RESULTS
Time
Saved
Between 15 and
0 hrs/week
Staff
Morale Increased
0 %
Reducing the Burden of Outpatient/ Inpatient Billing Splits through Automation
SphereGen Case Study
When a patient moves from an outpatient status to an inpatient status, service charges must correctly reflect the M2 designation for inpatient billing, or denials may occur.
The process of reviewing and correcting miscoded charges to avoid M2 denials includes multiple steps and is painstakingly time consuming.
Learn how our customer is approaching automating the process of billing code corrections for outpatient/inpatient splits, when evaluating patient status changes. By automating steps of the process through a phased approach, our customer can begin seeing ROIs quickly – with the overall end goal of saving hundreds of hours when splitting charges.
Reducing the Burden of Outpatient/ Inpatient Billing Splits through Automation
SphereGen Case Study
When a patient moves from an outpatient status to an inpatient status, service charges must correctly reflect the M2 designation for inpatient billing, or denials may occur.
The process of reviewing and correcting miscoded charges to avoid M2 denials includes multiple steps and is painstakingly time consuming.
Learn how our customer is approaching automating the process of billing code corrections for outpatient/inpatient splits, when evaluating patient status changes. By automating steps of the process through a phased approach, our customer can begin seeing ROIs quickly – with the overall end goal of saving hundreds of hours when splitting charges.
O V E R V I E W
One of the largest challenges for providers is the management of denials cost. An M2 denial occurs when service charges are not coded correctly or bundled together properly based on rules for billing outpatients versus inpatients, sometimes referred to as outpatient/inpatient splits. To avoid this error, meticulous review of the patient’s insurance coverage and all associated charges must be undertaken. Our customer is using Automation to reduce the considerable time efforts required to correct and realign codes for splits, setting the stage for significant ROIs in time savings.
Challenges
When an outpatient becomes hospitalized, billing charges must correctly reflect the M2 designation for billing. M2 denials occur when charges are incorrectly coded – either by status or according to the rules for inpatient billing. To reduce the possibility of M2 denials, all charges must be meticulously reviewed and corrections made as needed. This process may require well over 15 steps, as some bills have dozens of charges in multiple types. This workflow is not only time consuming for staff, but requires focus, detail and intricate knowledge of the billing rules and codes. If the work backs up, the likelihood of having time to accurately code bills reduces, resulting in more denials.
SOLUTION
Our customer’s goal is to automate multiple steps in the M2 or outpatient/inpatient splits process to relieve staff of time-consuming work and reduce overall M2 denial rates. SphereGen is using a phased agile approach to automate steps, so that automations can be deployed more quickly and our customer can begin realizing ROIs sooner. The first step in the phased approach was to automate the correction of SADs (Self Administered Drug) codes. The initial ROI of this step is a time savings of 1-3 hours/day for 3 FTEs. As more steps become automated, the ROI will continually grow eventually reaching hundreds of hours per month and increasing overall accuracy of claims submission.
THE DETAILS
PROCESS SAD ENCOUNTERS
As staff members work each encounter to split charges and determine M2 designation, completed encounters are moved to a work queue. Once a day, the bot accesses the queue and filters out all SADs codes. The bot then begins processing each SADs charge.
UPDATE CODES
For each charge, the bot retrieves the HCPCS code and updates the code to the appropriate value for M2 designation. The new code is then updated back to the queue. If the charge cannot be processed, the charge is written to an exception queue. Once all charges have been processed, the bot sends notification of the completed process so staff can complete the workflow.
EXCEPTIONS
If any charges are written to the exception queue, the bot notifies staff. Exceptions must be reviewed by staff for review and corrected manually.
CONCLUSION
The work in splitting bills and assigning M2 designations to patient encounters is highly manual work and can be incredibly time-consuming, especially if there are multiple charges on a bill. The process is tedious, detail oriented, and if not processed correctly – can result in costly denials.
Our customer is tackling this problem by automating multiple steps in the M2 designation process. By taking a phased approach, small but quick ROIs can be recognized. These wins empower staff, improve morale and increase overall accuracy resulting in less denials.
Although each automated step may only save a few hours each day, when viewed in total – the savings multiply. Eventually, the overall savings for these automations will total in hundreds of work hours per month.
Our customer will benefit by reducing costs in denials and improving staff morale by providing time for staff to refocus priorities.
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