Robotic Process Automation (RPA) is seen as critical by healthcare organizations for increasing net revenue, lowering costs, and improving the patient experience. While RPA addresses inefficiencies throughout the revenue cycle and provides quantitative benefits, it can also produce operational and qualitative benefits.
Healthcare organizations that have used RPA technology understand that automation has many benefits: quantitative, operational, and qualitative; read on to learn more:
- Quantitative Success Factors
Automation technology, particularly in high-volume patient inflow, can drive labor savings and revenue increases by eliminating rote tasks and reliably taking actions to avoid delayed or denied reimbursement. Automation will not necessarily reduce an organization’s overall headcount, but it will enable employees to focus on more revenue-generating tasks than they would otherwise.
- Operational Success Factors
RPA can improve turnaround times, service levels, and capacity by streamlining complex processes to work more smoothly. Automation often bridges the gaps between systems to facilitate a more unified consumer and caregiver experience in health systems’ often-fragmented technology landscape.
- Qualitative Success Factors
Healthcare organizations can improve accuracy, consistency, compliance, and risk management by incorporating bots into the workflow. Automation can thus help in providing peace of mind and reducing an organization’s risk profile.
Let’s take a look at some other critical success factors that can help you accurately calculate RPA ROI in Healthcare-
- AR Days– AR days, also known as days in Accounts Receivable, measure the time it takes to receive payment on a claim, assisting healthcare leaders in identifying potential revenue cycle issues and calculating the efficiency of their billing team. High AR days should serve as a warning to business owners because they can hurt the bottom line. Our advice is to reduce your medical AR days by submitting daily claims, promptly following up on old claims, and simplifying bills so that patients can understand them. The industry average is 35 days. In contrast, an AR of 60 to 90 days should raise a red flag.
- First Pass Acceptance Rate (FPAR), also known as the First Pass Clean Claim Rate (FPCCR), identifies problems and inefficiencies in claim submission and processing, revealing the effectiveness of the claims processing and medical billing team. The total rate of all claims submitted is a popular alternative to the Claims Acceptance Rate (CCR). Even if the claims are rejected initially, the First Pass Acceptance Rate only calculates acceptance based on the first submission. Lower AR days and faster payments will result from improving FPAR. Common causes of a lower rate include errors, oversights, and inefficient billing processes. The industry benchmark is 98%. More than 90% of a well-run medical practice should be efficient.
- Net Collection Rate (NCR) is the amount of money hospitals should collect from their patients and insurance companies. A high NCR reflects timely billing, adjudicated claims, and patient balances collected. Net collections, as opposed to gross charges, represent what your company can realistically expect in reimbursement. It reflects denial rates, unreimbursed visits, and other variables on revenue. Healthcare organizations should consider a billing audit if the NCR is less than 90-100% after write-offs.
- Denial Rate– the percentage of claims denied by payers is known as the denial rate and assesses the effectiveness of revenue cycle management processes. A low denial rate indicates a healthy cash flow and provides insight into how quickly the claims are processed. If the denial rate is not addressed promptly, it will have a negative impact on other KPIs. Missing information in the service or claim form and improper or lack of coding are the leading causes of high denial rates.
- The percentage of unbilled (unclean) claims (%)is the proportion of claims received from hospital LIS/EMR with unclean data that delays billing. Incorrect demographic information, missing or invalid DX codes, medical necessity edits, CCI edits, and missing invalid ordering physician errors are some examples.
Conclusion
Revenue cycle leaders can gain support for leveraging powerful technology that improves efficiency, quality, and revenue by focusing the conversation on the benefits of RPA implementation across three categories — quantitative, operational, and qualitative.
Revenue cycle leaders must bring the fundamental information when making the business case for RPA, starting with baseline data, which allows the organization to set realistic expectations for automation and its impact. Finally, discussing the impact of improved staff performance, work quality, data value, and reduced compliance risk.
Contact us at info@thediligentgroup.com if you’re interested in starting your organization’s RPA journey or upgrading your current automated processes to intelligent automation.
