Coding for Improved Reimbursements

Many growing payment models are underscoring the importance of risk adjustment and offering compensation for practices able to make up for the extra costs associated with high-risk enrollees. Hierarchical Condition Category (HCC) coding is a risk-adjustment model originally designed to estimate future health care costs for patients.

Payers use HCC codes, along with demographic factors such as age and gender to assign patients a risk adjustment factor (RAF) score. Using algorithms, a patient’s RAF score can be calculated and used to predict costs. So a patient with multiple chronic conditions would have a higher RAF score and be expected to have higher health care costs.

Hierarchical condition categories are based on ICD-10 coding which have associated risk scores for the patients. Risk factors serve to scale payments to be reflective of the risks associated with the patient. For example, CMS uses the HCCs to risk-adjust the payments it makes to Medicare Advantage (MA) plans and for care provided via some demonstration.

For those in MIPS, risk adjustment could positively impact your overall cost measure score and impact your complex patient bonus. These coding improvements could also help with other payment models, such as Medicaid’s Chronic Illness and Disability System program and CMS Primary Care First, as most diagnoses have the same impact on risk and follow the same concepts. Commercial payer arrangements are also starting to use HCC codes for evaluation.

CORHIO’s Coding Services:

  • Practice education sessions for clinical, coding and billing staff (versioned for primary care and specialists as needed)
  • Chart reviews to look for coding opportunities to increase reimbursements
  • Helpful reference materials to use when coding
  • Follow-up sessions to address specific questions and review other advanced payment models your practice could be participating in

Coding Example (click to open)

 

Testimonials

“Our providers have nothing but good things to say about Lauren’s training. They tell me they can’t document what they don’t know – they are not coders – so providing the top codes to use in the problem list was really helpful for them. Our providers are seeing complex patients but their documentation does not always reflect that. This training really showed us how we can improve our documentation by using the MEAT method.”

Crystal Kechter, EHR Project Support Manager
San Luis Valley Health.

“I thought the training was excellent – it’s very helpful to know how to code more specifically. The handout is very helpful to refer to.”

Dr. Melissa Voutsalath
San Luis Valley Health.