Health information is massive with valuable numeric and textual data, and because of the increased data velocity in today’s health care environment, a health plan’s data is replaced by new data within three years. But industry experts say 80 percent of health plan data remains trapped in unstructured text, such as clinical notes, electronic medical records and call center logs.
Text mining transforms unstructured data into a format that opens it to analysis. Medical reports, e-mails and research articles then can be used just like other health care data, such as age, gender, blood pressure and cholesterol levels, to perform data mining, clustering, neural networks, decision trees and regression analysis on rich data. Imagine how robust an investigation could become if a patient’s symptoms in clinical notes differed from the billing submitted to the payer. Imagine the integrity issues uncovered if the patient appeals a non-covered service, but after the appeal is denied, the doctor re-files the claim using the same date of service but different treatments.
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