Navigating Complex HCO Hierarchies: Insights from Data Leaders

Aug 18, 2026 | Ryan Sowers

Across the U.S. healthcare system, Veeva observes more than 350,000 data changes daily. When customer reference data fails to reflect those changes, it impacts the accuracy of your analytics, resulting in issues like misallocated territories, skewed patient-volume rollups, and conflicting market-share calculations. Executing a successful account-based targeting strategy demands real-world hierarchies backed by complete account data.

I recently sat down with data management leaders from EVERSANA, Organon, and Abbott to discuss how they leverage complete account data to manage complex healthcare organization (HCO) hierarchies with real-world precision. The key takeaway: to eliminate manual data cleaning and align reporting with field execution, organizations must transition from static directories to dynamic, verified affiliations.

Grounding analytics in real-world clinical activity

Mapping the continuous movement of healthcare professionals (HCPs) across multi-layered health systems is a foundational challenge. Visualize the U.S. healthcare system as a tree. The leaves are individual HCPs interacting with patients, while the branches represent the intricate networks of HCOs and how they connect. To design balanced territories and execute reliable account-level rollups, tracking must look past administrative addresses and map true clinical footprints.

Historically, navigating HCO structures meant wrestling with rigid database models. Longitudinal claims data like Veeva Compass now provides a way to dynamically record clinical activity. By aggregating real-world claims data, analytics teams gain objective, verifiable evidence of where a physician saw a patient, exactly when a relationship began, and when they stopped practicing at a location. This comprehensive view gives data teams the confidence to roll up prescriber-level metrics into accurate, top-tier account profiles.

Eliminating the tug-of-war between field and analytics

Data teams frequently face conflicting internal requests: Analytical teams need to map macro organizational volume for market access and contracting, while field teams demand insights into how to access HCOs for their daily calls.

When teams work from disjointed numbers instead of a shared reference point, they lose trust in corporate data.

Ryan LaValva from EVERSANA highlights how reliance on raw claims data alone can inadvertently mislead commercial operations if it lacks field context.

Peg Manto from Organon emphasizes that bridging this gap requires a unified, multi-layered data model capable of supporting both commercial perspectives simultaneously. She also highlights how a structured approach resolves the systemic burden of manual account mapping:

Veeva OpenData incorporates an intelligent scoring model that cross-references claims volume, public datasets, and field-validated entries. This delivers the complete account data necessary to unlock accurate account-based targeting. With access to structured immediate parent, hospital parent, and regional top parent layouts, analytics teams can run precise macro reporting while sales reps navigate localized targets natively within their CRM.

Ensuring accurate hierarchies through AI and human oversight

For operations professionals, processing endless Data Change Requests (DCRs) is a major resource drain. Teams often find themselves playing defense against administrative drift rather than focusing on a proactive data strategy.

To solve this, teams can integrate agentic data curation directly into processing pipelines. For instance, an automated HCO hierarchy reconciler agent deploys specialized AI agents to actively parse public health system schematics and check them against reference structures in near-real time.

Veeva found that this agent reliably reaches a high level of accuracy. However, that remaining variance is exactly why human verification remains critical to the model.

This hybrid model ensures that clear structural updates are processed instantly via automated curation. More complex cases, such as tracking cross-affiliated providers within heavily restricted healthcare systems, are automatically routed to data stewards for deep validation.

Robin Welt from Abbott shares how actively aligning internal data with an objective master reference infrastructure uncovers hidden opportunities and additional insights:

Delivering a future-proof analytics foundation

Absolute data accuracy is an ongoing operational commitment, not a static achievement. OpenData addresses the systemic pain points of data fragmentation by delivering a fully integrated, continuously verified view of U.S. healthcare hierarchies.

By unifying claims-based scoring, automated agentic tracking, and professional human oversight, OpenData provides your teams with the complete account data and precise structural foundation needed to eliminate administrative discrepancies and drive account-based commercial precision.

Learn More about Clean Data for Agentic Curation
Check out a recent video on how agentic data curation keeps reference data moving quickly for field teams to help get treatments to patients faster.