Reliability of cancer registration data in Scotland, 1997
Introduction
Population-based cancer registration is an essential part of any rational cancer control strategy [1]. The data provided by cancer registries serve a wide range of functions including public health surveillance, health service planning, evaluation of the impact of interventions on cancer incidence and survival, clinical audit, epidemiological and health services research, and provision of information for many purposes including health promotion and genetic counselling [2]. However, to fulfil all of these functions adequately, the data must be (and must be perceived to be) of high quality [3].
Cancer registration in Scotland was re-organised extensively between the years 1995 and 1997. Formerly, registration was performed by five autonomous regional registries, responsible for collecting a limited data-set, and largely reliant on the manual processing of submitted paper records. Periodically, the regional registries submitted data electronically to a national cancer registry for collation and validation. Following re-organisation, the national cancer registry assumed responsibility for all aspects of cancer registration and for extending the minimum data-set to include information on treatment and (for selected sites) stage of disease for all cases diagnosed from 1 January 1997 onwards. The mode of operation of the registry has been described in detail elsewhere [2]. Briefly, cases are now ascertained from multiple sources, electronically whenever possible, and records are linked by computerised probability matching to identify potential new registrations. Eligibility for registration is then verified by outposted staff referring to medical records; items of data which cannot currently be captured electronically are also abstracted at this time. In a previous study relating to the year of incidence, 1990, we demonstrated that cancer registration data in Scotland appeared to be of high quality [4]. The purpose of this study was to re-assess the quality of the data following what has been a major re-organisation and, in particular, to assess the reliability of new variables in the data-set.
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Patients and methods
A random sample of 3500 registrations, stratified by health board of residence, was generated from the Scottish Cancer Registry (SCR) by computer. The sampling frame consisted of all primary malignant neoplasms (ICD-10 C00–C96), excluding non-melanoma skin cancers (C44), secondary malignant neoplasms (C77–C80), and death certificate only (DCO) registrations diagnosed between April and September 1997. Permission to access relevant medical records was sought from Medical Directors of hospitals
Availability of medical records and representativeness of the sample
Of the sample of 3500 registrations, 3175 (90.7%) had medical records available for scrutiny. There were no statistically significant differences between the 3175 registrations assessed and all equivalent 1997 registrations in terms of age (P=0.144), sex (P=0.75) and major site (P=0.76) distribution.
Identifying/demographic data
There were 10 (0.3%) discrepancies in surname spelling, nine (0.3%) in forename, 41 (1.3%) in date of birth, 137 (4.3%) in address at diagnosis, 182 (5.7%) in postcode of residence at diagnosis, and
Discussion
In a previous study [4], we showed that the quality of Scottish cancer registration data compared favourably to that reported by the few other cancer registries undertaking such analyses. Overall, the results of this study suggest that the quality of cancer registration data in Scotland remains high. At 90.7%, the availability of medical records was similar to our previous study, and compares favourably to studies from elsewhere in the UK 5, 6, 7. We believe that our study population was
Acknowledgements
We are grateful to Medical Directors for granting permission to access medical records for this study, and to staff of the Medical Records Departments, and our own Cancer Registration Officer colleagues for facilitating the study. The data for the study were collected by Val Borland, Gillian Boyle, Laura Dobbie, Vi Duguid, Kjersti Fergusson, Sophie Houston, Chris Jones, Fiona MacKenzie, Etta Shanks, Tim Varley and Mary Virtue of the Information & Statistics Division Data Quality Assurance team.
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