Enhancing Medical Chart Review accuracy with AI-Driven NLP-Powered solutions

With value-based care programs¹ being focused by Accountable Care Organizations² (ACOs), which includes a group of doctors and healthcare providers in the United States, offer rewards³ based on the quality of care for Medicare Advantage (MA) patients they serve to ensure better health for the population at reduced costs.

If you participate in value-based reimbursements models and are looking to adopt the latest technology to ensure optimized reimbursements from the Centers for Medicare & Medicaid Services (CMS), then this article will walk you through the next-gen artificial intelligence (AI) solutions that you can add to your existing risk adjustment workflow.

The Role of AI-enabled solutions for value-based care programs

Patient charts, also known as medical records are crucial for determining the Medicare risk adjustment factor (RAF), also known as, RAF scores.

A risk adjustment factor is an approach performed by Medicare organizations to equate the health status of its Medicare patients to a numeric value, also called risk scores. This methodology is used to ensure patients at higher risk are attended to immediately and effectively.

A risk score is assigned every calendar year dependent on demographics and diagnosis (HCCs).

Now, in order, to capture an accurate risk score, you as a Medicare organization will need to submit all CMS Hierarchical Condition Category (HCC) codes and diagnosis that affected the patient’s health in the previous year. Missing any will impact the risk score of the Medicare patient that you serve.

How is AI helping MA organizations in risk adjustment?

A Medicare patient chart review is an integral part of a risk adjustment workflow. AI is helping MA organizations and medical coding companies enhance automation while improving efficiency and productivity while performing RAF.

Latest technology for chart review in risk adjustment

From extracting those large, unstructured, Medicare patient’s clinical data sets coming from multiple EHRs and EMRs to offering accurate HCC, ICD-10, and RAF scores. AI-powered Risk Adjustment Solutions based on natural language processing (NLP), are making it easy for MA organizations and medical coding companies to identify and validate the correct diagnosis codes in real-time. In addition, AI is transforming risk adjustment workflow through:

Seamless chart retrieval

AI-enabled risk adjustment chart retrieval solution is offering will allow seamless synchronization of patient’s medical records, coming in multiple formats, to support optimized reimbursements and quality Medicare patient care. AI-driven risk adjustment solutions offer configurable chart retrieval solutions through optical character recognition (OCR) to match health care provider’s electronic health record (EHR) or electronic medical records (EMR) system while ensuring Medicare’s patient data storage over a secured cloud server.

This way, you can also have access to your Medicare patient enrollee, anytime, from anywhere.

Smarter HCC and ICD-10 medical coding workflow

From identifying unreported chronic conditions to validating accurate medical codes from patient notes, and offering a comprehensive HCC and ICD-10 summary, AI is offering automated medical coding solutions that will eliminate the chance of costly errors including unreported diagnosis that is critical for accurate RAF score opportunities.

Automated medical coding solutions

From identifying unreported chronic conditions to validating accurate medical codes from patient notes, and offering a comprehensive HCC and ICD-10 summary, AI is offering automated medical coding solutions that will eliminate the chance of costly errors including unreported diagnosis that is critical for accurate RAF score opportunities.

Ending note

RAPPID.AI, the next-gen AI-powered risk adjustment solution, has been built based on a decade-long NLP system to ensure accurate HCC, ICD-10 codes, and RAF scores for all your MA organization enrollees in real-time. In addition, risk adjustment medical coding analytics solutions will add to your revenue cycle management.

RAAPID’s risk adjustment solutions also include a retrospective audit that will help your MA organization reduce the chances of costly errors that can include overpayment, underpayment, or even, penalties from CMS.

RAAPID was recently recognized in the league of 50 Smartest Companies of the year 2022 by The Silicon Review.

Ref:

¹https://www.cms.gov/
Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/Value-Based-Programs

²https://innovation.cms.gov/
innovation-models/aco

³https://www.ncbi.nlm.nih
.gov/pmc/articles/
PMC2690317/

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Disclaimer: All the information, views, and opinions expressed in this blog are those of the authors and their respective web sources and in no way reflect the principles, views, or objectives of RAAPID.