Sollie Annet, Roskam Jessika, Sijmons Rolf H, Numans Mattijs E, Helsper Charles W
Department of General Practice & Elderly Care Medicine, VU University Medical Centre, Amsterdam, The Netherlands Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands.
Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands.
BMJ Open. 2016 Sep 15;6(9):e012669. doi: 10.1136/bmjopen-2016-012669.
To assess the quality of cancer registry in primary care.
A cross-sectional validation study using linked data from primary care electronic health records (EHRs) and the Netherlands Cancer Registry (NCR).
290 000 patients, registered with 120 general practitioners (GPs), from 50 practice centres in the Utrecht area, the Netherlands, in January 2013.
Linking the EHRs of all patients in the Julius General Practitioners' Network database at an individual patient level to the full NCR (∼1.7 million tumours between 1989 and 2011), to determine the proportion of matching cancer diagnoses. Full-text EHR extraction and manual analysis for non-matching diagnoses.
Proportions of matching and non-matching breast, lung, colorectal and prostate cancer diagnoses between 2007 and 2011, stratified by age category, cancer type and EHR system. Differences in year of diagnosis between the EHR and the NCR. Reasons for non-matching diagnoses.
In the Primary Care EHR, 60.6% of cancer cases were registered and coded in accordance with the NCR. Of the EHR diagnoses, 48.9% were potentially false positive (not registered in the NCR). Results differed between EHR systems but not between age categories or cancer types. The year of diagnosis corresponded in 80.6% of matching coded diagnoses. Adding full-text EHR analysis improved results substantially. A national disease registry (the NCR) proved incomplete.
Even though GPs do know their patients with cancer, only 60.6% are coded in concordance with the NCR. Reusers of coded EHR data should be aware that 40% of cases can be missed, and almost half can be false positive. The type of EHR system influences registration quality. If full-text manual EHR analysis is used, only 10% of cases will be missed and 20% of cases found will be wrong. EHR data should only be reused with care.
评估初级保健中癌症登记的质量。
一项横断面验证研究,使用来自初级保健电子健康记录(EHR)和荷兰癌症登记处(NCR)的关联数据。
2013年1月,荷兰乌得勒支地区50个医疗中心的290000名患者,他们在120名全科医生(GP)处登记。
在个体患者层面将朱利叶斯全科医生网络数据库中所有患者的EHR与完整的NCR(1989年至2011年间约170万个肿瘤)相链接,以确定匹配癌症诊断的比例。对不匹配的诊断进行全文EHR提取和人工分析。
2007年至2011年间,按年龄类别、癌症类型和EHR系统分层的乳腺癌、肺癌、结直肠癌和前列腺癌匹配和不匹配诊断的比例。EHR和NCR之间诊断年份的差异。不匹配诊断的原因。
在初级保健EHR中,60.6%的癌症病例按照NCR进行了登记和编码。在EHR诊断中,48.9%可能为假阳性(未在NCR中登记)。结果因EHR系统而异,但在年龄类别或癌症类型之间没有差异。80.6%的匹配编码诊断的诊断年份一致。添加全文EHR分析显著改善了结果。一个国家疾病登记处(NCR)被证明是不完整的。
尽管全科医生确实了解他们的癌症患者,但只有60.6%按照NCR进行编码。EHR编码数据的再使用者应意识到40%的病例可能会被遗漏,近一半可能为假阳性。EHR系统的类型会影响登记质量。如果使用全文人工EHR分析,只有10%的病例会被遗漏,发现的病例中有20%是错误的。EHR数据只能谨慎地再使用。