Our summary
Evaluating the quality of cancer care is crucial for oncology practice administration and participation in value-based initiatives. Electronic health records (EHRs) provide an opportunity for automated calculation of quality measures on a larger scale compared to manual chart reviews. Achieving this, however, involves creating algorithms that process data and employ customized logic to establish clinically relevant metrics.
In this study, researchers crafted a time to treatment (TTT) metric, which measures the duration from the initial patient visit with their medical oncologist to the commencement of the first cancer treatment using EHR data.
Why this matters
This research proves that quality metrics can be derived from electronic health records (EHR) data on a large scale. The accuracy of these metrics, particularly the TTT metrics, hinges on the availability of complete and structured treatment data. To enhance accuracy, future research should incorporate diverse treatment modalities and employ advanced techniques like natural language processing. By simplifying quality assessments and paving the way for more precise cancer research, this study offers valuable insights for the future of oncology care.