Extraction of Electronic Health Record Data in a Hospital Setting: Comparison of Automatic and Semi-Automatic Methods Using Anti- TNF Therapy as Model.

There is limited experience and methods for extractions of drug therapy data from electronic health records ( EHR) in the hospital setting. We have therefore developed and evaluated completeness and consistency of an automatic versus a semi-automatic extraction procedure applied on prescribing and administration of the TNF inhibitor infliximab using a hospital EHR system in Karolinska University Hospital, Sweden. Using two different extraction methods (automatic and semi-automatic), all administered infusions of infliximab between 2007 and 2010 were extracted from a database linked to the EHR system. Extracted data included encrypted personal identity number ( PIN), date of birth, sex, time of prescription/administration, healthcare units, prescribed/administered dose and time of admission/discharge. The primary diagnosis ( ICD-10) for the treatment with infliximab was extracted by linking infliximab infusions to their corresponding treatment episode. A total of 13,590 infusions of infliximab were administered during the period of 2007 to 2010. Of those were 13,531 (99.6%) possible to link to a corresponding treatment episode, and a primary diagnosis was extracted for 13,530 infusions. Information on encrypted PIN, date of birth, time of prescription/administration, time of admission/discharge and healthcare unit was complete. Information about sex was missing in one patient only. Calculable information about dosage was extracted for 13,300 (98.3%) of all linked infusions. This methodological study showed the potential to extract drug therapy data in a hospital setting. The semi-automatic procedure produced an almost complete pattern of demographics, diagnoses and dosages for the treatment with infliximab. [ABSTRACT FROM AUTHOR]