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Exploring the Risk Adjustment Continuum: The Importance of Prospective and Concurrent Condition Capture

Risk adjustment programs under the Affordable Care Act, Medicare, Medicaid, and Medicare Advantage evaluate patients’ risk scores based on a combination of condition and demographics data. Using claims, charts, eligibility, and other data, the United States Department of Health and Human Services (HHS) and the Centers for Medicare and Medicaid Services (CMS) calculate how much to pay insurers based on the health needs of their member population. The more accurately conditions are captured by providers and plans, the more accurately everyone gets paid to care for their members.

However, patients interact with healthcare providers before, during, and after a documented visit that may be used for risk adjustment. Can healthcare providers use that information to create a more holistic view of member risk?

By looking at data from across the healthcare continuum, payers can improve revenue accuracy while providers improve care quality, and unaccounted-for conditions can receive early attention, preventing them from becoming more serious problems later. Retrospective reviews can identify missed risk-adjusting conditions or costly coding errors that happen upstream, ensuring accurate risk capture.

Risk Adjustment Explained

Risk adjustment (RA) is a method used by CMS and HHS to adjust healthcare payments to reflect the demographics and ongoing needs of a patient population. The goal is to ensure that organizations who serve needier patients receive additional funds to cover their higher cost of care.

Risk adjustment is used in tandem with capitated payment models to prevent insurers from favoring healthier low-risk individuals over people with more health conditions (and higher healthcare costs).

To determine healthcare plan payments, CMS and HHS assign each insured or beneficiary a risk score called a Risk Adjustment Factor (RAF) based on demographics and health conditions. Someone over 65 with multiple chronic conditions would receive a higher risk score than a 30-year old with no health conditions.

Most CMS and HHS risk adjustment programs evaluate data after the fact, using risk scores from a base year to predict the following year’s costs. Although they call this model prospective, it uses data retroactively to anticipate future member health needs and spending.

While this approach to risk adjustment aligns with government payment models, it doesn’t make a ton of sense from a care delivery perspective. Moving risk capture upstream, where condition data can inform patient assessment and treatment decisions as well as diagnosis coding, can have benefits for both risk adjustment and care quality.

What Is Prospective Risk Adjustment?

A truly prospective risk adjustment method takes a proactive approach. It starts with developing a list of diagnosis gaps—a combination of previously known chronic conditions and suspected conditions missing supporting documentation. These diagnosis gaps are then distributed to providers to evaluate, prioritize, and close during patient encounters at the point of care. Clinical coders then ensure these conditions are properly reflected on claims, which are factored into member risk scores.

Prospective risk adjustment requires some data analytics prowess, but the benefits are worth it. Clinicians have more information at their disposal to make informed treatment decisions. For example, a 55-year-old may present with normal blood glucose levels today, but a review of escalating blood pressure and cholesterol over time could indicate a need for early intervention to prevent a future chronic condition—diabetes.

At the administrative level, prospective risk adjustment equates to more accurate, complete coding practices. As CMS updates requirements around its risk adjustment programs, it’s important to make timely updates to comply with regulations and coding guidelines.

The prospective approach also benefits payers. By identifying patients who may be at risk for chronic conditions, they can plan outreach to members who may benefit from health and wellness resources or care/utilization management programs.

What Is Concurrent Risk Adjustment?

Concurrent risk adjustment happens after the patient encounter but before claims processing. During this period, provider staff can review clinical documentation to ensure it meets HCC coding requirements and satisfies MEAT criteria:

  • Monitor for signs, symptoms, and disease progression and regression
  • Evaluate test results, medication effectiveness, and response to treatment
  • Assess and address test results and medical records; discuss with patients
  • Treat with medications, therapies and other modalities

Note: Some organizations use the “TAMPER” approach: Treatment-Assessment-Monitor/Medicare-Plan-Evaluate-Referral.

Concurrent risk adjustment also allows clinical staff to search for under-documented risk opportunities and ensure all codes and conditions are complete and accurate.

The Challenges of Retrospective Risk Adjustment

As healthcare systems move away from episodic, reactive care to a proactive, predictive model, risk adjustment should follow suit. By using only data from one point in time, several months after the encounter, plans and providers may overlook valuable insights.

Codes and conditions from 2019 alone don’t provide insight into a patient’s health in 2020 or 2021. This retrospective approach doesn’t work well for population health initiatives, which revolves around identifying patients at risk of chronic disease and providing early intervention.

Reviewing conditions and codes long after the fact also introduces more chance for human error. Reviewing a year’s worth of charts for thousands of patients to meet an annual sweep involves a mountain of HCC coding. Tight deadlines can contribute to costly mistakes that impact reimbursement, compliance, and patient care.

Incorporating prospective and concurrent risk adjustment into the program mix requires more attention from medical coders, but allows payers and providers to integrate coding into the existing workflow. This coding arrangement may help eliminate the mad rush before an annual deadline, improving accuracy and reducing retrospective chart retrieval abrasion and retrospective chart review cost. It also aligns with CMS’s regulatory shifts to reduce retrospective coding submissions and capture HCCs correctly on encounter claims.

In Summary

Risk adjustment programs involve a complex set of documentation, coding, and submission requirements. Moving to a more holistic risk adjustment approach—one that takes into account the entire care continuum—takes time, technology, and a focused team effort. However, the improvements in risk adjustment accuracy and quality of care can lead to noticeable bottom-line benefits.

Looking for a technology partner to support your risk adjustment program? Apixio can help.

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