How it Works
The Anomaly Reports system scans your EMR records to identify billing and operational errors and generates reports. You and your staff will receive daily, weekly, and monthly reports based on your office schedule.
Each report has per-incident actionable information to allow efficient correction of errors.
To confirm that your staff has completed the required no-show follow-ups and billing corrections, weekly and monthly reports allow you to recheck whether previously flagged errors have been corrected.
Key Takeaways
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Your staff makes errors in EMR entries that go unnoticed (hard to find)
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Undocumented Encounters equals lost revenue (no records, no bill, no income)
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Missed documentation on Encounters leads to poor charting and liability
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Easy to miss no-show appointments leads to failure to engage for new appointments
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Daily corrections to operational errors equals difference between profitability and loss
Without systematic accountability, you cannot identify, quantify, or correct errors.
Our AI technology finds and helps you gain back lost revenue.
Operational Anomalies
Incorrectly Entered Appointments are very hard to find in the EMR. Your billing service can ONLY bill for Encounters that have been entered. Missed opportunities to recapture no-show patients are a large potential loss of revenue for your practice.
Current Reality
Operational errors inevitably occur in medical practices with high volumes of patients. Manual processes, inconsistent training, and staff changes all contribute to errors. Operational errors cost you money and increase liability.
Errors include unbilled visits, missed no-shows, uncharted visits, appointments not completed, and many other issues that impact your revenue.
Systematically fixing hard-to-find operational errors can be the difference between a profitable practice and one that loses money. AI technology in the Cloud by Analog InformaticsTM analyzes and reports on your existing EMR practice data. We automatically find missed revenue daily and improve the quality of your patient engagements using AI technology.
