Optimizing Hierarchical Condition Category-Risk Adjustment Factor Management in Population Health Using Rapid Process Improvement Methods
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View abstract on PubMed
Summary
This summary is machine-generated.Centers for Medicare & Medicaid Services (CMS) reimbursement relies on Hierarchical Condition Category (HCC) coding. This study used Lean methodology to develop tools, improving HCC-Risk Adjustment Factor (RAF) management and achieving a 4.1% score increase.
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.
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