A method for extracting electronic patient record data from practice management software systems used in veterinary practice. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Jones-Diette, Julie; Brennan, Marnie; Cobb, Malcolm; Doit, Hannah; Dean, Rachel
• Is Part Of: BMC veterinary research. Volume 12:Issue 1(2016)
• Page Start: 1
• Page End: 7
• Publication Date: 2016-12
• Subjects: Electronic patient records -- Extensible mark-up language -- Accuracy; Veterinary medicine -- Research -- Periodicals; Veterinary medicine -- Periodicals; 636.0890724
• DOI: 10.1186/s12917-016-0861-y
• Languages: English
• ISSNs: 1746-6148

Abstract

Abstract Background Data extracted from electronic patient records (EPRs) within practice management software systems are increasingly used in veterinary research. The use of real patient data gives the potential to generate research that can readily be applied to clinical practice. The use of veterinary EPRs for research in the United Kingdom is hindered by the number of different Practice Management System (PMS) providers used by practices, as obtaining and combining data from different systems electronically can be problematic. The use of extensible mark up language (XML) to extract clinical data for research would potentially resolve the compatibility issues between systems. The aim of this study was to establish and validate a method for the extraction of small animal patient records from a veterinary PMS that could potentially be used across multiple systems. An XML schema was designed to extract clinical information from EPRs. The schema was tested and validated in a test system, and was then tested in a real small animal practice where data was extracted for 16 weeks. A 10 % sample of the extracted records was then compared to paper copies provided by the practice. Results All 21 fields encoded by the XML schema, from all of the records in the test system, were extracted with 100 % accuracy. Over the 18 week data collection period 4946 records, from 1279 patients, were extracted from the small animal practice. The 10 % printed records checked and compared with the XML extracted records demonstrated all required data was present. No unrequired, sensitive information e.g. costs or services/products or personal client information was extracted. Conclusions This is the first time a method for data extraction from EPRs in veterinary practice using an XML schema has been reported in the United Kingdom. This is an efficient and accurate way of extracting data which could be applied to all PMSs nationally and internationally.