The Challenge:
This case study might qualify for Super Hero status. The client brought us multiple systems with 17 different lists of physicians, including different identifiers, specialties, type of practice, status, and clinic locations. Many of the lists did not agree.
The Methods:
MIA took the data from all sources. We matched the data, ran it through a scoring system looking for commonality (the system dynamically “learns”) and created one central “correct” list (ETL Plus*).
- This list was then used by marketing, planning, (including MIA patient segmentation) and in house analytic groups (operation support) for reporting
- In the state of TX and surrounding states, having one single point of contact helped marketing outreach – and the web front end allows the company to override
- There is no front end that you see – the data is the final product (Custom App Development)
The Results:
Obviously, the clutter and waste are gone. So are the criticisms and complaints. The grudging sound of success; “We started talking about the need for this ten years ago.” Oh well, now we will go hang up our capes.