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UASI in JAHIMA: “Documentation and Coding Practices for Risk Adjustment and Hierarchical Condition Categories”

UASI’s health information management (HIM) experts continue to set the pace in this fast-evolving field.

Our vice president of HIM consulting services, Mary Stanfill, MBI, RHIA, CCS, CCS-P, FAHIMA, co-authored a paper — published in the June 2018 issue of the peer-reviewed Journal of the American Health Information Management Association (JAHIMA) — that explored the concept of risk adjustment (RA).

What Is Risk Adjustment?

RA is a statistical analysis method by which payers attempt to anticipate utilization (and, consequently, the costs generated to a plan) that a beneficiary will likely exhibit over a given future period, typically a year.

The methods used by organizations — be they the Centers for Medicare & Medicaid Services (CMS), the Department of Health and Human Services (HHS), or private carriers — may vary, but all rely to some degree on analysis of assigned hierarchical condition categories (HCCs).

“To identify the conditions that predict future healthcare costs, HCC models first organize diseases and conditions into body systems or disease processes, called diagnostic groups,” Stanfill and her co-authors explained.

“Conditions in each diagnostic group are further organized into condition categories,” they wrote. “ICD-10-CM diagnosis codes are ranked into categories that represent conditions with similar cost patterns.”

Risk Adjustment Variations for Medicare Advantage vs. Marketplace Managed Care Beneficiaries

Because CMS’s RA process focuses on beneficiaries belonging to Medicare Advantage (Part C) plans (which include only aged, blind, or disabled individuals), it’s primarily concerned with predicting utilization for chronic disease management.

Thus, it doesn’t attempt to predict acute care or prescription costs.

CMS’s RA method uses costs incurred in a base calendar year to attempt to predict costs that will be incurred in the next year. So, a Medicare Advantage beneficiary’s utilization for 2018 would be used to predict his or her costs in 2019.

HHS’s RA method, on the other hand, is used to predict utilization for the entire population of members belonging to commercially managed marketplace (Affordable Care Act, or ACA) managed care plans (HMOs or PPOs).

That risk pool includes many younger, healthier people, so HHS’s risk adjustment models do attempt to predict ongoing costs associated with acute care and prescription medications. HHS consequently collects information on an ongoing, concurrent basis to predict costs in the same year.

Naturally, these somewhat divergent analysis goals result in differences in the HCC captures those agencies rely on for risk adjustment.

Tailor Provider Education to Account for Differing HCC Capture Goals

Because CMS’s risk adjustment model is prospective, providers need to understand when and how to capture HCCs that support the model’s aims, and to understand how those differ from HHS’s risk adjustment process.

For CMS’s process, “individual HCCs are only valid for one year,” the authors noted. Thus, “regardless of the HCC’s fundamental chronicity, on January 1 the patient’s HCC listing is blank.”

“A patient with diabetes with complications would need to have a face-to-face encounter with a provider where diabetes is discussed and documented for the appropriate HCC to be reported in the new base year,” they wrote.

“With such an emphasis on yearly code capture, provider education becomes a higher priority early in the year to prevent the loss of HCC diagnoses,” Stanfill and her co-authors pointed out.

“Providers should be educated to understand that while chronic conditions continually impact the patient’s health status, they are not implied under the HCC models,” they suggested. “Risk adjustment coding professionals should identify the documentation gaps and guide providers on how to eliminate the gaps.”

Best Practices to Support HCC Capture and Assist the Coding Team

The best policy, Stanfill and her co-authors stated, would be to encourage providers to thoroughly document all diagnoses — acute and chronic conditions alike — in every patient encounter, and to make sure that the corresponding codes are captured in the patient’s electronic health record (EHR).

EHR limitations may present a challenge to providers when treating patients who have many concurrent and/or chronic conditions.

For example, the authors wrote, if an organization’s EHR platform does not include enough diagnostic code fields to account for all of a patient’s conditions, the hospital system or provider group should work with its vendor to redesign the platform to allow more thorough HCC capture.

Click here to download the full practice brief, in which you’ll find these best practices and more explained.

Or, go here to read an abridged version of Stanfill, et al.’s article in JAHIMA‘s online version.

Need Help Setting Up Provider Education About HCC Capture?

We specialize in it. UASI Solutions is an industry leader in health information management, offering provider education resources, consulting services, chart auditing and third-party coding services that could help you improve your HCC capture rate and protect your revenue stream from costly, avoidable penalties.

Contact our team today. Let’s start your hospital, health system, or physician practice’s journey toward a more effective, efficient and profitable coding process.