Medical records have come a long way since the start of Meaningful Use. We’ve seen great leaps forward for some institutions for intra-organization communication. However, inter-institution and institution-agency communication still needs much improvement. We hope to see a common technical standard for recognizing and approving medical coding decisions and payments in the future.
Both hospitals and insurance agencies need a method to identify billing codes at the visit level without subjective and manual review of all patient visit notes. We have found that, on average, a one year medical history of 100 Medicare patients results in 14,000 pages of records. Manual inspection of every page to assign billing codes to each visit is a costly and time consuming practice.
We have been able to identify patients with specific conditions using knowledge from medical coders and the power of full-text search engines. We take complete medical records, in any visual format (we haven’t assessed audio yet!) and apply Big Data processing coupled with powerful search logic. This enables us to take subjective medical coder knowledge to apply an objective iQScore.
Our iQScore is an objective value assigned to subjective data from a visit or complete medical history. Using the iQScore, we identify medical risk in patients, and populations of patients. We have been able to greatly influence the risk-based payment schemes of organizations using this method.
We are excited to apply our technology solutions to healthcare to optimize payments to hospitals. We hope to have an accepted and technical communication process between agencies in the future. Until then, our raw-search Big Data solution will continue to make huge impacts for risk-based payments.