Big Data Mining Speeds Claims Payments

Sean Riesterer, director of revenue cycle and reimbursement for Silverton (Ore.) Health, knew he had to juice the time between rendering of service and submission of the bill, but he didn’t know how until he began comparing his organization with more than 1,000 others through a claims database maintained by RelayHealth. One in five of the hospital’s claims were taking between five and 10 weeks to get submitted, and the overall average was 30 days—too long for the financial health of the 48-bed organization.

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Comments (2)
10,000 claims/month is NOT big data. It is not even a lot of data. Why throw buzz words around that you don't understand? "Big Data" refers to millions and billions of records, such as collected in web traffic or machine-generated data. And it refers especially to the unstructured data not in a relational database, and the storage and retrieval methods to analyze that data. This is not even a data mining project. This is a data comparison project. It's nice to have a lot of reference data, but what was the predictive power of the mining model? Oh, there was none.
Posted by Matt S | Tuesday, March 25 2014 at 2:53PM ET
Angry much? The question asked how providers were using data outside local capabilities to manage - fitting the definition McKinnsey Global Institute used when coining "big data." Within RelayHealth's universe, are over 2 billion transactions annually ($1 trillion) which also fits within your stated size. So completing the original context, if a small provider generates 10,000 claims/month, we're talking 'big data' when compiling, comparing & analyzing encounter/claims/quality/experiential et al. data for 20% of claims/reporting nationally. All the best to you.
Posted by Sean R | Tuesday, April 01 2014 at 8:32PM ET
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