The following is a guest article by Helen Lamons, SVP of Revenue Cycle Management at Advata.
In recent years, AI has made various advancements in the administrative and clinical setting as healthcare systems leverage the technology to benefit workflow operations and reduce human errors. As a business, it makes sense to embrace AI in revenue cycle management (RCM) fully. The potential applications are limitless. As healthcare systems seek tactics to increase revenue following the dire financial impact of the pandemic, 2023 is the perfect year to consider implementing AI to benefit your team and bottom line.
Healthcare organizations are struggling with staff shortages across the board – ranging from the bedside to the back office. This reduction in staff is leading to an increasing number of accounts going uncollected. Thankfully, these facilities can implement tactics leveraging AI to improve denials management.
Hospitals and health systems in the U.S. are approaching monumental change — seeking ways to leverage AI to answer complex challenges. Two-thirds of hospital and health system executives already report using AI in some revenue cycle capacity, which is anticipated to grow significantly as the industry enters 2023.
Leveraging AI to Reduce Denials
As healthcare organizations of all sizes struggle with staff shortages, an increasing volume of accounts is written off as uncollectible, sacrificing crucial revenue. In a recent study from the 2022 State of Revenue Integrity survey published by the National Association of Healthcare Revenue Integrity (NAHRI), more than half (57%) of respondents said a lack of qualified staff had a negative impact on the backend processing. Respondents cited staffing shortages and new projects created by emerging regulations as pain points.
As health facilities face these growing staffing challenges, decision-makers can turn to AI for additional assistance. AI can help predict claim denials by analyzing past denial trends and alert staff of the potential denial prior to billing. AI allows for reviewing and correcting claims pre-bill. By utilizing AI-enabled dashboards, teams gain insight to help reduce recurring denials and improve workflows and education. To provide further benefits to the patient and accounts receivable (AR) team, self-pay patients can integrate with financial assistance technology that verifies any aid options. Additionally, integrating AI with provider documentation reduces queries from coding professionals, which expedites claims submissions. The list of AI applications is endless.
One of the largest areas with AI-enabled products and functions for RCM is denials management. By leveraging AI and data analytics to target places of high-dollar as well as high-volume and low-return, organizations can work denials proactively, instead of retrospectively. Once the backend processes are managed and visible, teams can move toward upstream process improvements. Identifying and implementing upstream fixes can lead to a quick turnaround of cash.
In healthcare, RCM performance is critical. Advanced technology solutions help improve the revenue cycle by using data to understand common patterns. Advanced solutions can guide the next recommended step and their prioritization from this analysis. These analytics will simplify the process and help capture increased revenue by first prioritizing the right tasks (cash-collecting tasks).
Invest in Technology for Accounts Receivable
In many healthcare organizations, up to 85% of AR volume remains unworked, leaving about 4% of financial value unrealized. The low-balance problem is one that most organizations struggle with daily. How are you supposed to work low-balance accounts that cost more to collect than you are paid?
Advanced analytics software can identify and provide a roadmap of the next suggested actions to resolve outstanding receivables, assist in workflow sequencing, and determine the appropriate workflow prioritization. The analytics do the discovery for health systems and bundle the populations of accounts with the same required actions together so they can be automated and/or worked en masse. Targeted recommendations can help make the decision-making process easier, faster, and much less expensive. With advanced AR offerings, teams can work 100% of the AR and increase AR collections by up to 1% of the total net patient service revenue (NPSR). To date, some companies with advanced offerings have individually generated over $500M of NPSR benefit to its customers.
Utilizing advanced data analytics enables more efficient use of an employee’s time, improving their productivity. By prioritizing the workflow, the AR team can decrease time spent on negative ROI accounts, capture more cash, and collect revenue for accounts that would have otherwise been written off as uncollectible.
Selecting the Best AI Offering to Improve RCM
Advanced analytics and AI-driven healthcare applications can bring technology, security, and compliance challenges. Providers should consider seeking a partner who offers in-depth hospital operations knowledge and deep data learning through practical experience to ensure ongoing success and avoid any of the above challenges. Select a partner who provides best practices in healthcare data management, responsible AI, and application delivery in a single deployment platform that has been refined through years of real-life operational revenue cycle management experience.
About Helen Lamons
Helen Lamons is the Senior Vice President of Revenue Cycle Management at Advata. With over 14 years of experience in revenue cycle management (RCM) operations, Helen has spent significant time leading and growing high-performing teams within the revenue cycle. She has led client success teams in patient engagement and SaaS companies.
Before Advata, Helen helped dozens of customers achieve cash improvement year-over-year while reducing A/R Days. Additionally, she has utilized robotic process automation (RPA) to help customers automate up to 50% of accounts receivable.
Helen graduated from Vanderbilt University with a Bachelor of Political Science degree and was a Division I SEC College golfer.
