A test of automated use of electronic health records to aid in diagnosis of genetic disease.

Purpose: Automated use of electronic health records may aid in decreasing the diagnostic delay for rare diseases. The phenotype risk score (PheRS) is a weighted aggregate of syndromically related phenotypes that measures the similarity between an individual's conditions and features of a disease. For some diseases, there are individuals without a diagnosis of that disease who have scores similar to diagnosed patients. These individuals may have that disease but not yet be diagnosed.

Methods: We calculated the PheRS for cystic fibrosis (CF) for 965,626 subjects in the Vanderbilt University Medical Center electronic health record.

Results: Of the 400 subjects with the highest PheRS for CF, 248 (62%) had been diagnosed with CF. Twenty-six of the remaining participants, those who were alive and had DNA available in the linked DNA biobank, underwent clinical review and sequencing analysis of CFTR and SERPINA1. This uncovered a potential diagnosis for 2 subjects, 1 with CF and 1 with alpha-1-antitrypsin deficiency. An additional 7 subjects had pathogenic or likely pathogenic variants, 2 in CFTR and 5 in SERPINA1.

Conclusion: These findings may be clinically actionable for the providers caring for these patients. Importantly, this study highlights feasibility and challenges for future implications of this approach.