The customer is a leading healthcare provider, with 13 different facilities across 6 states in the US. They are renowned for their commitment to exceptional service in Oncology and other specialized disease management. They were facing significant challenges in both Revenue Cycle Management and patient experience. Multiple siloed patient engagement systems were creating duplication of manual effort and the data were not in sync. Additionally, their legacy revenue cycle management processes resulted in high error rates and prolonged processing times, negatively impacting revenue collection.

Their leadership wanted to upgrade their legacy applications and also experiment with the emerging technologies to identify potential use cases suitable for their business. They were looking for a ‘Build Fast Fail Fast’ model to accelerate adoption of AI and Automation across the enterprise.

• Fragmented Patient Engagement Systems and Data Silos: The healthcare provider relied on multiple, disconnected patient engagement systems. This fragmentation led to duplicate efforts in data entry and communication across these systems. Furthermore, the lack of data synchronization created inconsistencies and hindered obtaining a holistic view of each patient’s journey.
• Inefficient Revenue Cycle Management (RCM) Processes: Their legacy RCM processes were prone to errors. This resulted in inaccurate billing, claim denials, and delays in collecting payments. These inefficiencies negatively impacted the healthcare provider’s cash flow and revenue.
• Compromised Patient Experience: The combined effects of data silos and inefficient RCM processes ultimately led to a subpar patient experience. Patients may have received redundant communication due to duplicate data entry. Additionally, billing errors and delays could have caused confusion and frustration.

• Initially we built 3 POCs from different lines of businesses to showcase the impact of RPA and AI technologies using different platforms/ tools.
• We then conducted an enterprise-wide readiness assessment and proposed our RPA Factory Model for faster adoption of emerging technologies. We also set up a mechanism to manage the ideation funnel where all the employees could contribute.
• We set up the RPA Factory Model with 8 different roles within 2 weeks and started churning out 5 RPA Bots every month. In the next 18 months, we built and deployed more than 90 Bots leveraging various different technologies for Finance, HR, IT, Customer Care, Revenue Cycle Management, Procurement and legal functions.
• We are also upskilling their employees through our AI-RPA upskilling platform, OMNI.

The implementation of Airo’s RPA solutions led to remarkable improvements and substantial cost savings for the healthcare provider:

• Streamlined Operations: Achieved a 48% reduction in overall operational cost through process automation and eliminating duplicate efforts. This translates to significant cost savings that can be reinvested into patient care initiatives.
• Enhanced Staff Efficiency: Improved overall productivity by 40%, allowing staff to focus on what matters most – delivering exceptional patient care.
• Soaring Patient Satisfaction: Patient satisfaction scores soared by 60%, reflecting a more streamlined and efficient experience throughout the care journey.
• Faster Reimbursements: Reduced claim denials by 4% on first pass, leading to faster reimbursements and improved cash flow.
• Accelerated Collections: Reduced the number of Days Sales Outstanding (DSO) to just 40 days. This translates to faster collections and improved financial health for the healthcare provider.
• Minimized Bad Debt: Successfully reduced bad debt from 11% to 8%, signifying a significant improvement in revenue collection and financial performance.

This case study exemplifies how a leading healthcare provider transformed patient care and financial performance with AI and automation. Facing siloed systems and inefficient processes, they partnered with Airo for a “Build Fast Fail Fast” approach. Airo implemented 3 initial Proof-of-Concepts (POCs) and established an RPA Factory Model, fostering enterprise-wide adoption. Within 18 months, over 90 RPA bots were deployed across various departments. These solutions yielded significant results: 48% reduced operational costs, 40% improved staff productivity, and a 60% surge in patient satisfaction. Additionally, faster reimbursements and minimized bad debt improved the provider’s financial health. This successful collaboration demonstrates the power of AI and automation to optimize healthcare operations and deliver exceptional patient experiences.