Tag: Eric McGuire

Unlocking Optimized HCC Documentation and Coding

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Eric McGuire

By Eric McGuire, senior vice president, Medical Coding and CDI Service Lines and Corporate Strategy, AGS Health.

Traditional fee-for-service reimbursements are falling by the wayside as healthcare continues its transition toward value-based reimbursement models. This is evidenced by data from the Health Care Payment & Learning Action Network (LAN), which shows more than half of healthcare payments in 2022 were made under value-based care models. Additionally, nearly 75% of health plan leaders surveyed by LAN believe value-based care model activity will continue to rise.

Integral to this transition – which requires providers to better manage patient costs based on a clear, concise, and comprehensive picture of patients’ health and medical conditions – are Hierarchical Condition Category (HCC) codes. Used by the Centers for Medicare and Medicaid Services (CMS) and commercial payers to forecast medical costs for patients with more complex healthcare needs, the HCC risk adjustment model measures relative risk due to health status to determine reimbursement levels. The more complex the patient’s medical needs, the higher the provider’s payment.

In fact, HCCs are the preferred method of risk adjustment for the Medicare population, which includes nearly 60 million people on both Part A and Part B, CMS reports. As such, accurate HCC management is critical for appropriate reimbursement of the care provided to Medicare patients and beneficiaries.

Accuracy is Key

The highly complex HCC model includes approximately 10,000 diagnosis codes that map to HCC codes and 189 different HCC categories with 87 CMS-HCCs, each of which represents diagnoses with similar clinical complexity and expected annual costs of care. Any error can significantly impact reimbursements, which under HCC is determined by mapping a patient’s diagnoses to these codes to create a Risk Adjustment Factor (RAF) score.

The RAF score represents the estimated cost of caring for that patient based on their disease burden and demographic information. It is then multiplied by a base rate to set the provider’s per-member-per-month (PMPM) reimbursement amount. The sicker the patient, the higher the RAF score and, subsequently, the provider’s reimbursement.

Each year, CMS publishes a list of diagnosis codes and corresponding HCC category. Hierarchies (or ‘Families’ of categories) are listed among related condition categories, which set values based on the severity of illnesses. Improperly documenting HCC codes, or failing to document the highest appropriate specificity, results in lower reimbursement rates. For example, HCC 19 (diabetes with no complications) might pay an $894.40 premium bonus compared to a bonus of $1,273.60 for diabetes with ESRD, which requires two HCC codes mapping to 18 and 136.

Conversely, properly documenting HCCs at the highest appropriate specificity can boost reimbursements. For example, if CMS has set a $1,000 PMPM for a patient with an RAF of 2.234 who has diabetes with complications reimbursement would be just $673 per month if the condition is not coded. However, if the case was properly coded as E11.9 Type 2 diabetes mellitus without complications under HCC19 Diabetes without complications, the RAF increases to 2.366, resulting in reimbursement of $1,062 per month. If properly coded as E11.41 Type 2 diabetes mellitus w/diabetic mononeuropathy under HCC18 Diabetes w/ chronic complications, the RAF increases to 2.513 for a reimbursement of $1,312.5.

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