Reventics Scales Capacity and Improves Accuracy in Healthcare Billing Service Leveraging Robotic Process Automation

Reventics’ medical coding service involves accessing EHR systems to download data, align datasets, and create a prioritized queue based on criteria such as age of data and dollar amount of a claim.  Services further entail assigning medical codes to patient charts and verifying patient insurance eligibility that require complex, secure, and HIPAA compliant workflows involving repetitive tasks executed at regular intervals.  These tasks are devoid of strategy, decision-making, or other high-value skills and tie up an employee’s time and talent.  Any increase in volume demands adding head count and any errors directly impact clients getting paid on time and create a frustrating experience for patients.

In its quest to create a fast and error-free medical coding workflow, Reventics employed Robotic Process Automation (RPA) to increase output and speed up reimbursements while freeing up employees for higher-value tasks.  The team successfully streamlined and automated repetitive parts of workflow - downloading data, scrubbing, merging data sets, and generating a prioritized queue to handover to medical coders.  Reventics likewise used RPA to verify insurance eligibility of patients and noticed a threefold increase in productivity.  Denial rates too reduced from 15% to 10%, minimizing manual follow ups.  RPA continuously endeavored to ensure clients got paid more quickly while successfully increasing turnaround time and lowering claim-denial rates.  Besides helping Reventics find additional revenue enhancement opportunities for clients, it also augmented the overall patient experience.

After implementing RPA, Reventics had a direct saving of 20 to 25 full-time equivalents (FTEs) and indirect saving through reduction in rework, denial and rejection rate, and down time for operations team.  Reventics estimates a $100,000 annual cost reduction in its India operations, comprised of both savings.  Reventics is working on implementing cognitive functionalities - AI and Natural Language Processing (NLP) - into RPA solutions for image reading and processing, while exploring ways to use assisted virtual agents and provide RPA as a service to clients.

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