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How smart is your retrospective risk adjustment solution?

Artificial intelligence (AI) enables a smarter, highly efficient chart review process while maintaining coding accuracy and completeness. 

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Each year, millions of medical charts are retrieved and reviewed manually to generate a more complete picture of member health status. Traditional retrospective risk adjustment processes lack the technology and tools to precisely predict and prioritize charts likely to support unreported diagnosis codes. The result has been a less efficient process which could disrupt providers by overloading them with unnecessary medical chart requests.

By chart volume, Optum is the leader of Medicare Advantage risk adjustment chart review. Our comprehensive retro risk adjustment enabled by artificial intelligence optimizes the chart retrieval and review process, informed by our experience with the largest database of Medicare Advantage medical records in the industry.

Optum AI modernizes the traditional chart review process by shifting the focus from volume to precision. Predictive AI prioritizes charts most likely to support specific unreported diagnosis codes. This saves providers time and reduces the total number of charts requested. Fewer chart requests mean more efficiency and better collaboration between health plans and providers.

Directly connecting to EHR systems helps enable AI to determine which charts to retrieve and when. AI helps identify the retrieval modality deemed most likely to be successful with providers. AI recommends which EHR files to extract and format for risk adjustment chart review. Directly extracting charts from the EHR enables faster turnaround time and increased retrieval rates.

Optum AI uses a 3-step process to determine the type of coding review most likely to lead to accurate and complete records. Step 1. Smart chart routing analyzes potential unreported conditions then routes charts to reviewers based on coder expertise. Step 2.  AI-enabled coding assists reviewers with specific diagnosis code suspects. Step 3. An AI completeness review determines if a member’s health history may still indicate possible unreported diagnosis codes. AI can help route charts for additional review or advance for QA. Because of AI, the chart review process has greater precision and accuracy and the results are more complete.

Our comprehensive solution is smart, efficient and helps maintain coding accuracy and completeness. It can also eliminate the need and expense of multiple vendors. Find out how to put our AI-enhanced retrospective risk adjustment solution to work for you!

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Transforming the risk adjustment process

Millions of medical charts are retrieved and reviewed manually each year to generate a more complete picture of member health status. Traditional retro risk processes lacked the technology and tools to precisely identify charts that support unreported diagnosis codes.

The result has been a less efficient process that can disrupt providers by requesting more medical charts than necessary. 

Optum uses artificial intelligence (AI) enabled by our experience with the largest database of Medicare Advantage medical records in the industry, as well as Affordable Care Act (ACA) and Medicaid medical records, to optimize the retrospective risk adjustment process.

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An AI-enabled comprehensive solution

Our comprehensive solution enables a smarter, highly efficient chart retrieval and review process. Optum AI-enabled analytics can transform your chart review operations due to its accuracy when trained with large amounts of data. 

AI modernizes the traditional chart review process by shifting the focus from volume to precision targeting of charts. The result is fewer chart retrieval requests, which lowers provider abrasion and increases the efficiency of each review. AI also helps the chart review process to be more precise when capturing suspected but unreported diagnosis codes.

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  • AI-enabled Retrospective Risk Adjustment
    How Optum AI streamlines the retrospective risk adjustment process

    In the Smart Chart Targeting step, AI-enabled analytics predict and prioritize charts most likely to support specific unreported diagnosis codes.

    During the Integrated Retrieval step, AI helps identify the retrieval modality (Direct EHR retrieval or Analog retrieval) deemed most likely to be successful with providers.

    For the coding step, AI-enabled analytics use a three-step process to facilitate efficient chart routing. AI helps the process to be more precise when capturing suspected but unreported diagnosis codes.

    Step 1: Smart chart routing analyzes potential unreported conditions then routes charts to coders based on coder expertise.

    Step 2: AI-enabled coding assists coders with specific diagnosis code suspects or full chart-targeted condition review.

    Step 3: Coding completeness review detects if a member’s health history may still indicate possible unreported diagnosis codes and can route chart for additional review, if needed.

    For the QA and submission step, configurable QA options and comprehensive submission services include the ability to generate and transmit submission data in multiple outbound formats based on client need.

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See how Optum can drive better risk and quality outcomes for members, health plans and providers.

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