The client team wanted to create a best-in-class data platform to support insights, forecasting, targeting, next generation data modeling. We supported them in developing a data platform that integrates two major claims vendors, lab data, with monthly maintenance.
Putnam’s prior work identified an idealized data platform that included two major claims datasets (Komodo and Symphony), which was a 1st in the US at the time. This framework leveraged tokenization technology and allowed for the addition of other datasets (e.g. labs, HUB, EHR, hospital).
We designed sensitivity analyses to de-duplicate common patients/claims, creating enriched claims where possible that are better than either dataset alone. We also leveraged the platform to combine two lab data sources into the data platform, linked to the claims data.
The development of the final data platform resulted in ~30% improved unique key patient coverage specific vs. either original claims dataset alone. The underlying details around each patient were also enhanced (i.e., more claims per patient, more diagnosed, and treated patients).
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