Chief Analytics and Data Officer, Anthem: Value-Based Care is One of the Most Fundamental Transformations

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(US and Canada) Neel Butala, Co-Founder HiLabs talks with Ashok Chennuru, Chief Analytics and Data Officer, Anthem, about the impact of big data on patient outcomes and the cost of varied value-based care programs.

Chennuru shares that the plants need to adopt technology to continuously and comprehensively monitor data quality. Value-based care is one of the most fundamental transformations happening at Anthem and across the healthcare or health plan industry and even with the providers. Value-based care consumes data from many of our significant and critical data sources, including our claims provider, clinical social drivers, etc. Layered on top of it are complex configurations that can correctly attribute members based on quality and cost of care to the right providers.

He shares that this is driven by particular value-based care arrangements. With different provider groups, elders, anywhere upstream or within the process can cause misattribution and delays or others reported to providers regarding the costume quality and delay payments, which creates, you know, provider operation.

Anthem has been a pioneer in value-based care and has invested almost a decade in developing and scaling its BBC processes of value-based care processes. However, for most of the time, Anthem has managed the processes by applying traditional rules-based approaches that can be challenging to maintain, which said dynamic and changing data.

We are now adopting machine learning techniques powered by Hilabs, like the M-chat process that can detect and correct others, both upstream and downstream, while also performing root cause analysis. So we can proactively fix issues rather than discover them after an event has occurred. Advanced analytics and machine learning techniques are the fundamental change in delivering high-quality, robust value-based care programs across Medicare, Medicaid, and commercial businesses.

Anthem is highly focused on lowering the overall cost for our members while improving the quality of care. The critical challenge for health plans and cost of care is how we can quickly identify the actual cost of care opportunities and a bit leading indicators and take action to realize, uh, the, uh, outtake actions or interventions to realize that. So at Anthem, we have invested heavily in aggregating the cost of care data from across the enterprise and building robust reporting and analytic data-driven discovery opportunities for cost reduction and quality improvements. However, even with significant investment in data and analytics, we still require teams of analysts to discover and confirm the cost of care opportunities. This is another area where AI-driven machine learning models can be powerful and have pattern recognition, and the ability to print early in the cycle is a great opportunity. We hope to leverage ML platforms to create this automatic pattern matching and recognition. Then, our analysts can spend most of the time determining how to realize those opportunities versus investing a lot of time in analyzing the data.