Innovation Through Automation: The Future of Oncology Data Management
The field of oncology data management is entering a new era—driven by increasing demands for accurate, timely data and constrained by a shrinking pool of qualified professionals. While the challenges are real, the opportunity to innovate has never been greater.
Here, we share the importance of automation in oncology data management.
A Shrinking Talent Pool, A Growing Need
In 2023, the National Cancer Registrars Association (NCRA) officially renamed the Certified Tumor Registrar role to Oncology Data Specialist (ODS)—a name that more accurately reflects the growing clinical and analytical complexity of the profession. But with the title evolution has come a deeper realization: there simply aren’t enough people to meet the growing demand.
The workforce shortage is well-documented. The NCRA and the National Cancer Institute previously reported approximately 7,000 certified cancer registrars across the US, with projections showing a need for hundreds more to keep pace with rising cancer incidence, reporting requirements, and population health initiatives.
More recently, the complexity of abstraction tasks has increased, while staffing levels have not kept pace—despite modest gains from automation and Natural Language Processing (NLP) tools. Health systems across the country are feeling the strain.
A Backlog with Real-World Impact
Few examples highlight this challenge more than the Veterans Affairs (VA) health system, which is currently experiencing a significant, multi-year backlog in cancer data abstraction. The consequences are more than administrative—this delay impacts veterans’ care, data integrity, research efforts, and even the funding of cancer programs.
The VA has turned to the private sector to staff up and fill these critical data gaps, making it clear that traditional staffing models are no longer sustainable on their own.
Automation as a Force Multiplier
This is where innovation comes into play. AI and automation aren’t here to replace Oncology Data Specialists, they’re here to amplify their impact.
Examples of AI-powered tools already proving value:
- NLP to extract relevant clinical details from pathology, operative, and treatment reports
- Pre-populated abstraction fields that reduce manual data entry
- Automated case prioritization based on timeliness, tumor type, or treatment complexity
- Data validation engines that flag inconsistencies or gaps for expert review
By integrating these tools into cancer registry workflows, each ODS can focus more on clinical judgment, compliance, and data quality, rather than repetitive data tasks. In short, AI becomes the engine that scales expertise.
A Path Forward
With major systems like the VA actively seeking outside support and automation tools continuing to evolve, the industry has a real opportunity to build a sustainable, hybrid model—one that combines the unmatched insight of human experts with the efficiency of intelligent automation.
The data burden isn’t going away. But with smart investments, the future of oncology data management can be one of resilience, innovation, and impact—ensuring that every patient’s journey is captured, every dataset is accurate, and every Oncology Data Specialist is supported.
Struggling with a backlog? Harmony Healthcare can help. Contact us today to learn how we support oncology data teams with expert staffing and AI-powered solutions.
