Revenue Recognition | ASC-606 Compliant Automated Model
CLIENT PROFILE
With over 1,000,000 annual patient visits, over 180 physicians in multiple locations, this client obtained the largest wallet-share of retinal eye care in the North America but couldn't estimate monthly revenue accruals. Read how leveraging technology & specialized data architects gave auditors 20/20 clarity with exceptional findings.
BUSINESS CHALLENGE
Data Services played a small role of a larger horizontal financial integration of five physician's groups across multiple disciplines including: Cash to Accrual, Budget, Forecast, Consolidation, Revenue Recognition, Physicians Compensation, Net Working Capital.
In order to achieve ASC-606 compliance, the recently developed MSO required an encounter-level solution providing the most accurate revenue model available.
TECHNICAL CHALLENGE
The organization joined three different patient management systems (PMS) and over 15 million discrete encounter details with an average growth of 9% per month.
The team’s original model accumulated these transactions, with unique and complex rules for each practice, in iterative monthly spreadsheets. Due to the complexity of aggregating analysis over time and the monthly growth, the models quickly outpaced spreadsheet capabilities.
Once the final model was realized, it required 5-7 consultant, 8-10 business days each month to execute. This Excel-based model was extremely slow, prone to crashing, and side-lined FP&A specialist while their machines 'computed' for hours a day when computing the next month's revenue.
SOLUTION
Our healthcare revenue recognition expertise provided the knowledge necessary for the Data experts to fully assess both the mechanics of the original spreadsheet-based model as well as gaps and inefficiencies.
The results were unparalleled performance and accuracy allowing a close process in less than 4 hours, including data validation. This cross-functional effort leveraged FP&A knowledge and cloud-scale computing, achieving previously unachievable insights. Not only was the solution more efficient, but the ability to compute data at scale allowed for larger payer sample sizes generating more accurate payer rate baseline metrics.
Microsoft’s industry-leading Power BI analysis and reporting tools allowed analyst to develop complex revenue analyses with drag and drop simplicity, enabling a future self-service user experience.