Use of Medicare hospital and physician data to assess breast cancer incidence
Use of Medicare hospital and physician data to assess breast cancer incidence
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DOI：
10.1097/00005650-199905000-00004
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发表时间：
1999-05-01
期刊：
影响因子：
3
通讯作者：
Lynch, CF
中科院分区：
文献类型：
--
作者：
Warren, JL;Feuer, E;Lynch, CF
目标.健康声明数据有可能成为廉价、及时和具有全国代表性的癌症信息来源。本研究探讨了医疗保险医院和医生的数据作为一个独立的来源，以确定事件乳腺癌病例的效用。数据来自医疗保险和国家癌症研究所的SEER癌症登记处。从1992年起，对居住在SEER州的妇女（n = 659，260），医疗保险医院和医生索赔进行了审查，以确定索赔中诊断为乳腺癌的妇女（n = 6，784）。这些妇女与SEER数据中1992年被诊断为乳房慢跑的妇女（n = 3，230）相匹配。计算医疗保险数据的敏感性、特异性和阳性预测值（PPV），使用Logistic回归模型来识别报告给医疗保险的癌症相关程序，这些程序可以区分真实病例和假阳性病例。纳入这些模型的预测值，以创建灵敏度与假阳性率和灵敏度与PPV. MTS的曲线。医疗保险医院数据的敏感性为62%，特异性为99.9%，PPV为88%。医生声称灵敏度提高了14%，特异性为99.4%，PPV为10%。纳入额外的癌症相关诊断和程序提高了区分真病例与假阳性的能力，尽管假阳性病例的数量仍然很高。总体而言，医疗保险数据评估乳腺癌发病率的潜力有限，主要是因为敏感性低和PPV差。医疗保险数据可能有助于确定接受选定乳腺癌治疗的妇女。此外，这些数据可用于帮助登记处集中病例发现工作，特别是对于接受癌症相关治疗的人。
OBJECTIVES. Health claims data have the potential of being an inexpensive, timely, and nationally representative source of information about cancer. This study examined the utility of Medicare hospital and physician data as an independent source to identify incident breast cancer cases.METHODS. Data came from Medicare and the National Cancer Institute's SEER cancer registries. From 1992, for women residing in the SEER states (n = 659,260), Medicare hospital and physician claims were reviewed to identify women with a breast cancer diagnosis on a claim (n = 6,784). These women were matched with women in the SEER data who had been diagnosed with breast canter in 1992 (n = 3,230). The sensitivity, specificity, and positive predictive value (PPV) of the Medicare data were calculated Logistic regression models were used to identified cancer related procedures reported to Medicare that could distinguish true cases from false positive cases. Predicted values from these models were included to create plots of sensitivity versus false positive rates and sensitivity versus PPV.RESULTS. Medicare hospital data had 62% sensitivity, 99.9% specificity, and 88% PPV. Physician claims increased sensitivity by 14%, with specificity of 99.4%, and a PPV of 10%. Inclusion of additional cancer related diagnoses and procedures improved the ability to distinguish true cases from false positives, although the number of false positive cases remained high.CONCLUSIONS. The Medicare data overall offer limited potential to assess breast cancer incidence, largely because of low sensitivity and poor PPV. The Medicare data may have utility to identify women undergoing selected breast cancer treatments. In addition, the data may be used to help registries focus case-finding efforts, particularly for persons undergoing cancer related treatments.