Product Line Budgeting (PLB)

The PLB module takes healthcare budgeting to the next level by using patient-level data to drive your forecasting and modeling. This provides more accurate budgets by modeling the impact of volumes, revenues, staffing, and expenses for nursing and ancillary departments based on actual relationships of clinical case type. It also links the strategic planning assumptions in a very tangible way to the operating budget. The PLB solution enables integration of your strategic planning with your operating budget, and simultaneously integrates productivity standards, rate modeling, net revenue modeling, and utilization analysis.

The PLB process workflow:

1. Load historical General Ledger, Payroll and Patient Data (typically 2 years of data).  This will provide a baseline from which to make assumptions going forward. 
2. Define your products based on DRG, ICD-9, payer, physicians, or any other field you have populated. Based on your definitions, the system will create a utilization profile down to the CDM level for each product defined.
3. Modify any of the profiles to reflect changes going forward. For example, you can model changes in length of stay, reduce the utilization across all products for a high cost drug, etc. You may also create new profiles from scratch, or copy existing profiles and modify them to reflect new services to be offered. 
4. Forecast monthly product cases for up to 10 years. This will drive departmental statistics, revenues, variable expenses, and net revenues for the enterprise. The system will flex monthly to help analyze utilization, revenue, labor and expense variances.
   

    

   

• Models up to 10 years forward
• Creates multiple models
• Models new programs
• “What-ifs” on case volumes, utilization changes, LOS changes, rate changes and payer method/mix changes
• Uses actual historical patient data to drive variable relationships for stats, revenues, expenses and net revenues
• Integrates job class staffing ratios
• Flexes the budget based on actual cases by product to analyze utilization variances
• Analyzes variance by product, DRG, physician, payer
• Models net revenues by product by payer using actual payments as basis
• Models rate structures at CDM level