Efficiency Comes in Phases
Abstracting efficiency does not come retrospectively.
Efficiency comes in phases and moves with the patient.
For decades, cancer registrars have been trained to abstract retrospectively—waiting until treatment was complete to build a complete case in a single abstracting session. Despite increasing pressure from physicians and administrators to provide real-time information, cancer registries have continued to hold on to the belief that delayed or retrospective abstracting is the most efficient and accurate.
PERCEPTION: “Efficient abstracting begins after the patient completes first course treatment.”
Reality tells a different story. Retrospective manual abstraction means cancer registrars spend months chasing down records, spend longer periods of time abstracting, data entry error rates increase, information grows stale, and insights shared with the clinical teams arrive too late to matter for patient care or quality improvement.
Automation augments concurrent abstracting and changes the equation. Data is auto-extracted and captured in phases, concurrently with–diagnosis, staging, first treatment, recurrence, follow-up—while records are fresh. With AI-enabled tools continuously scanning multiple feeds (pathology, imaging, surgery, radiation, medical oncology, EHRs), registrars visually review data that was auto-extracted and interpret the findings instead of manually searching and typing.
The benefit? Cleaner data, captured sooner, and available for care teams, administrators, and researchers in near real time. A pilot from the National Cancer Institute showed that concurrent reporting cut cancer incidence reporting delays dramatically without sacrificing accuracy (Chen et al, JNCI Mongraph, 2024). Similarly, Nelson emphasized that concurrent, real-time registry feeds create actionable intelligence that supports care decisions today, not months later (Nelson, BMJ, 2016).
TRUTH: Concurrent abstraction is far more than being faster and efficient — it’s smarter.
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