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Accurately reporting risk scores helps a health care organization receive proper credit for the value of care it’s providing.

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Is Risk Adjustment a Detriment to Your Health Care Organization?

  • 7/19/2017

Risk adjustment is an actuarial tool that allows health care organizations that care for sicker populations to have their costs and outcomes compared more accurately to others that serve healthier populations. Accurate reporting of hierarchical condition categories (HCC) risk scores ensures that certain cost and outcome metrics are not unfavorably skewed, and that an organization receives proper credit for the value of the care it is providing.

Is your health care organization’s risk score accurate?

Risk adjustment became a prominent concern for Medicare Advantage health plans in the early 2000s, but is becoming increasingly significant for providers in the migration toward pay-for-value. Whether your organization is a hospital, a physician practice, or an integrated health system, accurate risk adjustment is necessary to be paid correctly under the Centers for Medicare and Medicaid Services (CMS) value-based purchasing (VBP) and the Medicare Access and CHIP Reauthorization Act (MACRA). More importantly, accurate risk adjustment is critical for success with new advanced payment models (APMs) designed to reward value over volume.

Population health and service utilization initiatives can take years to generate meaningful cost savings, and they also impact top-line revenue. Addressing inaccurate risk adjustment can move cost and outcome metrics into a more favorable zone without impacting the bottom line. In addition, it can contribute to quality improvement by providing better data to accurately identify care management opportunities and gaps in care. Waiting to master risk adjustment could leave your organization at a competitive disadvantage.

How risk adjustment works

HCC is a method of risk adjustment that uses diagnosis codes submitted on claims, along with demographic variables, to account for differing prevalence of health risk factors in patient populations. An HCC risk score is calculated for each patient, aggregated for all patients in the population, and then used to normalize cost and outcome metrics for that population.

Accurate risk adjustment relies on cumulative documentation and coding of chronic conditions for each patient during an annual measurement period. The score resets to zero every year. Capturing a chronic condition for risk adjustment in compliance with coding guidelines requires that the provider address or treat the condition during an encounter, or consider it in their medical decision making, and document it appropriately. This aligns with high quality care that assesses the management of chronic conditions at least once annually and considers the whole patient in delivering the most appropriate care.

Assessing HCC risk score accuracy

Chronic conditions managed in the outpatient setting are most vulnerable to inaccurate reporting, because in the fee-for-service model, professional and outpatient services have historically required only a primary diagnosis for payment. The most effective method of assessing complete reporting of chronic conditions in the outpatient setting combines a review of CMS quality and resource use reports (QRUR) for a physician practice, data analytics, and chart reviews.

QRUR reports

The QRUR reports that physician practices already receive from CMS can be analyzed for signs of an inaccurate HCC risk score. If the report characterizes a practice as high cost, but is not substantiated by other data, it might signal inaccurate HCC risk scores.

Data analytics

Analysis of claims and electronic medical record (EMR) data can provide additional insight.

  • A low average number of ICD-10 codes per Level 3, 4, and 5 encounters combined with large volume of higher level encounters with only one diagnosis code may indicate inaccuracy.
  • A misalignment between the prevalence of chronic disease conditions in your population claims data and your experience with the population you serve, (as well as national and regional benchmarks) may signify inaccuracy.
  • A low re-capture rate of chronic conditions from year to year for “same-store” patients in your population claims data may indicate that persistent chronic conditions are not being consistently coded from year to year.
  • Discrepancies between chronic conditions captured in your population claims data and clinical EMR data and problem lists may reveal chronic conditions documented in the medical record but not reflected in claims data.

Chart review

Targeted documentation and coding reviews in areas highlighted by the data analytics can reveal specific areas that require attention.

Improving and managing HCC risk score accuracy

Accurate risk adjustment is not a one-time improvement effort — it is a continuous business requirement for which infrastructure, competencies, and management processes must be developed. A program for managing HCC risk score often begins in coding, but it also incorporates information at the point of care and an ongoing program of feedback for providers.


Training coders to code claims for HCC risk adjustment is a step in the right direction, but is usually not sufficient to drive the required level of accuracy. In some organizations, a large percentage of claims are released to the payer without review by a coder. For claims that are reviewed, coders can only add chronic condition codes that were appropriately documented. At the same time, they must also remove any codes that are not supported by the documentation. Consequently, the level of accuracy that is achievable is limited by providers’ existing documentation practices.

Prompts at the point of care

Complete coding of patient health status relies on a provider’s attention to chronic conditions during the encounter, as well as complete clinical documentation. Delivering accurate and relevant information to the provider at the point of care about the possible presence of chronic conditions and the status of capture during the current measurement period is a powerful tool. The information may also highlight gaps in care, which can then be addressed for improved management of chronic conditions. Vendors are providing more solutions to present such information within the EHR and the solutions are increasing in sophistication.

Provider engagement

To effectively use this information requires that providers think about the whole patient, not just the specific encounter and the condition they are treating. Historically, providers have not been trained to approach patient care or documentation in this way. It takes time to integrate this mind shift into your provider culture. Therefore, it is imperative that clinical leadership begin without delay to integrate the concept of accurate coding for risk adjustment with messages about quality and improving care delivery.

Ongoing clinical documentation improvement

Sustained improvements in the accuracy of HCC scores requires ongoing analytics, chart reviews, and documentation feedback to providers to promote accurate clinical documentation, particularly in the outpatient setting. The most effective outpatient clinical documentation improvement (CDI) programs use clinician champions partnered with coding professionals to deliver specialty-specific and provider-centric documentation feedback that goes beyond coding guidelines and aligns with the situations that providers encounter every day.

How we can help

CliftonLarsonAllen (CLA) can help assess your organization’s exposure to inaccurate HCC risk scores and risk adjustment by analyzing your QRUR reports, claims data, and clinical documentation to identify specific opportunities for improvement. Our team of revenue cycle, coding, and operations professionals can help support clinical leaders with data to promote provider engagement and plan and implement an outpatient CDI program. Additionally, our team can help deploy tools to improve risk score accuracy in a way that also supports care-redesign initiatives to improve the management of chronic conditions.