Utilize our RAF Batch Scoring tools to quickly identify missed documentation opportunities and focus on areas requiring improvement.
Instant RISK Score
for Extensive Chart Datasets
Calculation of RAF scores and Medicare Advantage Payments.
Watch Our Step-by-Step Demo To Know
How To Use This RAF Score Calculator

Your shortcut to calculate accurate Scores and
Medicare Advantage Payments

CMS HCC RAF Score Calculator
S.No ICD 10 CM Code HCC Value Diagnosis Description Delete Record

Medicare HCC RAF Score Calculator Click to edit

RAF Score and MA Payment

Want to download as PDF?

Category RAF Score MA Payments
What is Revenue Impact Analysis Report (RIAR) and how is it used in Prospective Reviews?

Before sending Dx codes from Prospective reviews to Physicians for CDI, a RIAR is generated using the demographic and Dx data to compare the revenue impact from Missed and New Dx codes with Billed Dx codes. The goal is to find and prioritise high-value diagnosis codes linked to HCC. Those high value Dx codes with medical evidence are then included as suggestions in EMR for physician review and CDI. Alternatively, the RIAR can be directly shown to physician for review and CDI. All these require absolutely no PHI data. Click here,to generate RIAR.

Why are healthcare organizations hesitant to do Prospective Reviews despite the big financial benefits?

Prospective reviews cost lot because it involves risk adjustment coding for the entire population, and also it takes lot of physician’s time for CDI. This means each patient's data must be quickly and carefully reviewed before the encounter to decide if it's worth doing a prospective review for potential revenue. Not every prospective review will find high value diagnosis codes linked to HCC. A big reason for this hesitation is that there aren't good tools to help pick the right charts for prospective review, and find the high value diagnosis codes after prospective review. The lack of awareness and helpful tools make it harder to feel excited about doing prospective reviews. Click here, to generate RIAR.

Discover how to prioritize charts and maximize revenue potential with our REST API web service. Sign up now
REST API: Optimize Risk Adjustment,
Detect Gaps, Identify High-Risk Patients &
Monitor Real-Time Risk Trends

Discover the RAF Score Calculator to simplify the way you approach post-prospective chart reviews and clinical document improvement (CDI) recommendation.

The RAF Score Calculator is a simple and quick solution that combines demographic and diagnosis risk scores to provide a comprehensive evaluation of a patient's health. The demographic risk score encompasses critical factors such as age, community, medical institution, and age-gender interactions. Meanwhile, the diagnosis risk score is founded upon the Hierarchical Condition Category (HCC) codes extracted from the patient's ICD-10 codes for diagnosis, reflecting chronic conditions.
By meticulously analyzing these factors, the RAF Score Calculator offers an accurate understanding of a patient's health landscape. The importance of the Risk Adjustment Factor Score cannot be overstated as they directly impact budgeting and resource allocation for shared-risk providers and payers.
A low risk score, while potentially indicating a healthier population, can also highlight the significance of accurate and comprehensive documentation. On the flip side, a high risk score signals patients with heightened health risks, necessitating a more intricate level of care and allocation of resources. An HCC RAF score of 1.00 serves as a benchmark for average resource utilization, while an HCC risk score surpassing 1.00 signifies increased resource requirements.

Benefits of RAF Score Calculator

  • With the RAF Score Calculator, the healthcare providers and payers gain a precise tool to allocate resources effectively. In addition to it, the risk score directly influences the average Medicare Advantage patient rate, ensuring that resource allocation corresponds accurately to a patient's health status.
  • This RAF Score Calculator tool is designed exclusively for medical coders and physicians. Its purpose is to streamline your approach to post-prospective chart reviews and clinical document improvement (CDI) recommendations.
  • RAF Score Calculator greatly assists medical coders in calculating risk scores with revenue impact, making the analysis process remarkably easy and quick.
  • This innovative RAF Score Calculator shifts the paradigm from a generalized approach to healthcare to one that is fine-tuned, patient-centric, and results-driven.

How To Use RAF Score Calculator

There are three primary categories of risk models in this Calculator: CMS-HCC, RxHCC, and ESRD, each featuring distinct models for both continuing and new enrollees. Upon selecting a risk model, you will find a list of corresponding risk factors available for selection. Following this, you can choose the gender and input an age up to 120.
Subsequently, you can enter up to 20 diagnosis codes either by manual entry or by copying and pasting them into the provided text box, separating them with commas.
For record removal, the delete button is available at the end of each row. Upon inputting all necessary data, click the submit button to generate the Revenue Impact Report.
Our RAF Score Calculator performs distinct calculations for RISK scores and Medicare Advantage Payment across demographics, diagnoses, and disease interactions. At the top of the Revenue Impact Report, you can find the button to download the report in PDF format generated by our RAF Score Calculator.
At the top of the Revenue Analysis Report, you can find the button to download the report in PDF format generated by our RAF Score Calculator.
Suggested Pages
npi graph

A Comprehensive Guide on HCC Coding Reviews

npi graph

Understanding the CMS HCC Risk Adjustment Model and its Significance

npi graph

The Role of RAF Score Calculator in Achieving Sustainable Success in Risk Adjustment

npi graph

Understanding HCC Risk Adjustment Coding (RA) in Healthcare Industry

Demographic Inputs
Risk Model
Risk Factor