Background: Measurement and monitoring of palliative care quality metrics for patients with advanced cancer promote early integration of palliative care within the oncology clinic. Accurately identifying the subset of advanced cancer patients within a population of cancer patients who would most benefit from palliative care is critical to the development of palliative care-relevant quality improvement activities. Methods: We evaluated two automated approaches to identifying patients with solid tumors sufficiently advanced to warrant discussions of palliative care and advanced care planning. These approaches included (1) pattern matching of words indicating an advanced cancer in oncology notes, radiology imaging, and active problem lists and (2) International Classification of Diseases (ICD-10) codes. We randomly selected 586 charts of patients with active cancer who are patients in our health system to establish a gold standard for advanced cancer through expert chart review. We evaluated the sensitivity and specificity of these automated approaches to identify advanced cancer patients compared with the gold standard. Results: We found that the highest performing pattern matching method had a specificity of 76% and a sensitivity of 81%. Using our final ICD-10 algorithm, we achieved a specificity of 92% and a sensitivity of 68%. We improved our sensitivity to 76% while maintaining our specificity at 91% when we excluded patients assigned to oncologists who predominantly see hematological malignancies. Conclusions: We achieved high specificity and reasonable sensitivity for an advanced cancer quality metric denominator using an ICD-10 algorithm within an academic oncology practice. This concrete definition will help inform quality improvement efforts locally and beyond.

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