Contiero Paolo, Tittarelli Andrea, Maghini Anna, Fabiano Sabrina, Frassoldi Emanuela, Costa Enrica, Gada Daniela, Codazzi Tiziana, Crosignani Paolo, Tessandori Roberto, Tagliabue Giovanna
Cancer Registry Division, Istituto Nazionale per lo Studio e la Cura dei Tumori, Via Venezian 1, 20133 Milan, Italy.
J Biomed Inform. 2008 Feb;41(1):24-32. doi: 10.1016/j.jbi.2007.03.003. Epub 2007 Mar 21.
Automated software for cancer registration, called Open Registry and developed by ourselves was adopted by the Varese (population-based) Cancer Registry starting from 1997. Since the use of automated cancer registration is increasing, it is important to assess the quality and completeness of the automated data being produced. In this study, we assessed the completeness of the automatically generated data by comparison with a gold standard of all cases identified by manual and automatic systems for the year 1997 when the automated system was introduced, and the manual system was still in operation. We also evaluated the efficiency of the automated system. 5027 cases were generated automatically; 2959 (59%) were accepted automatically and 2068 (41%) were flagged for manual checking. Sixty-nine cases (1.3%) were not recorded automatically, the most common reason (0.8%) being that the incidence record was dated 1998, even though the case was incident in 1997. A total of 98.7% of all cases found were picked up by the automated system. A completeness figure of 98.7% indicates that the automatic procedure is a valid alternative to manual methods for routine case generation. The fact that 59% of cases were registered automatically indicates that the system can speed up data production and enhance registry efficiency.
我们自行开发的名为Open Registry的癌症登记自动化软件自1997年起被瓦雷泽(基于人群)癌症登记处采用。由于自动化癌症登记的使用正在增加,评估所产生的自动化数据的质量和完整性非常重要。在本研究中,我们通过与1997年(引入自动化系统且手动系统仍在运行时)手动和自动系统识别出的所有病例的金标准进行比较,评估了自动生成数据的完整性。我们还评估了自动化系统的效率。自动生成了5027个病例;2959个(59%)被自动接受,2068个(41%)被标记以供人工检查。69个病例(1.3%)未被自动记录,最常见的原因(0.8%)是发病记录日期为1998年,尽管该病例实际发病于1997年。自动系统发现了所有病例中的98.7%。98.7%的完整性数字表明,对于常规病例生成,自动程序是手动方法的有效替代方案。59%的病例被自动登记这一事实表明,该系统可以加快数据生成速度并提高登记效率。