Oncology and Hematology Coders: Get Tips on HCCs and Risk Adjustment

Providers and coding staff should understand HCCs

Risk adjustment models often focus on chronic conditions, like cancer, when determining risk scores for patients. But limiting your medical coding to a single diagnosis isn’t the best approach for these increasingly important payment models. Oncology and hematology coders can get their reporting in line with risk adjustment models, including Hierarchical Condition Categories (HCCs), by following these tips.

Take A Quick Look at HCCs and Risk Adjustment

If you’re unfamiliar with HCCs, here are the basics. Medicare uses HCCs for Medicare Advantage and a couple of other programs. Other third-party payers also may use HCCs or a similar construct in their contracts with providers to determine payment rates.

For Medicare Advantage organizations, the Centers for Medicare & Medicaid Services (CMS) pays a fixed amount (capitated payment) per member per month instead of using a fee-for-service structure. If a patient requires more resources than the fixed amount covers, the Medicare Advantage organization has to cover that cost. Sicker patients typically cost more to treat, so to help remove the incentive for organizations to cover only the healthiest patients, CMS adjusts the capitated payment using the CMS-HCC model.

About one in seven ICD-10-CM codes maps to one or more HCC codes from CMS. There are roughly 80 HCCs, and each HCC is associated with a Risk Adjustment Factor (RAF) that helps with predicting the cost of care. CMS uses the HCCs (based on ICD-10-CM codes submitted by providers) and the patient’s demographic data to calculate the payment to the plan. The calculation uses historical code data, so the codes reported in a given year affect future payment.

In short, capturing ICD-10-CM codes that demonstrate the complexity of patient care (reason for the encounter, conditions treated, conditions affecting treatment) translates into more accurate future payments under these risk adjustment models.

Get to Know Hem/Onc HCCs

There are some HCCs that have a clear connection to oncology and hematology coding. Below you’ll find some examples of these HCCs as well as a small sampling of the ICD-10-CM codes that cross to those HCCs. This information applies to Medicare Advantage Plans V22 and V24 and is taken from the 2020 Midyear Final ICD-10 Mappings.

HCC 8: Metastatic Cancer and Acute Leukemia

  • C77.0 (Secondary and unspecified malignant neoplasm of lymph nodes of head, face and neck)
  • C92.01 (Acute myeloblastic leukemia, in remission)

HCC 9: Lung and Other Severe Cancers

  • C15.3 (Malignant neoplasm of upper third of esophagus)
  • C34.01 (Malignant neoplasm of right main bronchus)

HCC 10: Lymphoma and Other Cancers

  • C40.00 (Malignant neoplasm of scapula and long bones of unspecified upper limb)
  • C83.06 (Small cell B-cell lymphoma, intrapelvic lymph nodes)

HCC 11: Colorectal, Bladder, and Other Cancers

  • C03.1 (Malignant neoplasm of lower gum)
  • C18.2 (Malignant neoplasm of ascending colon)

HCC 12: Breast, Prostate, and Other Cancers and Tumors

  • C50.111 (Malignant neoplasm of central portion of right female breast)
  • C61 (Malignant neoplasm of prostate)

HCC 46: Severe Hematological Disorders

  • D46.1 (Refractory anemia with ring sideroblasts)
  • D47.4 (Osteomyelofibrosis)

HCC 47: Disorders of Immunity

  • D61.810 (Antineoplastic chemotherapy induced pancytopenia)
  • D70.1 (Agranulocytosis secondary to cancer chemotherapy)

HCC 48: Coagulation Defects and Other Specified Hematological Disorders

  • D68.0 (Von Willebrand’s disease)
  • D68.9 (Coagulation defect, unspecified)

Be Specific to Match Chronic Condition to Right HCC

Risk adjustment payment models rely on knowing the overall health of the patient to better assess risk, and therefore the care and expenses likely to be involved. Because of this, you should report  ICD-10-CM codes for all conditions that the provider considers in decision making. A popular acronym used in risk assessment is MEAT: Report conditions that the provider has Monitored, Evaluated, Assessed, or Treated during the reporting year.

For instance, an oncologist may take a patient’s diabetes or heart condition into account when deciding which medications are likely to produce the best results with the lowest risk for dangerous side effects. When reporting these other chronic conditions, be sure to choose the most specific code because that choice may affect HCC assignment and therefore the risk score.

A common example of how ICD-10-CM specificity affects HCC choice is that E11.9 (Type 2 diabetes mellitus without complications) maps to HCC 19, which is Diabetes without Complication. But ICD-10-CM codes for diabetes with complications map to higher-scoring HCC 17 for Diabetes with Acute Complications or HCC 18 for Diabetes with Chronic Complications. Consequently, capturing complications in the documentation and ICD-10-CM coding may translate to a more accurate risk score and higher future payments that reflect that risk.

Don’t Forget Z Codes for Health Status

Health status is another area that’s commonly overlooked for ICD-10-CM, but adequate reporting of status codes may translate to more accurate risk scores. The following are some HCCs with a couple of examples of the status ICD-10-CM codes they cross to that may be relevant for oncologists and hematologists.

HCC 22 Morbid Obesity

  • Z68.41 (Body mass index (BMI) 40.0-44.9, adult)
  • Z68.45 (Body mass index (BMI) 70 or greater, adult)

HCC 186 Major Organ Transplant or Replacement Status

  • Z94.81 (Bone marrow transplant status)
  • Z94.84 (Stem cells transplant status)

HCC 188 Artificial Openings for Feeding or Elimination

  • Z93.1 (Gastrostomy status)
  • Z93.59 (Other cystostomy status)

HCC 189 Amputation Status, Lower Limb/Amputation Complications

  • Z89.432 (Acquired absence of left foot)
  • Z89.511 (Acquired absence of right leg below knee)

What About You?

What’s your experience with HCCs? Have you had to change any of your ICD-10-CM documentation and coding habits?



Deborah works on a wide range of TCI SuperCoder projects, researching and writing about coding, as well as assisting with data updates and tool development for our online coding solutions. Since joining TCI in 2004, she’s covered the ins and outs of coding for radiology, cardiology, oncology and hematology, orthopedics, audiology, and more.

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