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Introducing RAAPID.AI – World’s First AI Assistant for Risk Capture

LOUISVILLE, Ky., February 24, 2022 ( – Healthcare is hard. And, when it comes to HCC Risk Adjustment, obstacles like inefficiencies & inaccuracies often crop up. And not to mention the failed audit reports and other legal implications relating to repaying the Centers for Medicare and Medicaid Services (CMS). This is just the tip of the iceberg.

Healthcare for approximately 110 million Americans is provided by the U.S. government through value-based care programs like Medicare, Medicaid, and the ACA exchange.

These programs rely on a system called risk adjustment. Around the world, every health care system is struggling with rising costs and uneven quality despite the hard work. It’s time for a fundamentally new strategy.

There was a time when “risk” used to be an interdiction among business leaders – something to be totally circumvented. But risks are a necessary part of moving the business forward. The whole cognition for risk is to innovate faster, and one needs to experience failure to do it, but in a way that leads to a new understanding to measure opportunity with the same yardstick that measures the risk involved.

Originating knowledge and understanding through science accoutres us to find solutions to today’s acute economic, social and environmental defiance Indicators and statistics take into account the broad range of country-specific contexts. In this milieu, a solid and comprehensive knowledge sharing on the latest and greatest advancements in Healthcare with Science and Technology is crucial.

There is great optimism that the application of artificial intelligence (AI) can provide considerable improvements in all the genres of healthcare from diagnostics to treatment. AI is ready to support healthcare personnel with a variety of functionalities from administrative workflow to clinical documentation and patient outreach, risk adjustment, proper HCC coding as well as specialized support such as in image analysis, medical device automation, and patient monitoring.

At RAAPID, “The risk-taking belief” begins with a commitment to meeting every customer’s needs

while promoting the safety and wellness of millions worldwide. “We are reimagining risk adjustment for healthcare, insurance, and technology businesses,” says Chetan Parikh – Founder & President RAAPID. has developed its state-of-the-art NLP (Natural Language Processing) technology that runs on top of Deep Learning algorithms. To establish a complete, accurate RAF for patients, all health conditions need to be accurately identified, addressed, and documented annually via claims submitted to the government for reimbursement.

RAAPID helps organizations ace reimbursement calculations and risk adjustment scores. The patented technology has been trained across millions of real clinical charts and delivers accurate outcomes. This AI-powered Risk Adjustment Software ensures you don’t miss out on HCC codes or RAF scoring opportunities.

Risk adjustment is critical for insurance Companies as risk-bearing entities take a fixed fee for covering the future cost of care for their members before they know the actual costs, the proper calculation is done once the state or the federal government overseeing the program receives all the diagnoses for all the members in the calendar year. Risk adjustment is a methodology where insurance companies participating in specific programs get their payments for managing the healthcare needs of their members based on diagnosis and a risk adjustment health plan relies on the accurate and consistent submission of all conditions each year. Risk adjustment modifies payments to all insurers based on an expectation of what the patient’s care will cost.

Traditional risk adjustment just isn’t efficient. Coders comb through thousands of pages of patient charts and look for documented chronic conditions. But this isn’t the most effective or efficient process. Data completeness and quality are the biggest implementation challenges. As, without analytics, they do not know how their risk adjustment process is performing overall and identify ways to improve as an organization.

Making this transformation is not a single step but an overarching strategy. RAAPID calls it the “Risk-Taking Belief”, as RAAPID combines the latest advances in machine learning, AI, natural language processing, data science, and data engineering with deep clinical and biomedical expertise to build the tools that allow health systems, to become fast, effective and error-free.

“With a comprehensive workforce of over 500 members who are industry veterans, based out of Louisville, Kentucky, RAAPID’s pedigree is built upon Trust, tech competence, stability, and Tech Innovation,” says Chetan.