Do GPs know their patients with cancer? Assessing the quality of cancer registration in Dutch primary care:a cross-sectional validation study

Objectives: To assess the quality of cancer registry in primary care. Design and setting: A cross-sectional validation study using linked data from primary care electronic health records (EHRs) and the Netherlands Cancer Registry (NCR). Population: 290 000 patients, registered with 120 general practitioners (GPs), from 50 practice centres in the Utrecht area, the Netherlands, in January 2013. Intervention: Linking the EHRs of all patients in the Julius General Practitioners' Network database at an individual patient level to the full NCR (similar to 1.7 million tumours between 1989 and 2011),... Mehr ...

Verfasser: Sollie, Annet
Roskam, Jessika
Sijmons, Rolf H.
Numans, Mattijs E.
Helsper, Charles W.
Dokumenttyp: Artikel
Erscheinungsdatum: 2016
Reihe/Periodikum: Sollie , A , Roskam , J , Sijmons , R H , Numans , M E & Helsper , C W 2016 , ' Do GPs know their patients with cancer? Assessing the quality of cancer registration in Dutch primary care : a cross-sectional validation study ' , BMJ Open , vol. 6 , no. 9 , 012669 . https://doi.org/10.1136/bmjopen-2016-012669
Schlagwörter: ELECTRONIC MEDICAL-RECORDS / CLINICAL-RESEARCH / DIAGNOSIS / COMPLETENESS / MORTALITY / VALIDITY / DATABASE
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-26671530
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://hdl.handle.net/11370/ad399e6b-16fc-4e8b-9ca7-ddc84423d36f

Objectives: To assess the quality of cancer registry in primary care. Design and setting: A cross-sectional validation study using linked data from primary care electronic health records (EHRs) and the Netherlands Cancer Registry (NCR). Population: 290 000 patients, registered with 120 general practitioners (GPs), from 50 practice centres in the Utrecht area, the Netherlands, in January 2013. Intervention: Linking the EHRs of all patients in the Julius General Practitioners' Network database at an individual patient level to the full NCR (similar to 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. Main outcome measures: 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. Results: 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. Conclusions: 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.