A risk adjustment factor score (RAF score) is the score that is assigned to every patient in a risk adjustment payment model. RAF score can be calculated by taking multiple factors into account which can be a combination of disease risk score and demographic risk score that are normally called Hierarchical Condition Category HCC.
This risk management model is specifically for the insurance companies and the Centers of Medicare and Medicaid Services (CMS) that are used to represent the health status of a patient. In addition, RAF scores are calculated to estimate and predict the cost of healthcare that an organization may have to bear in the future. This is why the accuracy in calculating the RAF score is important since the organizations are funding in order to provide high-level patient care.
Obtaining an RAF score accurately is a hefty task and it is intricate for anyone who wants to achieve it. You might be asking yourself, why my RAF doesn’t reflect the patient population, why my RAF is low, and so on and so forth. But if you do so, you are not alone.
Later in the article today, we’ll discuss how you can calculate your RAF score and some reasons for which it can be inaccurate.
What is the purpose of RAF score management?
According to Healthcare.gov, the official definition used for RAF defines;
“A statistical process that takes into account the underlying health status and health spending of the enrollees in an insurance plan when looking at their health care outcomes or health care costs.”
To fully understand the purpose of RAF adjustment, it is essential to understand how the RAF score is calculated;
The calculation for a patient’s RAF score starts with the demographics and the HCC which are normally known as medical healthcare codes for their health conditions.
To ensure that the providers are reimbursed fairly for all the services they have rendered, all the members involved have unique risk codes taken from the demographic factors like gender and age and are combined together with the categories that are predefined a.k.a. HCC – Hierarchical Condition Categories.
These demographic factors include to calculate the RAF score are;
- Sex
- Age
- Eligibility or disability status
- Institutional Status (inpatient care, nursing homes, etc.)
The demographics are paired with the diagnosed enrollees list. These HCC codes are deeply assigned with the specific factor of risk adjustment, which is also a part of the ICD-10 coding system that is normally used in healthcare. However, ICD-10 codes are diagnosis factor-based such as the location of the disease, severity, and the condition.
Whereas a lower score of HCC represents the high severity which eventually raises the RAF score. For instance, let’s take diabetes, if diabetes is well-managed without any severe condition or medication needs, it would be listed with HCC 19. On the other hand, diabetes with full ketoacidosis will have HCC 17 and would be considered more severe than HCC 19. These numbers will then be combined with the demographic information and then risk adjustment for the enrollee would be determined.
In most Medicare plans, HCC and demographics are the main factors that would determine the eligibility for someone’s Medicare plans. Also, when it comes to people with chronic healthcare conditions their RAF score fluctuates every time because of the change in diagnosis on a yearly basis. Although, patients with regular treatment obligations would possibly remain in the risk adjustment models.
Risk adjustment models
According to the conditions of an enrollee, the risk adjustments would be performed from one of these three risk adjustment models. With different goals in mind, every model has a different purpose.
CDPS – Chronic Illness and Disability Payment System
CDPS is the first model which is used by Medicaid state programs for fixed payment for the providers of disabled enrollees. This model can also be used for temporary Assistance to Needy Families – TANF assisting in a specific period.
As for CDPS – there are some notable characteristics of CDPS that makes it stand out from the rest of the RAF models. These include;
- In CDPS – there are around 20 hierarchical diagnosis categories that are grouped by diagnosis types or body systems.
- Every hierarchical category and subcategory shows the intensity of diagnosis and the expected expenses for the condition.
- They focus on the enrollees who need the most care.
- Hierarchical categories are applied to categories involved and are used to count diagnoses with higher costs. To understand it more, take two cardiovascular diseases for instance. If someone has two or more severe conditions due to cardiovascular diseases, the condition with a relatively higher cost would be counted.
- CDPS can be adjusted more than once to bring changes in medical coding.
- Patients are allowed to have multiple diagnoses with different categories.
HCC – Hierarchical Condition Category
The HCC model has two forms of HCC: HHS and CMS. The CMS – HCC was regulated after the Balanced Budget Act of 1997 in order to adjust capitation payment. These payments are actually based on the enrollees’ demographics and health conditions.
On the flip side, HHS –HCC came to light as a result of the Affordable Care Act. The main notable points to mention for both forms are;
CMS-HCC:
- Hierarchical models are applied to the categories so severe and high costs are counted in every category.
- At first, the diagnosis codes were organized into 805 groups of diagnostics, which were later categorized in 189 conditional categories.
- CMS-HCC uses an additive model to determine multiple risks from multiple diagnostics categories.
- The factors that influence someone’s risk adjustment in CMS-HCC include low-income status, disability, Medicaid, gender, age, and the entitlement reason.
HHS-HCC:
- It was the newest model and was introduced in 2014.
- In HHS-HCC, the same severe and high-risk diagnoses would be counted.
- It works on budget-neutral plans, which means the transfer of funds begins with low-risk plans and proceeds to high-risk plans.
- The HHS-HCC risk scores are highly affected by factors like age and gender.
- The model includes 189 conditional categories which are then concise to 127, which address chronic diseases with high-cost plans first.
ACG – Ambulatory Care Group
Here comes the third and last model of risk adjustments. This ACG is based on a completely different approach compared to what the other two define. The model is used to assign the diagnostic codes by utilizing 32 diagnostic ambulatory groups. These codes rely on how an enrollee’s condition can affect their health and what resources would be needed.
For instance, the possibility of a disability can eventually decrease the life expectancy, hospice care, and a therapist need, which is greatly addressed in the model. The model is also known as the Case Mix model because it involves research along with risk adjustments.
However, even if you know the models used in calculating risk adjustments to have full reimbursements, chances are there that they come out inaccurate. Here’s why;
Reasons for which RAF score can be inaccurate
Inaccurate HCC Codes
HCC codes are used to maintain accurate coding according to the conditions and the related factors. If the coders are not turning up accurate HCC information other than their demographic, it’s a chance that the RAF score might become inaccurate.
You stick to retrospective HCC coding reviews
Retrospective HCC coding review is a cumbersome, highly manual, and costly process that brings an administrative burden on the shoulders of healthcare organizations. It is better to implement prospective and concurrent reviews of the process instead of a retrospective which increases productivity and brings accuracy to the RAF score at the end.
Endnote
To mention, the accurate RAF score can be obtained by implementing some effective models. Also, the correct coding and knowing what model to use according to the enrollee’s condition and severity of the diseases will help in compiling the score. For better and hassle-free coding, hiring a credential service would be a better option.