Penell Johanna C, Egenvall Agneta, Bonnett Brenda N, Pringle John
Department of Clinical Sciences, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, P.O. Box 7054, SE-750 07 Uppsala, Sweden.
Prev Vet Med. 2007 Dec 14;82(3-4):236-51. doi: 10.1016/j.prevetmed.2007.05.020. Epub 2007 Jul 17.
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.
目的是评估瑞典一个大型马匹保险数据库中的计算机化保险数据与相应临床记录（CR）中的信息之间的一致性。纳入了400例兽医护理和140例生命索赔的随机样本。比较了不同来源之间关于马匹名称、品种和性别、出生年份、具体诊断和系统诊断（如关节、消化系统和骨骼系统）的信息。人口统计学变量的一致性分为一致、不一致或数据缺失。对于诊断信息，类别为一致、轻微不一致和严重不一致，对于系统信息为一致或不一致。CR中存在人口统计学信息的缺失值，从名称的2%到品种的16%不等。人口统计学信息的总体一致性>94%（不考虑缺失数据），系统一致性为92%，具体诊断一致性为84%。对于兽医护理和生命索赔，观察到的诊断一致性分别为85%和83%，轻微不一致为6%和5%，严重不一致为9%和12%。以CR数据作为金标准，对于评估的系统（关节、消化系统、骨骼系统、皮肤和蹄部），敏感性在62%（皮肤）至89%（消化系统）之间变化，而所有系统的特异性均>96%。阳性预测值范围从86%（皮肤）到97%（消化系统）。采用逻辑回归分析来检查与诊断一致性相关的因素。分别对兽医护理和生命索赔进行分析。检查的因素包括就诊类型（诊所/现场）、治疗兽医/诊所（分为地区兽医、私人执业者、小型诊所、中型诊所，对于索赔≥20例的诊所，为具体诊所）、计算机化或手动CR、处理人员、CR是否包含在纸质文件中、索赔是否被拒绝或报销、系统诊断以及纸质文件中是否包含即时结算（在兽医护理索赔分析中）或死亡证明（在生命索赔分析中）。对于兽医护理索赔，在逻辑回归模型中，就诊类型与一致性显著相关，诊所就诊产生的一致性优于现场就诊。
