Situation:
Medical billing is an important component of practices, ensuring smooth operation of the revenue cycle. Proper medical billing codes and all necessary supporting information are necessary to accurately charge health insurance providers and ensure accurate reimbursements. For example, healthcare providers must include certain information, such as medical cause for the procedure, to guarantee proper payment by insurers.

Problem:
Sometimes the healthcare provider doesn’t supply sufficient information about the performed procedure for billing coders. Resolving such issues requires requests for information (RFI) to which Physicians must respond. This process takes valuable time away from continued patient care. Furthermore, lacking certain information can substantially reduce payments by insurance companies, which ultimately increase the overall cost of healthcare.

Solution:
While ensuring protection of PHI and HIPAA compliance, our Director of Data Science lead the team that built a real-time natural language processing (NLP) algorithm to ingest and analyze dictated reports. This analysis identified key information required by medical coders relevant to the procedures described. If key details were omitted, based on for instance the exam modality (i.e., X-ray, MRI), the Physician was prompted to add specific details before sending off the report.

Outcome:
At the time this solution was implemented, the firm’s billing department processed roughly 300,000 dictations per month and were more than a month behind. Testing of the billing solution on submitted dictations was able to certify the completeness of information or identify what further information would be required by insurance providers for 30,000 dictations in 10 minutes.

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