Healthcare professionals know the significance of working with high quality personnel and adopting key applied sciences to make sure productiveness and effectivity.
Relating to deciding on expertise for the healthcare ecosystem, RAAPID is proving to be the next-gen AI-driven threat adjustment answer for each healthcare suppliers and insurance coverage firms to attain correct threat adjustment issue (RAF) scores for Medicare enrollees inside optimum timeframes.
RAAPID, the world’s first customized and customised AI assistant for threat seize, leverages pure language processing (NLP) expertise to assist healthcare insurance coverage firms, often known as payers, and medical coders enhance the accuracy and supply of RAF scores.
As well as, the trendy threat adjustment answer helps healthcare payers to automate administration workflow and reduce the chart overview timings.
With many medical coders and insurance coverage firms which can be used to standard threat adjustment strategies, RAAPID could be infused inside an current workflow to allow pure language processing (NLP) expertise for figuring out and validating Hierarchical Situation Class (HCC) and Worldwide Classification of Illnesses (ICD) codes in real-time.
Backed up with a group carrying a long time of business expertise, RAAPID is reimagining the danger adjustment course of for healthcare, insurance coverage, and expertise companies by permitting them to carry out chart overview workflow in simply three clicks.
The SaaS-based answer which can be accessible in an API, mechanically assesses and addresses the general goal of a retrospective audit by the Facilities for Medicare and Medicaid Companies (CMS).
CMS’ total goal of the retrospective audit is to:
- Evaluate high quality of care offered to sufferers
- Educate suppliers on documentation tips
- Decide if organizational insurance policies are present and efficient
- Optimize income cycle administration
- Guarantee acceptable income is captured
- Defend in opposition to federal and payer audits, malpractice litigation, and well being plan denials.
Earlier than the beginning of every 12 months, every MA group submits bids to the CMS that replicate their estimate of the month-to-month income required to cowl an enrollee with a median threat profile. The CMS compares every bid to a selected benchmark quantity for every geographic space to find out the bottom fee that an MA group is paid for every of its enrollees.
As part of the danger adjustment program, CMS consolidates sure HCCs into related-disease teams. For every of those teams, CMS assigns an HCC for less than high-risk ailments in a related-disease group. Thus, if MA organizations submit analysis codes for an enrollee that map to greater than one of many HCCs in a related-disease group, solely probably the most extreme HCC will probably be considered for figuring out the enrollee’s threat rating.
CMS multiplies the scores by the bottom charges, to sum up, the entire month-to-month Medicare fee that an MA group receives for every enrollee earlier than making use of the finances sequestration discount.
For healthcare payers to carry out threat adjustment with out expertise can result in:
- Use of extra manpower to fulfill CMS documentation tips and submission deadlines
- Lacking on figuring out these unreported diagnoses for RAF scoring alternatives
- Pricey errors whereas performing these repetitive threat adjustment duties.
A tech-driven RAF rating derivation workflow is pivotal for healthcare organizations, insurance coverage firms, medical coders, and well being suppliers. RAAPID’s HCC threat adjustment answer will convey automation in chart retrieval, overview, and validation of HCC and ICD codes. This manner Medicare organizations can guarantee a retrospective audit strategy to find out whether or not chosen analysis codes submitted to CMS to be used in CMS’s threat adjustment program have complied with Federal necessities.
Why RAAPID?
RAAPID strongly consider that the MA organizations ought to have entry to their MA enrollee’s knowledge anytime, from wherever. The trendy medical coding answer can be configurable primarily based on the MA group’s ever-growing wants.
Unlock the next-gen AI-based, NLP-powered threat adjustment answer and optimize reimbursements from the CMS.
