Leung K M, Hasan A G, Rees K S, Parker R G, Legorreta A P
Quality Initiatives Division, Foundation Health Systems, Woodland Hills, California 91367, USA.
J Clin Epidemiol. 1999 Jan;52(1):57-64. doi: 10.1016/s0895-4356(98)00143-7.
The objectives of this study were to validate a claims-based algorithm for identification of patients with newly diagnosed carcinoma of the breast and to optimize the algorithm. Claims data from all females aged 21 years or older who enrolled in a large California health maintenance organization during the study period from October 1, 1994 through March 31, 1996 were analyzed. Medical records of the patients identified through the claims-based algorithm were reviewed to determine whether the patients were correctly identified. The initial algorithm had a positive predictive value of 84% which was similar to the previous study. The percentages of correct identification significantly increased with the patient's age at diagnosis. Other patient demographic characteristics and facility characteristics were not related to the accuracy of the identification. Using a classification tree procedure and additional information from the false-positive cases, the initial algorithm was modified for improvement. The best-modified algorithm had a positive predictive value of 92% while only 0.5% (4/837) of the true-positive cases were excluded. The results once again demonstrated that patients with newly diagnosed carcinomas of the breast can be identified using claims data. These databases provide an efficient and effective tool for performing health services studies on large patient populations.
本研究的目的是验证一种基于索赔数据的算法,用于识别新诊断出的乳腺癌患者,并对该算法进行优化。分析了在1994年10月1日至1996年3月31日研究期间,加入加利福尼亚州一家大型健康维护组织的所有21岁及以上女性的索赔数据。对通过基于索赔数据的算法识别出的患者的病历进行审查,以确定这些患者是否被正确识别。初始算法的阳性预测值为84%,与之前的研究相似。正确识别的百分比随着患者诊断时的年龄显著增加。其他患者人口统计学特征和医疗机构特征与识别准确性无关。使用分类树程序和来自假阳性病例的额外信息,对初始算法进行修改以改进。最佳修改算法的阳性预测值为92%,而仅0.5%(4/837)的真阳性病例被排除。结果再次表明,使用索赔数据可以识别新诊断出的乳腺癌患者。这些数据库为对大量患者群体进行卫生服务研究提供了一个高效且有效的工具。