Schifano Patrizia, Papini Paolo, Agabiti Nera, Scarinci Marina, Borgia Piero, Perucci Carlo A
Department of Epidemiology, Health Local Unit RME, Rome, Italy.
BMC Public Health. 2006 Feb 7;6:25. doi: 10.1186/1471-2458-6-25.
Administrative data can serve as an easily available source for epidemiological and evaluation studies. The aim of this study is to evaluate the use of hospital administrative data to determine breast cancer severity and the appropriateness of surgical treatment.
the study population consisted of 398 patients randomly selected from a cohort of women hospitalized for first-time breast cancer surgery in the Lazio Region, Italy. Tumor severity was defined in three different ways: 1) tumor size; 2) clinical stage (TNM); 3) severity indicator based on HIS data (SI). Sensitivity, specificity, and positive predictive value (PPV) of the severity indicator in evaluating appropriateness of surgery were calculated. The accuracy of HIS data was measured using Kappa statistic.
Most of 387 cases were classified as T1 and T2 (tumor size), more than 70% were in stage I or II and the SI classified 60% of cases in medium-low category. Variation from guidelines indications identified under and over treatments. The accuracy of the SI to predict under-treatment was relatively good (58% of all procedures classified as under-treatment using pT where also classified as such using SI), and even greater predicting over-treatment (88.2% of all procedures classified as over treatment using pT where also classified as such using SI). Agreement between clinical chart and hospital discharge reports was K = 0.35.
Our findings suggest that administrative data need to be used with caution when evaluating surgical appropriateness, mainly because of the limited ability of SI to predict tumor size and the questionable quality of HIS data as observed in other studies.
行政数据可作为流行病学和评估研究的便捷可用来源。本研究旨在评估利用医院行政数据确定乳腺癌严重程度及手术治疗适宜性的情况。
研究人群包括从意大利拉齐奥地区因首次乳腺癌手术住院的女性队列中随机选取的398例患者。肿瘤严重程度通过三种不同方式定义:1)肿瘤大小;2)临床分期(TNM);3)基于医院信息系统(HIS)数据的严重程度指标(SI)。计算严重程度指标在评估手术适宜性方面的敏感性、特异性和阳性预测值(PPV)。使用Kappa统计量测量HIS数据的准确性。
387例病例中大多数被归类为T1和T2期(肿瘤大小),超过70%处于I期或II期,SI将60%的病例归类为中低类别。与指南指征存在差异,发现了治疗不足和治疗过度的情况。SI预测治疗不足的准确性相对较好(所有使用pT分类为治疗不足的手术中,58%也被SI分类为治疗不足),预测治疗过度的准确性更高(所有使用pT分类为治疗过度的手术中,88.2%也被SI分类为治疗过度)。临床病历与医院出院报告之间的一致性K = 0.35。
我们的研究结果表明,在评估手术适宜性时需谨慎使用行政数据,主要是因为SI预测肿瘤大小的能力有限,以及如其他研究所观察到的HIS数据质量存疑。