Mining free-text medical records for companion animal enteric syndrome surveillance.

Anholt, R M; Berezowski, John Andrew; Jamal, I; Ribble, C; Stephen, C (2014). Mining free-text medical records for companion animal enteric syndrome surveillance. Preventive veterinary medicine, 113(4), pp. 417-422. Elsevier 10.1016/j.prevetmed.2014.01.017

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Large amounts of animal health care data are present in veterinary electronic medical records (EMR) and they present an opportunity for companion animal disease surveillance. Veterinary patient records are largely in free-text without clinical coding or fixed vocabulary. Text-mining, a computer and information technology application, is needed to identify cases of interest and to add structure to the otherwise unstructured data. In this study EMR's were extracted from veterinary management programs of 12 participating veterinary practices and stored in a data warehouse. Using commercially available text-mining software (WordStat™), we developed a categorization dictionary that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records. The diagnostic accuracy of the text-miner for retrieving cases of enteric syndrome was measured against human reviewers who independently categorized a random sample of 2500 cases as enteric syndrome positive or negative. Compared to the reviewers, the text-miner retrieved cases with enteric signs with a sensitivity of 87.6% (95%CI, 80.4-92.9%) and a specificity of 99.3% (95%CI, 98.9-99.6%). Automatic and accurate detection of enteric syndrome cases provides an opportunity for community surveillance of enteric pathogens in companion animals.

Item Type:

Journal Article (Original Article)

Division/Institute:

05 Veterinary Medicine > Research Foci > Veterinary Public Health / Herd Health Management
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) > Veterinary Public Health Institute
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH)

UniBE Contributor:

Berezowski, John Andrew

Subjects:

600 Technology > 630 Agriculture

ISSN:

0167-5877

Publisher:

Elsevier

Language:

English

Submitter:

Susanne Agnes Lerch

Date Deposited:

24 Mar 2015 14:25

Last Modified:

15 Oct 2015 09:50

Publisher DOI:

10.1016/j.prevetmed.2014.01.017

PubMed ID:

24485708

Uncontrolled Keywords:

Electronic medical record, Enteric syndrome, Informatics, Surveillance, Text-mining, Veterinary

BORIS DOI:

10.7892/boris.65564

URI:

https://boris.unibe.ch/id/eprint/65564

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