Does Structured Reporting Improve Lung Cancer Reports?

A structured reporting tool improved report completeness, reduced classification errors, and achieved high physician adoption during routine lung cancer pathology reporting.

By
Andrea Surnit
July 2, 2026
3 min

Conexiant

Objective:

To evaluate the impact of a structured pathology reporting tool on the completeness and accuracy of lung cancer pathology reports.

Approach:

Retrospective Phase: 123 conventional synoptic pathology reports for primary lung cancer resections were re-entered into the structured reporting platform to assess completeness and identify discrepancies.
Prospective Phase: The structured reporting tool was integrated into routine diagnostics for 151 consecutive lung cancer resection cases over 1 year, with its use remaining optional.

Key Findings:

Retrospective reports showed 98% completeness with 33 missing or inconsistent data elements identified.
Common omissions included spread through air spaces, pleura invasion, and tumor-to-margin distance.
The structured reporting tool achieved 99.9% completeness during the prospective phase with only one missing data element.
90% adoption rate among pathologists for the structured reporting tool.
Automated tumor-node-metastasis staging detected six classification errors in conventional reports.

Interpretation:

Limitations:

Study conducted at a single institution, limiting generalizability.
Limited to lung cancer resection specimens, which may not apply to other diseases.
Workflow efficiency and user satisfaction not quantitatively evaluated.
Integration with electronic health records and external registries was still in progress.