Analog Informatics Corporation

Medical Appointment Errors Detected and Solved by AI

Consequences of Appointment Errors

Today’s high-traffic medical practices face the daily consequence of appointment errors caused by the front desk and clinical staff. At Analog Informatics, we have measured daily appointment error rates of up to 9% in medical practices.

Making matters worse, EMRs do not make it easy to find and correct these errors. Billing companies try to fix coding errors, but when there are missing charts, they have no way to recover revenue.

Appointment and charting errors are shortcomings in the EMR that cause daily patient/guest frustration and significant lost revenue.

In this article, we will discuss common appointment and charting errors. We will show how Analog Informatics AI technology detects and assists staff in correcting errors daily.

History of Appointment Anomaly Detection

Analog Informatics develops and sells modern patient engagement and reputation management systems. We track patient workflows through the EMR from appointment setting, pre-op, and post-op periods. Using the workflows, we keep patients and their authorized guests up to date on their appointments, arrivals, departures, and care plans. We also track and report on the progress of lab/pathology workflows to patients and guests.

Human Errors Confused Our AI

In our product’s field testing, we discovered that many patient workflows ended in impossible states each day, confusing our AI. In analyzing and discussing these errors with clinical leadership, we used AI to isolate and report them.

We had to terminate ongoing conversations with patients and guests when we detected a broken workflow caused by bad appointment data. Our stopping communication disappoints patients and guests who depend on our updates to navigate their healthcare experience.

AI Helps Correct Appointment Errors

We have resolved errors limiting damage and losses by retraining staff and daily error reports to staff. Fortunately, by staff correcting errors promptly, our AI resumes normal patient and guest communication.

Accurate, Timely, and Appropriate Patient Communication via AI

Consistent and continuous communication with patients and their guests makes patients feel better about their procedures and hopeful of their outcomes. AI-based reminders and updates are part of a new wave of personalized communication that reduces practice labor costs. AI communication improves the reputation of healthcare providers who use it. We deliver updates via voice synthesis, text messages, and emails to every consumer device, PC, and phone.

Automation of No-Show and Cancelation Recall Scheduling

One of the most common errors was a failure to complete appointment status for each patient.

Failure to note the final appointment status for EVERY patient was the most common error. This failure meant no notation of no-shows and cancelations in the EMR. This results in a missed canceled appointment caused by an appointment scheduling error.

With accurate appointment final status, we generate periodic recall reminders for patient no-shows and cancelations. We aim to return a replacement appointment to the practice calendar immediately.

Failure to consistently re-engage patients to reschedule missed appointments is a common revenue loss that our AI can reverse. By using AI to re-engage missed appointments, we recover lost revenue.

AI Timing of Patient and Guest Requests for Public Reputation Reviews

We handle scheduled requests to patients and guests for public reviews on Google and Yelp on appointment completion. By understanding the appointment type and timing, we can predict the ideal time to request a reputation review. Appointments not noted as fulfilled or completed create havoc. Is the appointment a no-show, a cancelation, or a completed appointment?

With no final appointment status, it is impossible to know if and when to request a public reputation request. This is another loss of earned media of 5-star reviews caused by human error.

Uncharted Appointments and Unbilled Appointments

Completed appointments with no encounter records were the most concerning. We didn’t know if we saw theft by practitioners giving away services. In other cases, it may have been simply the staff failing to record procedures delivered, resulting in revenue loss. Other scenarios were failures to finalize charts or encounters.

Although statistically rare, unbilled appointments did occur every month in our testing resulting in a significant loss of revenue each month. In our estimation, the loss was equivalent to 1 to 3 FTEs (full-time employees). Because these are unrecorded procedures, back-office billing could not detect or inquire about the losses.

Some practitioners would not chart follow-ups as they are frequently not billable. The default behavior was not to chart visits if the examination results were typical. We have retrained staff to chart all visits for better legal protection.

Technical Description: Detecting Appointment Error

The Anomaly Reports system scans EMR records to identify billing and status errors, and then generates reports. All staff receive daily, weekly, and monthly reports based on in-office schedules.

Each report has per-incident actionable information to allow efficient correction of errors.

Daily, weekly, and monthly anomaly reports are automatically emailed to staff. The reports help staff check if previously flagged errors have been corrected.

Key Takeaways

  • The staff makes errors in EMR entries that go unnoticed (hard to find)
  • Missing Encounters equal lost revenue (no records, no bill, no income)
  • Missed documentation on Encounters leads to poor charting and liability
  • Easy-to-miss no-show appointments lead to failure to re-engage patients to schedule new appointments
  • Daily corrections to appointments and charting errors equal can mean the difference between profit and loss for a practice

AI provides systematic accountability for appointment management that you cannot identify, quantify, or correct manually.


Appointment errors inevitably occur in medical practices with high volumes of patients. Manual processes, inconsistent training, and staff changes all contribute to errors. Appointment errors cost you money, impair proper patient communication, and increase liability.

Fixing hard-to-find appointment errors can be the difference between a profitable practice and one that loses money. AI technology in the Cloud by Analog Informatics 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.

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