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Validation of a national disease recording system for dairy cattle against veterinary practice records
M Jansson Mörk1, C Wolff, A Lindberg
1Department of Clinical Sciences, Swedish University of Agricultural Sciences, P.O. Box 7019, SE-750 07 Uppsala, Sweden. marie.mork@kv.slu.se
Abstract:
In Sweden, morbidity in dairy cattle is monitored through a national disease recording system. This system gives valuable information for research as well as advisory work and genetic evaluation. Our main objective was to evaluate the completeness in the disease recording system. Farm copies of veterinary records (n=851) from 112 herds, from March 2003 to April 2004, were compared with the information registered in the recording system. The evaluation of completeness was performed at two stages: (i) in the raw data transferred from the Swedish Board of Agriculture (SBA) to the Swedish Dairy Association (for records, cases and diagnostic events) and (ii) in the dairy disease database (DDD) at the Swedish Dairy Association (for diagnostic events). The evaluation was stratified by record type: manual and computerized records from state-employed veterinarians and private veterinarians, respectively. The completeness was high both for records (95-100%) and cases (90-99%) except manual records from private veterinarians (76% for records and 74% for cases). The overall completeness for diagnostic events was 75% in the DDD, with significant differences between record types. For all record types other than manual records from private veterinarians, the majority of diagnostic events lost disappeared after registration in the raw data from the SBA. The reasons for loss found suggest that there is potential for improvement. A multilevel logistic regression analysis showed that the completeness of diagnostic events in the DDD depended on region, diagnosis and veterinary employment. The random effect of veterinarian accounted for 35% of the modeled variation. Future studies are needed to assess how the differential misclassification affect estimates based on the data, and how to account for it.
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