Validation of computerized Swedish horse insurance data against veterinary clinical records.

The aim was to evaluate the agreement between computerized insurance data in a large Swedish horse insurance database and the information in the corresponding clinical records (CR). A random sample of 400 veterinary care and 140 life claims was included. Information on name of the horse, breed and gender, year of birth, specific diagnosis and system diagnosis (e.g. joints, digestive and skeletal) was compared between sources. The concordance for demographic variables was categorized as agreement, disagreement or data missing. For diagnostic information, the categories were agreement, minor disagreement and major disagreement and for system information agreement or disagreement. There were missing values for demographic information in the CR, varying from 2% for name to 16% for breed. The overall agreement for demographic information was >94% (disregarding missing data), 92% for system and 84% for specific diagnosis. For veterinary care and life claims, the observed agreement for diagnosis was 85 and 83%, minor disagreement 6 and 5%, and major disagreement 9 and 12%, respectively. Using the CR data as gold standard, for the systems evaluated (joints, digestive, skeletal, skin and hooves), sensitivity varied between 62% (skin) and 89% (digestive) whereas the specificity was >96% for all systems. The positive predictive values ranged from 86% (skin) to 97% (digestive). Logistic regression analysis was used to examine factors associated with agreement for diagnosis. Analyses were performed separately for veterinary care and life claims. Factors examined were type of visit (clinic/field), treating veterinarian/clinic (categorized as district veterinarians, private practitioners, small clinics, medium clinics and, for the clinics with > or =20 claims, the specific clinics), computerized or manual CR, processing clerk, whether the CR was included in the paper file, if the claim was rejected or reimbursed, system diagnosis and if a immediate settlement (in analysis for veterinary care claims) or death certificate (in analysis for life claims) was included in the paper file. For veterinary care claims, in the logistic regression model type of visit was significantly associated with agreement, with clinic visits generating better agreement than field visits.

Traffic-related air pollution exposure and incidence of stroke in four cohorts from Stockholm.

We investigated the risk of stroke related to long-term ambient air pollution exposure, in particular the role of various exposure time windows, using four cohorts from Stockholm County, Sweden. In total, 22,587 individuals were recruited from 1992 to 2004 and followed until 2011. Yearly air pollution levels resulting from local road traffic emissions were assessed at participant residences using dispersion models for particulate matter (PM10) and nitrogen oxides (NOX). Cohort-specific hazard ratios were estimated for time-weighted air pollution exposure during different time windows and the incidence of stroke, adjusted for common risk factors, and then meta-analysed. Overall, 868 subjects suffered a non-fatal or fatal stroke during 238,731 person-years of follow-up. An increment of 20 µg/m(3) in estimated annual mean of road-traffic related NOX exposure at recruitment was associated with a hazard ratio of 1.16 (95% CI 0.83-1.61), with evidence of heterogeneity between the cohorts. For PM10, an increment of 10 µg/m(3) corresponded to a hazard ratio of 1.14 (95% CI 0.68-1.90). Time-window analyses did not reveal any clear induction-latency pattern. In conclusion, we found suggestive evidence of an association between long-term exposure to NOX and PM10 from local traffic and stroke at comparatively low levels of air pollution.

Validation of computerized diagnostic information in a clinical database from a national equine clinic network.

BACKGROUND: Computerized diagnostic information offers potential for epidemiological research; however data accuracy must be addressed. The principal aim of this study was to evaluate the completeness and correctness of diagnostic information in a computerized equine clinical database compared to corresponding hand written veterinary clinical records, used as gold standard, and to assess factors related to correctness. Further, the aim was to investigate completeness (epidemiologic sensitivity), correctness (positive predictive value), specificity and prevalence for diagnoses for four body systems and correctness for affected limb information for four joint diseases. METHODS: A random sample of 450 visits over the year 2002 (nvisits=49,591) was taken from 18 nation wide clinics headed under one company. Computerized information for the visits selected and copies of the corresponding veterinary clinical records were retrieved. Completeness and correctness were determined using semi-subjective criteria. Logistic regression was used to examine factors associated with correctness for diagnosis. RESULTS: Three hundred and ninety six visits had veterinary clinical notes that were retrievable. The overall completeness and correctness were 91% and 92%, respectively; both values considered high. Descriptive analyses showed significantly higher degree of correctness for first visits compared to follow up visits and for cases with a diagnostic code recorded in the veterinary records compared to those with no code noted. The correctness was similar regardless of usage category (leisure/sport horse, racing trotter and racing thoroughbred) or gender.For the four body systems selected (joints, skin and hooves, respiratory, skeletal) the completeness varied between 71% (respiration) and 91% (joints) and the correctness ranged from 87% (skin and hooves) to 96% (respiration), whereas the specificity was >95% for all systems. Logistic regression showed that correctness was associated with type of visit, whether an explicit diagnostic code was present in the veterinary clinical record, and body system. Correctness for information on affected limb was 95% and varied with joint. CONCLUSION: Based on the overall high level of correctness and completeness the database was considered useful for research purposes. For the body systems investigated the highest level of completeness and correctness was seen for joints and respiration, respectively.