The US healthcare system is undergoing a seismic shift: value-based care (VBC) is quickly taking over fee-for-service (FFS), with the number of healthcare payments that involve some form of value component increasing over 500% since 2012. But what does that mean for high-risk patients – and how will it impact access to quality care?
This article explains how patient risk scores are used to calculate value-based care payments.
Patient risk scores are metrics used in healthcare to estimate an individual’s likelihood of experiencing a specific health outcome, such as disease progression, complications, hospitalization, or mortality.
Rather than a single universally applicable score, there are hundreds of different patient risk scores in usage. Some of these are highly specific, such as the qRISK2 score, which is used to measure how likely a patient is to have a heart attack in the next 10 years. Others measure a broader range of risks, such as the risk adjustment factor (RAF) score, which is used to measure and compare the expected cost of care for all patients under Medicare Advantage plans.
The overarching goal of value-based care is to reward the quality of service a healthcare provider offers, rather than the quantity of services they administer. But this presents a problem: what if a provider happens to take on a large proportion of high-risk patients that require a lot of expensive treatments?
The provider may not receive adequate reimbursements; they might even receive the same reimbursements for caring for a patient with far fewer care requirements – making lower-risk patients more financially attractive and creating a negative incentive to enroll more low-risk patients.
The Centers for Medicare and Medicaid Services (CMS) understood that this could disadvantage high-risk patients and make it harder to find a provider. That is why they introduced risk adjustment: a process designed to adjust reimbursement rates based on the level of patient risk.
The CMS risk adjustment methodology measures patient risk using a risk adjustment factor (RAF) score. The organization uses data on historical care costs to set a “base rate” for each county:
For example, if the annual base rate is $12,000, caring for a patient with an RAF score of 1.5 will entitle your practice to an MA reimbursement of $18,000.
RAF scores are based on two core factors: Demographic Information and Medical History. These two elements are combined to produce a single RAF score that considers all aspects of the patient’s previous and expected health risks – and therefore provides a reasonable estimate of their future care requirements and costs:
Demographic data used includes:
Each demographic characteristic is assigned a specific risk score based on actuarial data. For example, older patients are typically given higher RAF scores.
CMS uses a system of Hierarchical Condition Categories (HCCs) to account for an individual’s health conditions. This system:
For example, a patient with diabetes and complications may have a higher HCC score than a patient with diabetes without complications.
The CMS also considers the interaction between certain conditions that, when present together, can significantly increase a patient’s predicted healthcare costs. For example, diabetes combined with chronic obstructive pulmonary disease (COPD) may yield an additional adjustment because these conditions together present greater complexity than each on its own.
Patient risk scores are the backbone of value-based care reimbursements. But establishing accurate scores requires:
All of which makes the process time-consuming and difficult for physicians – especially when they are already so busy.
HCC Assistant uses natural-language processing (NLP) to produce HCC coding recommendations at the point care – with 98% accuracy. The tool saves hours of effort for your physicians, simplifies the risk adjustment process, and helps the average provider increase their RAF scores by 35%.
Want to see how it could make life easier for your physicians – and ensure you receive fair insurance reimbursements?
