Health plans, globally have begun to realize the pompous value of Prospective risk adjustment programs, and deservedly so. Prospective risk adjustment programs authorize timely, effective interventions including the demonstration of probable gaps in care that support conditions coded to the highest degree of specificity. Paradoxically, retrospective risk adjustment programs limit the potency of code capture. A risk adjustment program that only consists of retrospective chart reviews is short-sighted and does not support the outcomes-driven, population health management which is now innate in most of the payment models.
A comprehensive retrospective risk adjustment solution technologies the traditional chart review process by shifting the focus from charts’ volume to precision targeting charts. The result is minor chart retrieval requests, which decrease provider erosion and increase the productivity of each review.
In prospective Risk adjustment, data is collected as the characteristics or circumstantial changes. In retrospective studies, individuals are sampled and information is gathered about their past.
Transitioning to the traditional Medicare Advantage to retrospective risk adjustment process, Millions of Medicare Advantage medical charts are retrieved and coded manually each year to generate a more complete picture of patient health status. Typical retrospective risk adjustment methods lacked the latest technology and tools to accurately identify medical charts that support unreported diagnosis codes.
RAAPID uses NLP Powered AI-Enabled Risk adjustment solution to optimize the retrospective risk adjustment process. It can be configured to automatically optimize HCC Risk Adjustment Coding & Chart Retrieval Solutions which do not support unreported diagnosis codes. RAAPID’s AI-enabled Risk adjustment solution maximize the productivity of the retrospective risk adjustment process by Prioritizing charts with precision to support unstructured diagnosis codes by Identifying the retrieval modality, and Predicting & prioritizing disease conditions possibly supported in the chart for coder review.
For years, the presiding approach for ensuring that patients’ diagnoses are accurately coded, involved retrospective risk adjustment—employing battalions of medical coders to scrub the medical chart after a patient encounter. Like all risk adjustment solutions, this approach requires documenting and reflecting the true disease burden of patients and populations, so that appropriate resources can be directed to them. Moreover, better coding ensures that providers are reimbursed based on the severity of illnesses which they are treating.
Which is the optimal approach to risk adjustment?
A technology-driven effective mix of all of the above is the answer – A triumphant risk adjustment strategy is heavily dependent on prospective interventions and programs but may need to add on some retrospective elements to address physicians’ needs. So that a deep dive insight on patient care is prioritized by the physicians eliminating “predictive” prescription.
Prospective programs, however being more operationally complex to deliver, are preferred because the ability to impact behavior, at the point of care, is powerful and has significant streaming effects, including higher overall value, impact on ROI, and lesser compliance risk.
Prospective risk adjustment can be the most unique method for obtaining a comprehensive insight into your member population. It also enables forecasting the cost of care for your Medicare Advantage, Medicaid, and Commercial lines of business.
The challenge:
Finding an authentic tech-driven prospective risk adjustment program for Risk-Score Accuracy Improvement that health plans, and physicians would collaborate to reduce costs and improve health, quality, and outcomes is crucial and critical too. It is essential to augment practices with dedicated clinical resources which can curate properly structured information to save physicians time by streamlining coding and mapping gaps in care.
Conclusion
As long as risk adjustment exists, there will be a requirement for retrospective chart review. Prospective programs succeed when they honor physicians’ time. In reality, small hindrances in coding and documentation practices can make a major difference to the accuracy of risk adjustment, while intensifying clinical value. A more effective approach requires the right amount of physician insight to support risk adjustment activity, and it effortlessly integrates that effort into existing workflows.
It’s not a cakewalk, but for plans willing to take on the risk, the ultimate results will be more than worth it.
