2.5M provider records, scored for lower cost.
A payer’s provider analytics team gained a repeatable scoring method, built around its own rules. It supports a lower total cost of care.
Challenge
The questions
- 01Which measures and comparison groups should inform the score?
- 02Where was the underlying information sufficient to support a useful result?
- 03How could the scoring logic become a repeatable operating capability?
The client needed a provider scoring algorithm that could support its approach to managing total cost of care. The output had to be usable in business decisions. The team also had to see how each score was produced.
Provider information and performance measures needed to be connected consistently across a large population. The client also needed to distinguish usable evidence from missing or insufficient information before relying on the scores.
Scale made that distinction important. A missing score needed to remain distinguishable from a low score, and comparisons needed an appropriate basis.
Solution
Flume built a provider scoring algorithm around the client’s objectives and business rules, scoring 2.5 million provider records.
The implementation brought the required provider information, analytical definitions, and scoring logic into a repeatable process. ContextBase retained the relationships and decisions behind the method so the resulting scores could be explained, reviewed, and updated.
Impact
2.5M
Provider records scored
The figure describes the reach of the scoring engine. Its effect on medical cost is evaluated separately.
- The client has an operating capability for provider analysis and decision support.
- Changes to definitions or decision rules are weighed against the existing method, with a clear view of which results they affect.
- Where the method is useful, and where more information or review is needed, stays visible.
Start with the question your team keeps waiting on.
See how ContextBase answers it on your own claims, eligibility, and contract data.