Development and evaluation of a scalable alternative to chart review for phenotype case adjudication using standardized structured data from electronic health records

Objective Chart review as the current gold standard for phenotype evaluation cannot support observational research at scale. It is expensive, time-consuming, and variable. We aimed to evaluate the ability of structured data to support efficient patient status ascertainment and develop a standardized and scalable alternative to chart review. Methods We developed Knowledge-Enhanced Electronic Patient Profile Review system (KEEPER) that extracts the patient structured data elements relevant to a given phenotype and presents them in a standardized fashion that follows clinical reasoning principles. We evaluated its performance compared to manual chart review for four conditions (diabetes type I, acute appendicitis, end stage renal disease and chronic obstructive lung disease) using randomized two-period, two-sequence crossover design. Inter-method agreement, inter-rater agreement, accuracy, and review duration were measured. Results Ascertaining patient status with KEEPER was twice as fast compared to manual chart review. 88.1% of the patients were classified concordantly using full chart and KEEPER, but agreement varied depending on the condition. Two clinicians agreed in classification of patient status in 91.2% of the cases when using KEEPER compared to 76.3% when using full chart. Patient classification aligned with the gold standard in 88.1% and 86.9% of the cases respectively. Conclusion This proof-of-concept study demonstrated that structured data can be used for efficient patient ascertainment if are limited to only relevant subset and organized according to the clinical reasoning principles. A system that implements these principles can achieve similar accuracy and higher inter-rater reliability compared to chart review at a fraction of time.