Capture Better Data
Under the traditional fee for service program, encounter data chiefly supported the claims reimbursement process. Providers were paid based on CPT codes, so long as there was a diagnosis code that made the office visit, procedure or test medically necessary. The life cycle of encounter data was typically no more than 60 days from when the patient was seen, to the claim was filed and ultimately paid (even if it was initially denied and resubmitted).
Coded encounter data, particularly diagnosis codes, are much more important and have a longer life cycle as reimbursement shifts from a volume-centric model to value based reimbursement.
Measuring and paying for quality and cost effectiveness sounds like common sense to most outside of the industry, however industry veterans are quickly point out that often the most skilled physicians take care of the sickest patients. These patients have complex chronic diseases and comorbidities that make their expected outcomes worse than the average patient. These patients also consume a disproportionate share of healthcare dollars, costing the healthcare thousands of dollars more each year than the average patient. To equitably measure quality outcomes and cost effectiveness these measures would have to be risk adjusted to factor patient acuity into quality and cost scores.
Practices must capture better data to successfully transition to Value Based Reimbursement
The preferred risk adjusted methodology is HCC coding, which users patient demographic and diagnosis information to project patient acuity and future healthcare expenses. HCC coding, reviews all diagnosis for a patient in the last 12 months and assigns a weight to each of these conditions. This means that encounter data is not only used for proper fee for service reimbursement, but is used for risk adjusted quality and cost measures that impact MIPS performance and fee for service positive or negative adjustment for years into the future.
Medicare and commercial payers are already collecting and calculating these risk scores today based on claims data submitted by physicians. Only 18% of physician practices today have risk adjusted contracts with commercial payers, however that number is expected to increase significantly over the next 3-5 years. Understanding risk adjustment and having access to the data is a powerful tool when negotiating contracts with commercial insurance companies and helps level the playing field.
White Plume helps physician practices analyze, understand and optimize HCC coding and the importance of documenting and coding comorbidities. We can help your practice capture better data to support the transition to value based reimbursement under MIPS.