Hayes' Healthcare Blog

How to Reduce Billing Errors Using GE Centricity EMR Forms

Posted by Robin Tardif on July 5, 2017 at 9:00 AM

In the current state of the ever-changing healthcare landscape, organizations like yours are facing a Revenue-Cycle-Blog.pngchallenging time of reducing healthcare costs while keeping an eye on your margins. You want to make your organization as effective and efficient as possible while at the same time maximizing your margins and minimizing costs.  One of the key places you can start is your billing department.

You want to make sure your billing department is as efficient as possible and one of the most common issues concerns how much time it takes to review and correct rejected orders for office-visit billing. This is especially an issue with new providers or departments in your organization.  If your facility has over 30 providers, it can take several hours each week to fix these billing errors, which can significantly extend the time it takes to receive reimbursement, putting more strain on your bottom line. 

The first step in correcting this problem is to identify the root cause.  Many, if not most, of these problems are caused when the end user starts a new office visit encounter in the electronic medical record (EMR) system. Required information may be entered incorrectly or go missing entirely for a variety of reasons. Common causes are the user rushing to get the patient checked in and roomed in an acceptable amount of time. The user also often forgets to change the ‘Responsible Provider’ from their own name to that of an actual provider or doesn’t select the ‘Visit ID’ associated with the appointment.

These two common examples are easily fixed when the user is alerted to the problem.  Fortunately, a quick and easy solution is to create a custom form that will highlight missing or incorrect information.  A form can be used to remind the user that these items are necessary and need to be corrected immediately. 

An EMR form can be used to:

  • Check for existing visit ID
  • Compare the clinical date to the appointment date
  • Compare user’s location of care to patient’s location of care
  • Check that the responsible provider has the appropriate credentials

Office visit charges must be associated with specific Visit ID.  Reminding the user that this information is missing allows the user to associate the patient visit with the appropriate appointment prior to the billing orders being submitted.

The clinical date for the encounter must also match the appointment date of the office visit.  In many cases, the appointment date may not match because the appointment has not been changed to an “Arrived” status.  However, if a provider is playing ‘catch-up’, and is creating an office visit encounter for the previous day, he/she needs to remember to change the clinical date to reflect the actual date the patient was seen.  Unfortunately, once an encounter is started in the GE Centricity EMR, the clinical date cannot be changed.  The user must discard the current document, and create a new encounter with the correct date. Ensuring that the dates match is another item that can be listed on the EMR reminder form.

Another matching issue concerns the location of care where the entry for the patient and the encounter must be the same.  The problem of these not matching typically arises with users who ‘float’ from one department to another on a regular basis.  In Centricity, when users log in to the EMR, their location of care defaults to the last one they used.  When the user forgets to change their location of care to their new department, all encounters created by that user will subsequently default to using that incorrect location of care.  Fortunately, once made aware of the issue, the user can modify the encounter location of care through the Document Properties.

Having an incorrect responsible provider will also cause billing orders to fail.  One method for validating this is to create user accounts with the provider credentials at the end of the last name in a specific format.  For example, a provider who is an “M.D.” would have “MD” after their last name.  The form checks for the valid credential, and indicates if the provider listed doesn’t meet the requirement.  The responsible provider can also be changed through the Document Properties.

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The form in the example above was created for a medical facility with multiple specialties.  The billing department complained about the numerous hours they were spending each week researching and getting these errors corrected.  The time spent on these issues required one of the billing specialists to set aside most of a day each week to resolve rejected billing orders.  This took time away from her regular job duties, as well as those of the office managers and end users who had to help fix these orders.

To troubleshoot the location of the errors were being generated, I discussed the issue with the manager of the EMR and several billing specialists.  They provided a list of the top reasons for billing orders being rejected.  For the items that were caused by user error - missing or incorrect data for example - we created a form that would validate the required information when starting a new encounter.  After incorporating this form into all encounters, the client reduced their rejected billing orders by over 60 percent – a significant savings in time and effort.  In addition, by highlighting the errors, users became more aware of the mistakes and remembered to open the office visit correctly in the future.

In the end, this was a very simple solution to a very expensive problem.  Billing orders are now being processed with far fewer rejections and errors.  Man hours are being saved from not having to investigate and resolve the rejections and errors.  And the users are being gently reminded to fix their mistakes without requiring extra training. A win-win-win for all involved.

For more information on getting the most from your EMR, download our roadmap, How to Save Your EHR: 6 Steps to Holistic Optimization.


Download Roadmap

Topics: emr efficiency, emr optimization

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