Although the nonprofit regional health system held a stable market position with its health plan, the operation of its managed services organization (MSO) was heavily manual, fragmented, and dependent on brittle processes. Critical workflows relied on paper, inconsistent handoffs, and workarounds that were vulnerable to routine disruptions such as courier delays, internet issues, and reliance on printed checks. The aging claims adjudication system required significant manual intervention to keep production moving.
These inefficiencies created payment risk exposure, slowed throughput, and limited the organization’s ability to scale effectively in a competitive market. With Epic Tapestry slated to replace core systems, the healthcare system needed to stabilize current operations to ensure business continuity during the transition.
Data Disparity and Differing Workflow Perspectives
A major challenge stemmed from inconsistent, incomplete, and manually maintained data. Key performance metrics—including auto-adjudication rates, examiner productivity, and inventory levels—were tracked across disparate spreadsheets, often with differing methodologies. Variability in data quality made it difficult to construct a unified and accurate picture of the MSO’s performance. To overcome data fragmentation, Impact Advisors triangulated insights across multiple sources and standardized templates to improve data cleanliness. This allowed the team to construct a reliable view of current-state performance despite system limitations.
A second challenge involved bridging the gap between leadership’s strategic understanding of workflows and frontline employees’ lived experience of workarounds and bottlenecks. Ensuring recommendations were both feasible and grounded in operational reality required reconciling these perspectives.
A Combination of Insights and Real-World Experience
Impact Advisors executed a structured, insight-driven approach that combined field observations, extensive interviews, and
detailed data analysis. The methodology centered on three pillars:
- Leadership and Frontline Insights: Structured interviews with MSO leaders and shadowing sessions with frontline staff—including claims examiners, team leads, auditors, eligibility analysts, IT and configuration specialists—provided a comprehensive understanding of both strategic intentions and actual workflow challenges. These observations formed the foundation for identifying inefficiencies, validating hypotheses, and pinpointing opportunities to streamline processes.
- Claims Insights Analysis: The team analyzed paid claims data to assess intake volumes, manual versus auto-adjudication patterns, turnaround time compliance, and coding trends. This revealed throughput constraints, potential rework drivers, and variability in adjustment patterns, all of which were the result of broader observed inefficiencies.
- Resource and Capacity Assessment: A detailed staffing evaluation measured throughput per full-time employee and inventory backlogs, benchmarked against industry norms, to determine whether resource allocation aligned with workload demands.
Positive Impact
The assessment identified four critical areas where the health system could achieve rapid operational improvement and build readiness for Epic Tapestry.
- Vendor Rationalization: Evaluate capabilities and interoperability of multiple clearinghouse vendors and claim processing vendors, and identify optimal Epic-compatible solution to streamline workflows.
- Forced Payment Process Redesign: Conduct a Rapid Process Improvement (RPI) event to further identify inefficiencies and redundancies. Redesign the process to reduce admin costs and eliminate non-value steps.
- Claim Digitization and Paper Reduction Initiative: Engage stakeholders across care delivery and operations to identify key levers. Develop MSO paper reduction strategy with identified ownership and success metrics.
- Contract Management System Modernization: Conduct a market scan of leading contract management solutions and facilitate an RFP process. Identify vendor of choice based on functional, technical, and operational fit.