Narrative electronic patient records as source of discharge diagnoses.
OBJECTIVE
To evaluate the consistency of diagnostic data extracted from narrative electronic patient record (EPR) notes compared with the data from a patient administrative system (PAS). To assess potential benefit of using EPR notes as source of diagnosis data and as basis for case identification.


METHODS
Construction of a computer algorithm to extract ICD-9 codes from narrative EPR notes. Assessment of consistency and reliability of the diagnostic codes retrieved from EPR notes and PAS. Estimation of efficiency of case identification based on data from PAS and EPR.


RESULTS
Diagnosis codes were retrieved from PAS with sensitivity of 0.989 and the positive predictive value (PPV) was 0.993. Codes were retrieved from EPR with sensitivity of 0.908 and PPV of 0.990. Combining these two sources increased sensitivity to 0.999.


CONCLUSIONS
Discharge diagnoses were easily extracted from narrative EPR notes by automatic methods. Information extracted from record notes was not significantly different from the corresponding data in PAS, but EPR was incomplete as compared with PAS. Utilizing data extracted from EPR improved case identification significantly.
Mikkelsen
Gustav
G
Department of Clinical Neurosciences, The Norwegian University of Science and Technology, St. Olavs Hospital, 7006 Trondheim, Norway. gustav.mikkelsen@medisin.ntnu.no
Aasly
Jan
J
D000465:Algorithms; D003933:Diagnosis; D038801:International Classification of Diseases; D016347:Medical Records Systems, Computerized; D010351:Patient Discharge