Robust Analytics and Predictive Analytics

CFO’s now play a key role in operational decisions and decision support.

A good BI analytics platform accepts multiple daily feeds for IP census data, all financial data from the financial IT platform, and data from any stand-alone sub-systems that have not been integrated with the IT financial platform.

A robust BI analytics system enables a CFO to customize KPI’s as desired, delivering a point-and-click capability to drill-down to as many layers as needed, including to the individual patient account level.

The series of dashboards typically includes all revenue drivers, service line and department data, payer data, patient demographics, and a series of dashboards that compare daily, weekly, monthly, quarterly, and mid-year periods versus the budget.

An effective BI platform tracks services not yet billed, services billed in the pipeline, payer remittance advice, reimbursement by payer, payer denials of claims and their status, a series of payer YTD comparatives vs. budget and the last fiscal year, any results from a Clinical Documentation Initiative (CDI), self-pay metrics, collection metrics, days of cash on-hand, and any other performance measurement of value to the CFO and Controller.

This is a lot of data, so an ability to drill-down quickly to key takeaways is a must.

Most CFO’s still receive some customized Excel reports from staff. This can be especially valuable when comparing the hospital’s retail performance in diagnostics and laboratory services, ED utilization, Same- Day Surgeries, etc. with competitors.

A strong BI analytics platform is a valuable tool by itself, however it becomes even more valuable when doing financial modeling.

Anything that can be quantified and is important can be part of a BI series of financial and operational dashboards. CFO’s need to be able to design their BI analytics dashboards per their needs, and the dashboards must produce clear takeaways. Otherwise, making sense of change is more problematic.

CFO’s need a powerful predictive analytics algorithm to measure the net revenue impact of potential change. Our financial modeling does this at budget time and in any season for anything we can quantify.

This enables you to weigh alternatives with confidence when considering what potential change will do. Here are a few examples:

  • A change in how you price services
  • Pursuing a new growth strategy
  • Recruiting physicians for select service lines
  • Adding more Retail services
  • Partnering with area employers for more Retail Services
  • Creating an ‘Upstream Medicine’ initiative
  • Implementing a new Behavior Health initiative using diversion peers in the ED
  • Building out the hospital digital platform to enhance patient engagement
  • Launching a new digital branding and marketing campaign

See what ‘Q’ can do for you!