Health and Fitness

A Comprehensive Guide to the Medicare Risk Adjustment Model for Patients

A Comprehensive Guide to the Medicare Risk Adjustment Model for Patients

This article will look at the Medicare risk adjustment model for patients. This model assigns a risk score to Medicare Advantage (MA) enrollees based on their health conditions and demographic details to account for predicted healthcare expenditures.

The risk adjustment process relies on medical record data providers submit on claims. This information helps align payments to MAOs with a patient’s risk characteristics.


The Medicare risk adjustment model for patients is vital to help manage healthcare costs and ensure that beneficiaries receive quality care. It is based on a variety of factors, including demographics and diagnoses.

The Centers for Medicare and Medicaid Services (CMS) uses this model to modify capitated payments for commercial and Medicare Advantage plan enrollees. It relies on identifying claim diagnosis codes associated with Hierarchical Condition Categories (HCCs).

To accurately capture HCC conditions for risk score calculation, healthcare organizations must submit encounter/claims data promptly. CMS has strict requirements for the medical record documentation used in this process.

While this can be time-consuming, healthcare organizations must meet federal government standards. Fortunately, new software can make the process easier by automating the search for HCCs and HEDIS gaps, reducing the clerical burden on office staff.

Physicians can also improve patient outcomes by closing gaps in HCC and HEDIS reports related to their care using this technology. This can result in more significant revenue and savings for the health plan.

The current risk-adjustment system is a prospective model which relies on the current year’s diagnoses and demographic information to predict future payments. Some experts argue that this fuels overpayments to plans and can worsen disparities in access to care by underestimating the costs of people with less health insurance who use fewer services.

Hierarchical Condition Categories (HCCs) List

HCC coding is an integral part of risk adjustment payment methodology for Medicare Advantage (MA) organizations, which leverage changes in the reimbursement to MA health plans based on the anticipated healthcare expenditures of patients with chronic conditions. This risk adjustment model helps ensure that MA organizations receive more accurate payments than traditional methods, which pay MA organizations less for healthy enrollees and more for unhealthy ones.

There are 19 HCCs, each corresponding to a specific diagnosis code in the ICD-10 medical record. For example, diabetes alone (HCC 19) is lower risk than diabetes with complications such as neuropathy and diabetic nephropathy (HCC 18).

To avoid miscoding, providers must select ICD-10 codes that align with HCCs. It is also essential to establish specific and relevant codes for the patient.

A thorough understanding of ICD-10 coding is required to code HCCs correctly for Medicare and other payers. For this reason, many coding certification programs and other resources offer courses and materials related to ICD-10 coding.

HCC coding also allows using Risk Adjustment Factor (RAF) scores assigned to individual patients to help determine risk. These complex scores can help predict a patient’s expected healthcare costs. They are a vital part of the risk adjustment process, a significant component of CMS’ Quality Payment Program.


Specific requirements must be met to participate in the Medicare risk adjustment model for patients. These requirements ensure that Medicare pays health plans fairly and avoids unfairly penalizing them for enrolling sicker beneficiaries.

To meet the requirements, health plans must accurately capture diagnoses from encounter data, the information submitted by healthcare providers through claims. This documentation must identify specific HCC (Hierarchical Condition Category) diagnosis codes associated with a patient’s chronic or severe disease.

Using accurate and complete encounter data for health plan members is crucial to achieving the most reliable and precise risk adjustment factor scores. This is important to ensure that the patient is accurately represented in the plan and that the health care costs are accurately forecasted for the subsequent contract year.

A key component to capturing the most accurate and comprehensive encounter and claims data is the complete, accurate, and timely submission of these documents. This will enable CMS to predict and predictably pay for the health care accurately costs the plan expects to incur.

The Centers for Medicare & Medicaid Services (CMS) uses the Hierarchical Condition Category method to assign risk scores to patients. This method puts related encounter data like medical diagnoses into groupings based on resource use and anticipated cost.


The Medicare risk adjustment model for patients is a reimbursement tool healthcare organizations use to help ensure they receive adequate compensation for their medical costs. This compensation is essential to maintaining coverage and access for patients more likely to require expensive services and treatments than the average patient.

The model combines a range of risk adjustments into one calculation to accurately predict the healthcare costs associated with enrollees. This includes prospective (diagnosis coding) and retrospective (claims data) risk adjustment.

For prospective risk adjustment, CMS uses diagnosis codes submitted by healthcare providers through claims to calculate a risk score. This score is then used to determine Medicare payments to healthcare organizations.

Inpatient diagnoses are preferred for risk adjustment, as they reflect more individualized information about the patient’s disease burden than ambulatory encounter data. Additionally, they are more easily collected than mobile encounters.

A risk score is then multiplied by a published denominator to derive an expected annual expenditure for each beneficiary. This amount is then used to calculate the per-member-per-month (PMPM) capitated payment to the healthcare organization for that specific period.

Written by
Cosmo Jarvis

Cosmo Jarvis is a multi-talented artist excelling in various creative realms. As an author, his words paint vivid narratives, capturing hearts with their depth. In music, his melodies resonate, blending genres with finesse, and as an actor, he brings characters to life, infusing each role with authenticity. Jarvis's versatility shines, making him a captivating force in literature, music, and film.

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