Leveraging AI, Automation, and Data Analytics in a Hospice Setting

By Lindsay Myers, VP of Revenue Cycle & HIM, Chapters Health System

In the hospice setting, the revenue cycle is not only complex but also uniquely fragile, as billing cannot proceed without complete documentation. The sequential nature of hospice billing, where one month’s claims must be fully processed before the next can begin, means that even minor deficiencies can halt revenue entirely. Small delays or errors upstream can have a profound impact on cash flow.

At the nation’s largest nonprofit hospice network, Chapters Health System, AI and automation have become the key to scalability. These tools are expanding the capacity of the RCM and HIM teams, reducing variability, and increasing quality and compliance as the patient census has grown exponentially through affiliations.

AI and automation allow organizations to shift from labor-intensive, manual, and Excel-based processes to create more scalable, streamlined workflows.

AI and Automation

Medicare and multiple state Medicaid programs comprise the majority of the payer mix for most hospices, bringing complex compliance requirements. Physician certifications and recertifications, various elements of the election statement, the timing of face-to-face encounters, and other requirements must be present in order to bill and receive payment.

Historically, this has required significant manual work to identify deficiencies. Team members would check spreadsheets, then follow up with multiple parties—often multiple times—to receive the necessary billing information. It was an error-prone and time-consuming process that spanned multiple departments, adding countless messages to already full inboxes.

To improve this process, the Chapters Health System is developing an AI-driven chart review process to analyze the completeness of clinical and other documentation in real time. The goal is to identify missing or inconsistent elements and route those issues directly to the party that can make corrections—whether that’s a physician, admission nurse, coder, or HIM specialist. Workflows are also being developed to help flag errors, generate alerts, and re-review records as updates are made, eliminating the need for human teams to recheck files multiple times.

The potential ROI is significant, given that hospice is subject to sequential billing requirements. Missing dates, blanks on forms, or missing physician signatures can block multiple months of billing. The impact can be even greater for long-stay patients, or when errors affect a high volume of census days.

The utilization of AI and automation will improve the turnaround time and help resolve documentation gaps. In addition to labor cost savings, another benefit is increased accountability. With each error type associated with specific roles, this process helps identify education opportunities for team members and creates an automated escalation process.

AI is also being leveraged in authorizations to help meet onerous insurer requirements. We started our RCM AI journey with authorizations because the technology is widespread and mature, and can be replicated at scale.

Data Analytics: Integrating Systems for Visibility and Action

Strategic data analytics takes a broader, more proactive view of revenue cycle performance. One of the ongoing challenges that hospice organizations face is that the data requirements for billing reside in disparate systems from multiple electronic medical record (EMR) platforms, to the clearinghouse, and a separate accounting system.

Chapters Health System has an enterprise data warehouse with data feeds from each system. This enables the IT team to build custom reports and dashboards that support RCM operations and strategy. For example, data analytics are used to:

• Identify services not billed by comparing expected census-based revenue to actual claims submitted.
• Identify billing aberrations, such as variations between hospices, anomalies, and patterns within levels of care or add-on payments, etc.
• Monitor KPIs, such as Days in AR, collections percentage trends, denials, and unbillable days trends, and third-party payer conversions for uninsured patients.
• Identify potential compliance concerns, particularly changes in clinical documentation after a claim has been released.

Analytics does not end with reporting—there is a cross-departmental approach to reviewing days of care that are written off or not billable due to various reasons. This approach recognizes that the revenue cycle is not just a singular department’s responsibility—it is a process that encompasses many teams from intake and admissions to medical services, nursing, HIM, and more.

Data analytics has accelerated the identification of issues, enabling prompt action. It also helps leadership teams monitor performance targets and quickly identify root causes of challenges and training needs if metrics begin to deteriorate.

Conclusion: Technology as a Strategic Imperative

AI and automation allow organizations to shift from labor-intensive, manual, and Excel-based processes to create more scalable, streamlined workflows. Data analytics, meanwhile, provides insights that help leaders monitor performance, uncover risks, and plan strategically. Together, these tools continue to transform the hospice revenue cycle from a reactive, fragmented function into a coordinated, high-performance engine that supports both financial sustainability and regulatory compliance.

As these tools continue to refine and expand capacity, the goal is not only to reduce denials and accelerate cash, but also to build a scalable revenue cycle function that is aligned with the mission and complexity of hospice care. In doing so, hospice organizations can ensure that financial operations will support the mission of care in service to patients and families for years to come.