How are working ODS-Cs preparing for AI integration, and what skill sets will keep us essential? (Student Inquiry)
Hey everyone,
I'm currently in an NCRA accredited program with plans to take my ODS-C exam upon completion, of course. I'm genuinely intrigued by the daily assignments and tasks involved in oncology data work and the meaningful, essential role cancer registries play in research, treatment tracking, and public health.
As I look ahead to entering the workforce, I wanted to ask current/experienced ODS-Cs for your perspective on how specialized AI software are starting to shift daily workflows and the direction of the future.
With the majority of the central, daily work being digital and centered on data extraction, initial case finding, and coding, this all strongly signals that tech will eventually handle a larger degree of the routine data processing. From what I've investigated, at least presently, standard setting bodies (like NCRA, CoC etc) still emphasize credentialed human oversight and direct involvement to maintain strict data quality standards. However, as health systems look to maximize efficiency (as does any industry) the day to day functions of an ODS-C are bound to evolve.
For someone entering the field over the next couple of years (by the time I graduate, become credentialed, and am initially hired) I’d love to hear your insights on a few questions.
For those already seeing AI or automated case finding in your registries, how has it changed your day to day workload? Has it shifted focus more toward primarily case abstraction, quality auditing, or data validation?
What advanced skills, continuing education (degree and/or specialized certification), or specialized directions, (central/state registry reporting, data auditing, management/leadership, specialized informatics, or otherwise, as those were just a few potential directions that came to mind) would you recommend focusing on and potentially pursuing to remain highly adaptable as the industry changes?
What aspects of an ODS-C’s skills, such as interpreting complex, ambiguous clinical notes or navigating nuanced, individualized pathology, do you feel are most difficult for automated systems to replicate and/or achieve at high levels of accuracy?
Unfortunately due to a permanent physical disability, a fully stationary career path like this is an absolute necessity for me (I would have pursued allied health ages ago, but careers that aren't guaranteed consistently stationary are quite literally not sustainable short term let alone long term for me :’/), so I'm fully invested in building a resilient, long term career in this industry.
I'd sincerely appreciate any guidance, honest reflections, or advice you can share on how to best position myself for the future of the profession as a whole.
Thanks so much for your time and for those of you who are already immersed in the role and industry for sharing your direct experience!