RAAPID at RISE National 2024
Music City Center Nashville, TNMarch 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.
Execution Matters
RAAPID’s Clinical NLP (CNLP) infused Large Knowledge Models (LKMs) Platform Powers an End-to-End Risk Adjustment Solution that Matters.
Key Benefits
RAAPID’s retrospective risk adjustment solutions process structured and unstructured clinical data to suggest accurate HCC codes to increase the RAF score.
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.
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.
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.
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.
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.
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
Why RAAPID’s Risk Adjustment Solution is Perfect for You
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
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
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.
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)
