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Secondary databases in equine research

data quality and disease measurements

Penell, Johanna (2009). Secondary databases in equine research. Diss. (sammanfattning/summary) Uppsala : Sveriges lantbruksuniv., Acta Universitatis Agriculturae Sueciae, 1652-6880 ; 2009:59
ISBN 978-91-576-7406-7
[Doctoral thesis]

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Knowledge on disease occurrence in the Swedish equine population is lacking. Secondary data (data not produced primarily for research) including medical information offer potential to investigate disease occurrence in populations without primary data collection. This thesis explored the potential use of two nation-wide secondary equine databases for research on diseases in the Swedish horse population. The data quality in one insurance database and one database from a national equine clinic network was evaluated. For diagnostic information, the agreement in insurance data was 84% whereas the completeness (proportion of problems in the clinical records recorded in the database) and correctness (proportion of recorded disease events in the database truly occurring) of clinic data was 91% and 92%, respectively. Logistic regression showed that agreement/correctness was significantly associated with type of visit (clinic data and veterinary care claims in insurance data), whether diagnostic codes were present in the clinical record and affected system (clinic data). To present disease occurrence in the respective study populations, disease was presented as incidence rates (insurance data) and proportional morbidities (both databases). For insurance data, the most commonly affected system was joints, followed by whole body, skin and digestive system. The most common specific diagnosis was fetlock inflammation. For clinic data 22% of all visits were health visits, and for problems visits, the most commonly affected body system was joints, followed by whole body, respiratory and skeleton system. For both databases, disease occurrence was highly related to demographic factors in the horse population. The data quality in both databases was found adequate for research purposes, with due consideration of variation in data quality among disease problems. Presentation of disease indices from the two databases provided useful information on disease occurrence in horses throughout Sweden. Importantly however, as many factors affect disease, results from other studies are not directly applicable to Sweden. Thus disease statistics need be obtained from the specific population of interest.

Authors/Creators:Penell, Johanna
Title:Secondary databases in equine research
Subtitle:data quality and disease measurements
Series Name/Journal:Acta Universitatis Agriculturae Sueciae
Year of publishing :2009
Number of Pages:75
ALLI Penell JC, Egenvall A, Bonnett BN, Pringle J. (2007). Validation of computerized Swedish horse insurance data against veterinary clinical records. Preventive Veterinary Medicine 82, 236-251. II Penell JC, Egenvall A, Bonnett BN, Pringle J. (2005). Specific causes of morbidity among Swedish horses insured for veterinary care between 1997 and 2000. Veterinary Record 157, 470-477. III Penell JC, Bonnett BN, Pringle J, Egenvall A. Validation of computerized diagnostic information in a clinic database from a national equine clinic network (submitted manuscript). IV Penell JC, Egenvall A, Bonnett BN, Pringle J. Health events in Swedish horses based on data from a national equine clinic network (manuscript). Papers I-II are reproduced with the kind permission of the publishers
Place of Publication:Uppsala
Publisher:Dept of Clinical Sciences, Swedish University of Agricultural Sciences
Associated Programs and Other Stakeholders:SLU - Research Areas for the Future > Future Animal Health and Welfare (until Jan 2017)
ISBN for printed version:978-91-576-7406-7
Publication Type:Doctoral thesis
Full Text Status:Public
Agrovoc terms:horses, data collection, data analysis, measurement, insurance, evaluation, diagnosis, animal diseases, sweden
Keywords:secondary data, equine, insurance data, clinic data, data quality, validation, agreement, completeness, correctness, disease measurements, logistic regression
Permanent URL:
ID Code:2119
Faculty:VH - Faculty of Veterinary Medicine and Animal Science
Department:(VH) > Dept. of Clinical Sciences
Deposited By: Johanna Penell
Deposited On:06 Oct 2009 00:00
Metadata Last Modified:02 Dec 2014 10:16

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