The Challenge:

This joint venture client had approximately 14 different providers and a $2 million per year operating budget. They rarely shared information. Drill down a level and you discover that the client provided sliding fee scale care for approximately 85,000 unique individuals who accessed one or more of the providers. Yikes!

So how do you get data from all different providers, standardize it, crosswalk all individuals across all systems – dealing with cumulative data over 3 years and 150,000 unique individuals.

The Methods:

In order to obtain a single unified data set, MIA assembled and de-identified all of the data (ETL Plus*).

• The dataset was then sent to an actuarial firm who ran the unified data through their system and came up with what the cost would have been had Medicare reimbursed the cost of care.
• MIA was then able to build a budget using that data for the client as a whole (Planning Analytics).

The Results:

Client was able to:

• Send MIA back the cost weekly so they can see what the specific costs are for each diagnostic grouping
• Identify a subset of patients with the largest bills to create health protocols which lessen the cost of service.
• Note; this last outcome is extremely powerful. Once you can identify the “heavy users” you can create an action plan that works to lower utilization of the most valuable categories of assets – like trauma centers.