What is Data Accuracy

Data Accuracy Definition

Data Accuracy is the non-negotiable requirement for regulatory compliance and patient safety. For C-level Executives, inaccurate data is a high-cost liability; it leads to misdirected payments, "ghost networks," and potential legal action under the No Surprises Act. Accuracy goes beyond just having the "right" name; it means the provider is at the stated location, on the correct plan, and maintaining an active license. Operationally, maintaining accuracy is a "decay" problem—provider data changes at a rate of roughly 2% to 3% per month. Without automated verification loops, a directory can become 30% inaccurate within a single year. Strategically, accuracy is built by cross-referencing multiple primary sources (NPPES, CAQH, State Boards) to ensure that the data serving the member directory is the same data used by the claims engine.

FAQs

How is Data Accuracy measured in a provider network?

It is typically measured through "Accuracy Scores" derived from secret shopper surveys or by comparing internal records against external primary sources (PSV).

What is the cost of "Bad Data" in healthcare?

The industry loses billions annually due to claim reworks, manual directory corrections, and federal fines for non-compliance with transparency laws.

Can data be "valid" but not "accurate"?

Yes. A phone number can be in the valid format (10 digits), but if it rings a disconnected line or the wrong office, it is "valid" but "inaccurate."