This material is copyrighted. Any organization gaining unauthorized access to this report will be liable to compensate KLAS for the full retail price. Please see the KLAS DATA USE POLICY for information regarding use of this report. © 2024 KLAS Research, LLC. All Rights Reserved. NOTE: Performance scores may change significantly when including newly interviewed provider organizations, especially when added to a smaller sample size like in emerging markets with a small number of live clients. The findings presented are not meant to be conclusive data for an entire client base.