Data quality in the Norwegian dairy herd recording system: agreement between the national database and disease recording on farm.

The majority of herds in Norway participate in the national dairy herd recording system. For disease events, this involves transferring information registered on farm, using individual cow health cards (CHC), to the central cattle database (CCD). Before using data from such a database, validation with an aim of describing data quality should be performed, but is rarely done. In this study, diagnostic events from CHC and CCD from 74 dairy herds were compared. Events in 2008 from female cattle with minimum age of 1 yr were included (n=1,738). Discrepancies between the 2 data sources and assessment of data quality were evaluated using agreement between events on CHC and in CCD, calculating completeness and correctness for the CCD, and using a multivariable regression model for agreement (1/0). The agreement evaluation described the concordance between the 2 data sources, whereas the calculations of completeness and correctness depended on a reference data source assumed to be more reliable. Completeness of the CCD was defined as the proportion of diagnostic events on the CHC that was recorded therein. Correctness was defined as the proportion of the CCD events that was also recorded on the CHC, and with the same date and diagnostic code. The agreement was up to 87.5%, the majority of disagreement being caused by unreported events on the CHC (between 10 and 12% of all events). Completeness of the CCD was regarded as high, between 0.87 and 0.88, and correctness excellent, between 0.97 and 0.98. The multivariable regression model found 4 factors that increased the odds for diagnostic events being in agreement between CHC and CCD. These were the events occurring during the 305-d lactation period; the herd size being 75 cows or less; the event occurring during the spring, summer, or winter rather than autumn; and lastly, the diagnostic code for the disease event being preprinted on the CHC, involving a simple check mark as opposed to writing a 3-digit code. The model found a high degree of clustering within herd. In conclusion, disease data in the Norwegian national database for dairy cows are valid to use for epidemiologic research, having in particular an excellent correctness, but it is of concern that at least 10% of data are missing. The proportion of unreported data should be taken into consideration whenever data from this database are used. Reasons for discrepancies found are important to be aware of in any work aiming to improve data transfer from farm to central databases.

Validation of Nordic dairy cattle disease recording databases--completeness for locomotor disorders.

The Nordic countries Denmark (DK), Finland (FIN), Norway (NO) and Sweden (SE) all have unique national databases holding the disease records of dairy cows. The objective of this study was to estimate and compare completeness for locomotor disorders in the four Nordic national databases. Completeness figures for farmer-recorded disease events were calculated on two different levels: the first refers to disease events that were observed on the farm regardless of whether a veterinarian had been involved (FARMER); the second refers to farmer records of cases attended by a veterinarian, i.e. to veterinarian-treated disease events (VET). A sample of herds with 15 or more cows was obtained from a simple random sample of dairy farms in FIN, NO and SE, and from a systematic random sample in DK. There were 105, 167, 179 and 129 participating farmers in DK, FIN, NO and SE, respectively, and during two 2-month periods in 2008 these farmers recorded the disease events they observed on the farm. Data from the four national databases were extracted in May 2009. The two data sources, farmer recordings and national databases, were managed in a comparable way in all four countries, and common diagnostic codes were created and added to match recordings appearing in both datasets. In all 555 farmers completed data records in the first data-recording period, and 515 farmers did so in the second period. In DK, FIN, NO and SE, 55%, 77%, 82% and 75%, participating farmers completed the recordings during the first recording period, respectively; the corresponding figures for the second recording period were 71%, 82%, 83% and 91%. To calculate completeness, disease cases recorded in the national databases were compared with the farmer recordings using an exact match for the locomotor complex defined as same country, herd identification number (id), cow id, and event date at the levels of FARMER and VET. Completeness at FARMER level were 0.22, 0.21, 0.23 and 0.12 in DK, FIN, NO and SE, respectively. At VET level they were 0.37, 0.27, 0.34 and 0.17. To compare differences in completeness between countries exact 95% confidence intervals were calculated. There were significant differences in completeness between DK and SE at both FARMER and VET level. The completeness indicate that the ability to estimate true disease occurrences in the four national databases varies and is in general poor. Completeness should be taken into account when disease occurrences in different countries are compared.

Completeness of metabolic disease recordings in Nordic national databases for dairy cows.

The four Nordic countries Denmark (DK), Finland (FI), Norway (NO) and Sweden (SE) all have national databases where diagnostic events in dairy cows are recorded. Comparing and looking at differences in disease occurrence between countries may give information on factors that influence disease occurrence, optimal diseases control and treatment strategies. For such comparisons to be valid, the data in these databases should be standardised and of good quality. The objective of the study presented here was to assess the quality of metabolic disease recordings, primarily milk fever and ketosis, in four Nordic national databases. Completeness of recording figures of database registrations at two different levels was chosen as a measure of data quality. Firstly, completeness of recording of all disease events on a farm regardless of veterinary involvement, called 'Farmer observed completeness', was determined. Secondly, completeness of recording of veterinary treated disease events only, called 'Veterinary treated completeness', was determined. To collect data for calculating these completeness levels a simple random sample of herds was obtained in each country. Farmers who were willing to participate, recorded for 4 months in 2008, on a purpose made registration form, any observed illness in cows, regardless of veterinary involvement. The number of participating herds was 105, 167, 179 and 129 in DK, FI, NO and SE respectively. In total these herds registered 247, 248, 177 and 218 metabolic events for analysis in DK, FI, NO and SE, respectively. Data from national databases were subsequently extracted, and the two sources of data were matched to find the proportion, or completeness, of diagnostic events registered by farmers that also existed in national databases. Matching was done using a common diagnostic code system and allowed for a discrepancy of 7 days for registered date of the event. For milk fever, the Farmer observed completeness was 77%, 67%, 79% and 79%, and for Veterinary treated completeness 88%, 71%, 80% and 82%, in DK, FI, NO and SE, respectively. For ketosis, the Farmer observed completeness was 77%, 55%, 70% and 46%, and for Veterinary treated completeness 84%, 75%, 79% and 56%, in DK, FI, NO and SE, respectively. The differences observed in some of these completeness figures indicate that metabolic disease frequency measures when calculated from these four national databases do not accurately reflect the true difference in metabolic disease occurrence in dairy cows between countries. Further standardisation of disease registrations is necessary for valid between-country assessments.