Limitations of electronic databases: a caution

The purpose of this study was to assess the completeness and accuracy of information from two electronic datasets, one of which is voluntarily submitted, the other submitted by mandate.

Emergency department (ED) data have been voluntarily submitted by several hospitals to the Kentucky Emergency Medical Services Information System (KEMSIS). Similar information on all patients admitted to the hospital has been submitted by mandate to the state under the Uniform Billing Act (UB92). UB92 data for patients with at least one diagnosis code > or = 800 were available. The KEMSIS and UB 92 data for one hospital were compared to those manually abstracted from the ED log and medical records for completeness and accuracy.

There were 316 patients listed on the ED log that were subsequently admitted to the hospital. The KEMSIS database contained 266 (84%) of these records, but only 91 (34%) were classified as having been admitted. Of those correctly classified as admitted, only 25 (27%, or 9% of the total 266) were correctly classified as to the hospital of admission (directly to hospital or transferred to another facility). Discharge diagnoses in the KEMSIS database and hospital records were concordant in 240 (90%) of the patients, even for those misclassified as to disposition. There were 37 patients listed in the ED log admitted during the study period with at least one discharge diagnosis field > or = 800. Eight patients were transferred to another institution, making the total population available for study period 29. Only eight (28%) of these patients were included in the UB92 database. The diagnosis codes were concordant between the UB 92 data and ED log in all cases.

There is significant misclassification and/or omission in electronic databases. This is true regardless of whether data is reported voluntarily or by mandate. Electronic data must be independently validated before they are used for policy or research purposes.