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Risk Adjustment and Value-Based Care

America’s healthcare system is experiencing a paradigm shift, driven by the need for quality care instead of quantity of care. Providers are encouraged to provide a better, higher standard of care instead of turning a practice into a factory, churning out patients at high volume. As government and private payers work to shift from fee-for-service to a value-based care model another, important and often overlooked, aspect is risk adjustment. Risk adjustment factors into most of the Pay-for-Performance (P4P) quality programs but also plays a role in Value Based Care (VBC) in general.

Risk adjustment is a statistical categorization process that considers the underlying health status and health spending of the enrollees in an insurance plan when looking at their health care outcomes or healthcare costs1 and diagnosis profile. Risk Adjustment is critical to ensuring patient health complexity is fully captured and resources are appropriately allocated to treat and manage their care needs. Healthier patients are categorized with a lower risk score than sick patients. By analyzing a practice’s patient population’s wellness as a whole, the practice then has an overall risk factor which public and private payers use to calculate reimbursements. Additionally, for pay-for-performance models, bonus points can be allocated depending on how complex the state of your patient population’s health is. The more complex, the bigger the bonus.

This incentivizing also carries with it some dubious ethics, how much is a complex patient worth to third party payers?  Complex and multiple diagnoses cost more to treat and therefore it makes sense that the practice should receive a higher monetary reimbursement for that patient, but the question becomes, how much more? It is difficult to compare cancer to diabetes or depression, never mind comorbidities. The differences in diagnoses do not alter the fact that diseases may carry the same level of complexity to treat but are they the same in cost?

Risk adjustment can also change the ways practices choose their patients. Risk adjustment can backfire leading to patient dumping in which practices/clinicians offload certain patients due to the belief that more resources will be expended caring for that patient than recouped from third party payers.

As shared risk models and programs expand, more practices will have to adjust by factoring in risk and examining the current case load. Accurately identifying high and low-risk patients is key to making sure that your practice will be correctly reimbursed for the patient care expenditures incurred. This is easier said than done, however as there are many difficulties when it comes to calculating and joining in shared-risk and shared-savings programs.

ReportingMD can help to mitigate the challenges many practices struggle with, such EHR or claims data accessibility limitations and/or systems constraints that reduce transparency of patient complexity data and analysis. ReportingMD has tools and services that draw the focus to understanding how to better document the patient’s true complexity for improvement patient care and more accurate reimbursements.