Understanding the Role of Hierarchical Condition Categories (HCCs) and How They Impact Target Prices Under CMS TEAM

In the world of value-based care, understanding how patient complexity is captured and reimbursed is key to success- especially in Medicare's newest payment innovation: the Transforming Episode Accountability Model (TEAM). Within this, one of the most critical tools in this process is the Hierarchical Condition Category (HCC) system.

This article will cover everything you need to know surrounding HCCs, how they work, their role within CMS team, and how hospitals can use it to their advantage.

What Are Hierarchical Condition Categories (HCCs)?

Hierarchical Condition Categories, or HCCs, are a clinical classification system developed by the Centers for Medicare & Medicaid Services (CMS) to adjust payments based on patient health status. Each HCC represents a group of related diagnoses that are expected to carry similar cost implications. CMS uses HCCs to quantify the disease burden of individual beneficiaries, essentially flagging which chronic or acute conditions a patient has that may require more complex, costly care.

In the TEAM model, HCCs are derived from inpatient, outpatient, and physician claims using Version 28 of the Medicare Advantage Risk Adjustment Software, and include both specific HCC flags (e.g., HCC48 Morbid obesity) and a count of how many HCCs are present for each beneficiary (categorized as 0, 1, 2, 3, or 4+).

Why Do HCCs Matter in TEAM?

Within the CMS TEAM methodology, HCCs play a pivotal role in determining the target price- the spending benchmark against which hospital performance is measured.

Since hospitals don’t control which patients walk through the door, CMS includes risk adjustment to level the playing field. HCCs are one of the primary patient-specific risk adjusters used to reflect this variation in case mix.

Here's how HCCs influence the TEAM target price process:

• Risk Adjustment Multiplier: Each clinical episode is evaluated for patient-level factors—including the presence and count of HCCs—that are then used in a weighted linear regression model. This model estimates the expected deviation in spending based on those characteristics. The result is a risk adjustment multiplier, specific to each episode, that adjusts the baseline benchmark price upward or downward.
• Target Price Calculation: For hospital-specific pricing, CMS applies the average risk adjustment multiplier—heavily influenced by HCC presence—to the regional benchmark price. This ensures that hospitals treating more medically complex patients aren't unfairly penalized in a cost-based performance evaluation.

In short, accurate and thorough Hierarchical Condition Category coding is not just an administrative task, but rather directly affects financial sustainability under the TEAM model. It ensures hospitals are credited appropriately for the acuity of the patients they serve, and it aligns reimbursement with the real cost of care delivery.

How CMS TEAM Actually Applies HCCs

Here is how CMS actually applies HCCs to adjust risk:

1. Calculates regional preliminary target prices using three years of baseline episodes and communicates them before the performance year.

2. Computes risk adjustment factors through a national regression using claims from specified three-year windows. The exponentiated coefficients become multiplicative risk factors.

3. Applies, at reconciliation, the beneficiary-level HCC count factor and episode-specific HCC indicators, plus age and social need, and hospital-level factors for bed size and safety-net status. Prices are then normalized.

High-Value HCCs in CMS TEAM — The Conditions That Move the Needle

In the CMS TEAM model, not all HCCs carry equal weight. Some conditions are so commonly predictive of cost variation across multiple bundles that they play an outsized role in determining a hospital's target price. These are what we call high-value HCCs- conditions that, when documented and coded accurately, can significantly influence risk-adjusted benchmarks across a wide range of episodes.

A handful of HCCs appear in all five of the TEAM clinical episode types, indicating their broad relevance across surgical areas. By identifying and coding these high-value HCCs reliably, hospitals can more accurately reflect their patient population's clinical complexity and ensure their benchmarks are appropriately adjusted. The list of high-value HCCs include:

• HCC37 Diabetes with Chronic Complications
• HCC48 Morbid Obesity
• HCC125 Dementia, Severe
• HCC126 Dementia, Moderate
• HCC127 Dementia, Mild or Unspecified
• HCC199 Parkinson and Other Degenerative Disease of Basal Ganglia
• HCC226 Heart Failure, Except End Stage and Acute
• HCC238 Specified Heart Arrhythmias
• HCC253 Hemiplegia/Hemiparesis
• HCC326 Chronic Kidney Disease, Stage 5
• HCC383 Chronic Ulcer of Skin, Except Pressure, Not Specified as Through to Bone or Muscle

Common Pitfalls that Decrease Target Prices — And Can Result in Financial Penalties for Your Organization Under CMS TEAM

Understanding the role of HCCs is the first step but accurate and consistent implementation is where the impact of HCC documentation can be leveraged. In a value-based healthcare model like TEAM, capturing the right diagnoses ensures the full clinical story of the patient is told.

Yet, despite their importance, HCCs are frequently under-documented, misclassified, or missed altogether, especially during pre-operative workflows or time-pressured encounters.

Several recurring issues can compromise the accuracy and completeness of HCC coding:

• Incorrect Coding of Chronic Conditions: Chronic diseases must be specifically identified and documented as chronic—not simply mentioned or listed on the problem list. Without clear evidence of ongoing treatment or monitoring, these conditions may not qualify for HCC capture.
• Nonspecific Diagnoses: General ICD-10 codes like I50.9 (Heart failure, unspecified) fail to map to higher-weighted HCCs such as HCC226 (Heart Failure, Except End Stage and Acute). This can result in significant under-adjustment for patient risk.
• Lack of Clinical Validation (MEAT): Diagnoses that are not clearly Monitored, Evaluated, Assessed, or Treated in documentation may be disqualified during audits, even if the patient truly has the condition.
• HCC Drop-Offs: Chronic conditions must be actively documented each calendar year. If a condition like diabetes with CKD isn’t reaffirmed in current documentation, it disappears from the patient’s risk profile causing RAF score decay and reduced benchmark pricing.
• Pre-Op Blind Spots: Pre-surgical evaluations often prioritize acute surgical clearance, but fail to reaffirm underlying chronic conditions that carry weight in TEAM’s risk adjustment model—leaving money and clinical flags on the table.

Real World Example — How Documentation Can Impact CMS TEAM Target Price

How does this translate into missed opportunities? Below are two documentation examples that show just how much a few words can change both clinical risk visibility and payment.

Scenario 1: “Patient has type 2 diabetes. Also has chronic renal insufficiency. Stable at this time.”

• Resulting ICD-10 Codes: E11.9 – Type 2 diabetes without complications; Possibly N18.9 – CKD, unspecified
• Mapped HCCs: HCC38 – Diabetes without complications (~0.105 RAF) + CKD unspecified (does not directly map)
• Total RAF: ~0.105

Scenario 2: “Patient has type 2 diabetes mellitus with stage 3 chronic kidney disease, currently stable on medication and monitored regularly. This condition was evaluated and discussed today.”

• Resulting ICD-10 Codes: E11.22 – Type 2 DM with diabetic CKD; N18.3 – CKD Stage 3
• Mapped HCC: HCC37 – Diabetes with Chronic Complications (~0.318 RAF)
• Total RAF: ~0.318

Compared to Scenario 1, Scenario 2’s documentation increases the RAF score by approximately 30% RAF weighting increase, a higher set target price and a higher reimbursement amount. Simply by clearly linking diagnoses (“diabetes with stage 3 CKD”); denoting that the condition is staged (CKD Stage 3); and satisfying MEAT-criteria (evaluated, monitored, treated), a potential missed HCC coding opportunity is avoided.

Opportunities to Optimize HCC Documentation

To address these gaps, organizations should embed HCC awareness into every stage of the patient journey, especially in areas like pre-op visits, surgical planning calls, and post-discharge follow-up.

Opportunities in Pre-Operative Workflow

• During pre-op visits, clinicians should take a moment to reconcile the full problem list and actively document chronic conditions, not just those immediately relevant to the surgery.
• Nurses and schedulers conducting pre-surgical phone calls can be trained to flag uncontrolled or unaddressed conditions (e.g., poorly managed diabetes, chronic ulcers, cognitive impairment) and route patients for appropriate evaluation prior to the procedure.
• Coders and clinical documentation specialists (CDIs) can partner with surgical teams to create checklists for high-value HCCs based on the clinical episode type

Leveraging EPIC EHR for Smarter Coding

Epic’s EHR platform offers multiple tools to make HCC documentation easier, more consistent, and less burdensome for clinicians.

• SmartPhrases: Using SmartTools like .cd SmartPhrases and SmartTexts, clinicians can insert predefined blocks of clinically and code-validated text into their notes. This workflow allows for rapid, standardized MEAT-compliant documentation that supports HCC capture without adding friction.
• SmartTexts: Pre-built SmartTexts can include embedded SmartLists to capture disease severity (e.g., CKD stage or ulcer depth); prompts to confirm active management of chronic conditions; and fields that encourage clinicians to complete the documentation with specificity and intent.

AI-Driven Coding Nudges

Some organizations also layer in AI coding support tools that integrate with their EHR and performance evaluation softwares to flag missing HCCs or ambiguous diagnoses before the note is signed. This provides real-time prompts to clarify vague conditions.

Making HCCs a TEAM Sport

Ultimately, HCC capture is responsibility shared by the entire clinical care team- it requires participation from clinicians, nurses, CDIs, and analysts alike. When every team member sees documentation as a tool to accurately represent patient complexity, hospitals are better positioned to thrive in models like TEAM. From surgical schedulers to attending physicians, every interaction is an opportunity to reinforce the patient’s full risk profile- one accurate ICD-10 code at a time.