Enterprise Revenue Forecast Manager: 20-Week Implementation

Dean Dorton

Achieve Precise Forecasting with wRVU Data through the power of Microsoft Azure

Medical centers and integrated healthcare entities are pressured to accurately develop and manage provider forecasts. Using work relative value units (wRVU) is essential to success. The team at Dean Dorton has designed a tool that pulls the necessary data into one spot, in an accurate usable format, while comparing the overall organizational needs.

Harnessing the power of Microsoft Azure, the Dean Dorton Enterprise Revenue Forecast Manager is quick to deploy, cost-effective, and can be accessed on any trusted secure device. Historical information is imported into Azure Data Lakes and presented to department users via a trusted Microsoft Excel Online experience with a custom plug-in designed to manage the input and management of forecasting updates. Final updates are submitted back to Microsoft Azure SQL for further analysis and reporting as well as review by the Budget Team. Dashboarding is provided via Microsoft Power BI.

Implementation includes customizations to meet the specific needs of the organization, set up of the Azure environment within the organization's tenant, deployment of UAT and Production environments, and training, as well as follow-on support. Options for additional modules including ratio-based forecasting to associated technical components, payor mix, and more are also available.

Achieve Precise Forecasting with wRVU Data

  • Precision down to the individual provider and wRVU levels
  • Streamlined wRVU forecasting process for greater financial accuracy and budgeting through multiple variables
  • Accurate forecasting at the provider level with consistency across departments, practices, and locations


  • Defined historical baseline
  • Advanced provider modeling
  • Increased forecasting accuracy


  • Calculated based upon historical ratios
  • Adjusted based upon changes in provider forecast
  • Created provider and hospital forecasting consistency


  • Identified revenue expectations
  • Modeled for Payer changes
  • Analyzed contract negotiation