Taking the Risk Out of Risk Identification

As the healthcare industry continues its seismic shift from volume- to value-based care, primary care physicians have had to assume more responsibility for identifying and flagging patient risk.

More specifically, it’s on you to ensure that you’re not only capturing and reporting accurate risk-related data, but that you’re also identifying gaps in risk score accuracy—both to enable accurate payments and to improve patient care.

Risk adjustment: a brief overview

Risk adjustment is the process of setting payments for health plans to reflect the expected treatment costs of their members. Because of differences in health status and treatment needs, costs can vary widely among members.1

Under the Affordable Care Act, risk adjustment transfers funds from health plans with lower-risk members to plans with higher-risk members—to prevent plans and providers from selectively enrolling healthier members and provide adequate funding for those who treat patients with greater health needs.2

Retrospective, or concurrent, risk adjustment—the most commonly used method—uses claims data from a period of time to assess the differential risk for the same time period. Prospective risk adjustment uses historical claims to predict the future risk of a population.3

How are risk scores calculated?

Patient risk scores are calculated based on various risk adjustment models, including:

  • Hierarchical Condition Category (HCC)—mandated by the Centers for Medicare & Medicaid Services to identify patients with serious or chronic illness and assign a risk factor score
  • Clinical Risk Group (CRG)—a claims-based system that classifies individuals into mutually exclusive clinical categories
  • Chronic Illness and Disability Payment System (CDPS)—a diagnostic classification system used by Medicaid programs

Risk adjustment data sources include hospital inpatient and outpatient facilities and, most relevant to you, physician records.

What risk adjustment means for you and your practice

To ensure accurate payments and to identify and close gaps in risk score accuracy, proper coding and documentation in the medical record are essential. However, this can be both challenging and time-consuming. Here are a few tips that may help.

  • For retrospective risk reporting, don’t rely on claims data alone—combine it with EHR data, notes, and assessments for a more accurate picture of patient risk
  • Review your charts to find any common documentation errors—develop a targeted list of records to review by comparing EHR data to submitted claims
  • Integrate risk adjustment at the point of care—make sure patient records are current and accurate, with up-to-date medication and prescription information and comprehensive active problem lists.

Data analytics tools can also help you extract important diagnosis information located deep within unstructured or inaccessible patient data.3

Data Diagnostics® can help you identify risk score accuracy gaps

Data Diagnostics with Risk Score-Related reporting from Quest can help you identify patient risk score accuracy gaps (e.g., HCC, CRG, CDPS, etc.) and support accurate disease burden documentation of unaddressed or worsening conditions—to provide a more accurate understanding of patient-specific disease burden.

With Data Diagnostics Risk Score-Related reports, clinicians get patient-specific insights into both historically identified and predicated risk-adjusted diagnoses across a broad spectrum of applicable risk models. These reports also offer specific codes to help with proper documentation within medical records and/or EHR platforms.

Ensuring risk score accuracy can lead to more accurate payments, a healthier practice, and healthier patients.

1. Schone E, Brown RS. Risk adjustment: what is the current state of the art and how can it be improved? Robert Wood Johnson Foundation. July 2013. Available at www.rwjf.org/en/library/research/2013/07/risk-adjustment—what-is-the-current-state-of-the-art-and-how-c.html. Accessed April 13, 2017.
2. Health Payer Intelligence. Why value-based care reimbursement needs risk adjustment. 18 Jul 2016. Available at healthpayerintelligence.com/news/why-value-based-care-reimbursement-needs-risk adjustment. Accessed April 13, 2017.
3. Centers for Medicare & Medicaid Services. Risk adjustment methodology overview. 2012. Available at www.cms.gov/CCIIO/Resources/Presentations/Downloads/hie-risk-adjustment-methodology.pdf. Accessed April 13, 2017.