RAAPID at RISE National 2024

Music City Center

Nashville, TN 

March 17-19, 2024

RISE Booth # 1057

We are Excited to Meet You

At RAAPID,  we are an end-to-end risk adjustment solution provider for payers and providers. We are passionate about making a positive difference by leveraging the power of our clinical Large Knowledge Models (LKMs).

We are excited to shake hands with you at RISE National in Nashville.

RAAPID Overview

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Neuro-Symbolic AI

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Execution Matters

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Prospective Previsit Solution

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Retrospective Risk Adjustment Solution

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Execution Matters

RAAPID’s Clinical NLP (CNLP) infused Large Knowledge Models (LKMs) Platform Powers an End-to-End Risk Adjustment Solution that Matters.

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Key Benefits

RAAPID’s retrospective risk adjustment solutions process structured and unstructured clinical data to suggest accurate HCC codes to increase the RAF score.

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Efficiency and Outcomes Matter

We analyze the membership and claim data to intelligently and effectively stratify and prioritize members based on probable higher ROI and reduce chart retrieval, Retrospective Review/Audit, Data submission, and Vendor management. This eventually reduces the period of the retrospective risk adjustment program.

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Cost, Accuracy & Scalability Matters

We bring pace to your chart retrieval (>90% failure rate), bring down the cost of coding by 40% (onshore/offshore), and increase productivity by 2X. With the help of our in-house coders and partners, we can handle large volumes of charts.

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Privacy & Compliance Matters

RAAPID cares about compliance, privacy, and risk when exposing PHI. Masking PHI no matter where people access data (Onshore or Offshore), privacy, security, and compliance is ‘taken up yet another notch’ through de-identification and masking the eighteen (18) elements of PHI without affecting a Coder’s or Auditor’s ability to do their job. You can turn this on/off as per your project requirement.

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Risk Elimination Matters

OIG and RADV audits will undoubtedly increase. However, using RAAPID’s retrospective risk adjustment solution, health plans can minimize the risk of penalties if/when they get an audit and any defense or reconciliation during these audits as they will consistently submit optimum appropriate MEAT evidence-based ADDs and DELETEs of HCC codes. As we proudly say, RAAPID’s technology is soft-approved by one of the RADV auditors.

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Compliant ROI Matters

We enable payers to run the most profitable retrospective risk adjustment programs by maximizing the revenue without getting penalized by auditors. RAAPID also delivers a compliant ROI on prospective pre-visit, where we reduce care gaps and suspect potential emerging conditions to effectuate better RAF scores. All this with explainable AI ‘human in the loop’ of risk-based management reduces variation and costs to deliver appropriate reimbursement compliantly.

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Reducing Clinician Burnout

In today's clinical setup, pursuing efficiency and providing the best possible patient care is an ongoing process rather than a final goal. We analyze 360-degree longitudinal data that reduces chart review time by 60% to surface care gaps and emerging chronic conditions. With the mission of caring for caregivers, RAAPID’s prospective pre-visit risk capture technology helps to reduce clinician workload and shifts the focus towards patient-centered care.

Meet the RAAPID team at RISE

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Chetan Parikh

Founder & CEO

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Michael Clark

President & Chief Growth Officer

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Yaw Asante

Vice President - Sales

Christopher Lally

Christopher Lally

Vice President - Operations

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Devanshu Yadav

Vice President - Corporate & Strategy

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Durai Ramachandiran

Vice President - Products

Why RAAPID’s Risk Adjustment Solution is Perfect for You

Fostering Risk Adjustment

Fostering Risk Adjustment

As we transition to value-based care (VBC) and risk-based contracting, health plans and providers’ financial performance is linked with risk adjustment. Our retrospective risk adjustment solutions utilize natural language processing (NLP) to accurately read unstructured & structured medical records to better identify risk, and improve the Efficiency & ROI of Risk adjustment programs

Fostering Risk Adjustment

Clinically Trained Large Knowledge Models

Trained on 30M+ of real and diverse clinical data, our solutions are built upon state-of-the-art AI, NLP, Machine Learning (ML), and Deep Learning (DL) models that interpret the context surrounding identified information to get a better clinical understanding

Clinically Trained Large Knowledge Models
Explainable AI

Explainable AI

We believe in explainable AI, meaning all the output the system suggests is backed by reasoning, context, and MEAT evidence presented to the end users. It is a “Human-in-the-loop” solution that frees reviewers & QA from manual processes and helps them focus on things that really matter – Data Interpretation & Decision making.

Explainable AI

Highly Configurable & Cloud Agnostic

One-size-fits-all, out-of-the-box AI solutions never work in Healthcare. Built on modern cloud architecture and API first approach, we work with our customers to fine-tune our models and customize workflows to deliver truly personalized solutions on any cloud platform. (Google, Azure, AWS or Government cloud)

Highly Configurable Cloud Agnostic

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