Evaluation of the Reliability of Electronic Medical Record Data in Identifying Comorbid Conditions among Patients with Advanced Non-Small Cell Lung Cancer

Background. Traditional methods for identifying comorbidity data in EMRs have relied primarily on costly and time-consuming manual chart review. The purpose of this study was to validate a strategy of electronically searching EMR data to identify comorbidities among cancer patients. Methods. Advanced stage NSCLC patients (N = 2,513) who received chemotherapy from 7/1/2006 to 6/30/2008 were identified using iKnowMed, US Oncology's proprietary oncology-specific EMR system. EMR data were searched for documentation of comorbidities common to advanced stage cancer patients. The search was conducted by a series of programmatic queries on standardized information including concomitant illnesses, patient history, review of systems, and diagnoses other than cancer. The validity of the comorbidity information that we derived from the EMR search was compared to the chart review gold standard in a random sample of 450 patients for whom the EMR search yielded no indication of comorbidities. Negative predictive values were calculated. Results. The overall prevalence of comorbidities of 22%. Overall negative predictive value was 0.92 in the 450 patients randomly sampled patients (36 of 450 were found to have evidence of comorbidities on chart review). Conclusion. Results of this study suggest that efficient queries/text searches of EMR data may provide reliable data on comorbid conditions among cancer patients.