Intelligent Abstraction = Efficiency & ROI

Is abstracting 4+ months after diagnosis efficient?
Research says it is not!

A common objection to concurrent abstracting is that updating a case multiple times takes more time and effort. Today, many cancer registrars still believe touching a case more than once is wasted time.

False Perception: “Updating cases in phases takes longer than abstracting once in 4-6 months.”

In practice, the opposite is true. Phasing distributes work across the patient’s journey, spreads workload evenly, and avoids the frantic year-end scramble. Cognitive science research proves that chunking tasks improves speed and accuracy—by breaking work into smaller steps, humans process information faster and with fewer errors (Wu, PLoS One, 2023).

Automation with AI takes this even further. Intelligent abstraction tools auto-populate fields, provide real-time updates in sync with patient care, and surfaces missing information, thereby shrinking manual effort. A review in npj Digital Medicine showed that AI automation reduced task times in 67% of clinical workflows, freeing professionals for judgment-based work while maintaining accuracy (Nature, 2024).

Concurrent abstraction powered by automation means registrars spend less time searching and typing—and more time validating, curating, and improving quality. Far from adding time, phasing saves it.

Truth: Phased, or concurrent, abstracting in near real-time with AI automation has proven to be faster and more accurate than delayed abstracting.

This post was originally published on LinkedIn.

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