HCCs: An Operational Perspective – HIM Scene

Posted on August 8, 2018 I Written By

The following is a guest blog post by Cathy Brownfield, MSHI, RHIA, CCS, Chief Operating Officer, TrustHCS.

Hierarchical Condition Categories (HCCs) were mandated by the Centers for Medicare and Medicaid Services (CMS) in 1997. In 2003 HCCs were selected as a risk adjustment model to be used to determine reimbursement for Medicare Advantage Plans.  They describe chronic condition diagnoses for patients and are determined from other codes assigned during physician encounters—including ICD-10 codes, CPT codes and medication codes.

The HCC framework is progressively being applied to numerous healthcare reimbursement reform initiatives. As the shift from volume to value advances, so does the importance of accurate HCC coding. This month’s blog explains the correlation between HCC coding and value- based reimbursement.

Two HCC models prevail

There are two HCC models in use by the federal government: CMS-HCC and HHS-HCC. Both models employ a risk adjustment score to predict future healthcare costs for plan enrollees. They operate within a hierarchical structure in which the more complex diagnoses absorb and incorporate less complex, chronic conditions.

The CMS-HCC model addresses a predominantly elderly population (65 years and over) and includes more than 9,000 ICD-10 codes that map to 79 HCC codes; these numbers do change and will increase slightly in FY 2019.

The Department of Health and Human Services (HSS) maintains the HHS-HCC model, which addresses commercial payer populations and covers all ages. This system incorporates CPT and medication codes and is currently comprised of 128 HCC codes.

Relationship to risk adjusted payment programs

The following are some of the risk adjusted payment programs currently using HCCs to determine reimbursement:

  • MA – Medicare Advantage Plan
  • MSSP – Medicare Shared Savings Program (ACO)
  • CPC+ – Comprehensive Primary Care Plus (Medical Home Model)
  • Commercial – Mainly the ACA

Each of the models primarily use ICD-10 codes taken from claims data to identify individuals with serious or chronic illnesses and assign a risk factor score to each enrollee based upon a combination of the individual’s health conditions and demographic details. Each HCC has a risk factor, an individual can have multiple HCC’s and those factors add up to their overall risk adjustment factor.

According to the CMS website, “risk adjustment allows CMS to pay plans for the risk of the beneficiaries they enroll, instead of an average amount for Medicare beneficiaries. By risk adjusting plan payments, CMS is able to make appropriate and accurate payments for enrollees with differences in expected costs. Risk adjustment is used to adjust bidding and payment based on the health status and demographic characteristics of an enrollee. Risk scores measure individual beneficiaries’ relative risk and risk scores are used to adjust payments for each beneficiary’s expected expenditures. By risk adjusting plan bids, CMS is able to use standardized bids as base payments to plans.”

How to operationalize accurate HCC coding

The risk-adjustment data for these programs is based on active diagnoses. In order to ensure the information is accurate, providers must conduct face-to-face encounters with their patients and all pertinent diagnoses must be documented in the medical record on an annual basis. Accurate documentation and coding is paramount to proper reimbursement under risk adjusted programs that use HCCs.  Beyond accurate HCC coding, it is important for HIM professionals to be aware of CMS reporting and data collection methodologies when operationalizing HCCs.

Reporting considerations to know

In 2012, CMS began transitioning the Medicare Advantage Organizations (MAOs) data collection method from its original format to an Encounter Data Payment System (EDS). The data collected under the EDS is unfiltered and more detailed than EDS’s predecessor, Risk Adjustment Payment System (RAPS). While CMS has gone back and forth on which algorithm to use, a blend of 85 percent RAPS and 15 percent EDS scores is currently in place for 2018.

Data is submitted directly to CMS where filtering logic is applied to extract the valid diagnosis codes from the data. The codes are then used in the risk score calculation process. With this process, MAOs must verify the completeness and accuracy of the data submitted to CMS to ensure that all appropriate diagnosis codes have been accepted for risk adjustment by CMS.

The RAPS/EDS blend will return to a 75/25 split in 2019. Additionally, CMS is proposing to calculate the EDS risk scores amended with RAPS inpatient diagnoses. Other 2019 changes are listed below.

2019 CMS-HCC Model Changes

  • Behavioral Health Conditions
    • HCC 55 Drug/Alcohol Dependence: Add opioid (and other substances) overdose ICD-10 diagnosis codes to HCC 55
    • Add HCC 56 Drug Abuse, Uncomplicated, Excluding Cannabis, includes opioid dependence diagnoses (among other narcotics)
  • Mental Health and Substance Abuse Disorders
    • Add HCC 59 Reactive and Unspecified Psychosis
    • Add HCC 60 Personality Disorders
  • Add HCC 138, Chronic Kidney Disease Stage 3 (Moderate Only)

Role of HIM and where to learn more about HCCs

In the new frontier of value-based payment, HIM is the purveyor of accurate coding and HCC assignment for organizations and providers. Savvy HIM leaders ensure they have the most up-to-date information by monitoring the following websites and information sources:

About Cathy Brownfield
Cathy Brownfield is the Chief Operating Officer of TrustHCS. She holds over 17 years of operations, auditing and coding experience. Prior to TrustHCS, Cathy served as the Operations Director for HealthPort’s Coding Operations division overseeing scheduling, billing, and quality assurance efforts.

Cathy holds her Master of Science in Health Informatics from Arkansas Tech University. She received her Bachelor of Science in Health Information Management from the same university. Cathy is a Registered Health Information Administrator and a Certified Coding Specialist. As a member of the American Health Information Management Association she volunteers on the Coding Community Council and also the PPE work group.