Optimizing Hierarchical Condition Category-Risk Adjustment Factor Management in Population Health Using Rapid Process...

Area of Science:

• Healthcare Management
• Quality Improvement
• Health Informatics

Background:

• Centers for Medicare & Medicaid Services (CMS) reimbursement is tied to Hierarchical Condition Category (HCC) coding.
• Risk adjustment optimization in medical systems often involves expensive chart review processes.
• Previous workflow implementations for HCC management were complex and siloed.

Purpose of the Study:

• To implement HCC-Risk Adjustment Factor (RAF) improvement tools for optimized HCC-RAF management in Population Health.
• To utilize rapid process improvement methods to streamline HCC coding and documentation.
• To reduce costs associated with traditional chart review processes.

Main Methods:

• Employed Lean methodology and Rapid Process Improvement Workshops (RPIW) to develop and implement tools.
• Created a suite of tools including provider education, tip sheets, clinical champions, audits, practice alerts, and decision-support tools.
• Embedded new tools into standard work for provider teams.

Main Results:

• Achieved a 4.1% improvement in enterprise HCC-RAF scores in Year 1.
• Developed optimized workflows and tools for providers and team members.
• Demonstrated provider willingness to adopt new tools, indicating successful culture change.

Conclusions:

• Lean improvement methods facilitated the collective design and adoption of HCC management tools.
• Streamlined processes and newly developed tools optimized operations and reduced waste.
• Providers embraced the tools, enabling them to work more efficiently and effectively.