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A clearer picture of quality performance with AI

Manual abstraction for quality measure compliance is inefficient and doesn’t capture a true picture of quality gaps that need to be addressed by clinicians to improve patient care. Artificial Intelligence (AI) can streamline the clinical abstraction process and deliver a more accurate analysis of performance against quality measure benchmarks.

More accurate quality reporting in less time

Providers and plans are under pressure to accurately measure and improve patient care quality. While many process measures are easy to glean from claims, important procedure and outcome measures require abstractors to look for evidence of measure compliance in patient charts. Quality abstraction & overreading is expensive, time consuming, and distracting—but AI technology can help.

Quality Identifier - Confirmed Evidence of Quality Measure Compliance

Benefits of AI-powered quality abstraction

  • Accuracy. Sophisticated AI models can find more evidence of numerator compliance than manual chart reviews.
  • Speed. Abstractors are pointed directly to predicted quality facts for review without having to wade through every page of a patient’s chart.
  • Control. Manage abstractor and overread assignments, track progress toward measure goals, and view a detailed record of decision-making for every measure set.

Our solution

Quality Identifier

Quality abstraction and overreading is a time consuming, costly process. Apixio’s Quality Identifier solution uses AI algorithms to locate evidence of numerator compliance in patient charts. Abstractors can quickly review predicted clinical facts and confirm whether they demonstrate compliance with relevant measures, significantly reducing the amount of time needed to gather supporting evidence for HEDIS and MA Stars submissions.

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