A Look at Risk Adjustment in Value-Based Care

More and more, healthcare organizations are considering value-based care plans to help improve health outcomes for patients and lower costs for payers and providers. The process involves risk-adjustment, which depends on sources of real-world data (RWD) such as electronic health records (EHR). Unfortunately, the system can be gamed due to the unstructured nature of EHR. However, artificial intelligence (AI) may help glean accurate information from EHR.

According to Ketan Patel, MD, “Many health plans have turned to AI-based technologies like natural language processing to scour patient records for critical details required to substantiate conditions. Natural language processing automates expensive, manual chart reviews, which sometimes require clinicians to wade through thousands of pages of documentation to pick out a tiny piece of data they seek. Notably, natural language processing is adept at analyzing unstructured text, which often contains important information into a patients’ current diagnoses which is often buried in the notes sections of EHRs. This data can then be standardized and mapped to HCC codes for accurate, data-supported risk capture.”

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(Source: Managed Healthcare Executive, September 7^th, 2022)