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Published in: Virchows Archiv 1/2016

01-01-2016 | Annual Review Issue

Does standardised structured reporting contribute to quality in diagnostic pathology? The importance of evidence-based datasets

Authors: D. W. Ellis, J. Srigley

Published in: Virchows Archiv | Issue 1/2016

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Abstract

Key quality parameters in diagnostic pathology include timeliness, accuracy, completeness, conformance with current agreed standards, consistency and clarity in communication. In this review, we argue that with worldwide developments in eHealth and big data, generally, there are two further, often overlooked, parameters if our reports are to be fit for purpose. Firstly, population-level studies have clearly demonstrated the value of providing timely structured reporting data in standardised electronic format as part of system-wide quality improvement programmes. Moreover, when combined with multiple health data sources through eHealth and data linkage, structured pathology reports become central to population-level quality monitoring, benchmarking, interventions and benefit analyses in public health management. Secondly, population-level studies, particularly for benchmarking, require a single agreed international and evidence-based standard to ensure interoperability and comparability. This has been taken for granted in tumour classification and staging for many years, yet international standardisation of cancer datasets is only now underway through the International Collaboration on Cancer Reporting (ICCR). In this review, we present evidence supporting the role of structured pathology reporting in quality improvement for both clinical care and population-level health management. Although this review of available evidence largely relates to structured reporting of cancer, it is clear that the same principles can be applied throughout anatomical pathology generally, as they are elsewhere in the health system.
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Metadata
Title
Does standardised structured reporting contribute to quality in diagnostic pathology? The importance of evidence-based datasets
Authors
D. W. Ellis
J. Srigley
Publication date
01-01-2016
Publisher
Springer Berlin Heidelberg
Published in
Virchows Archiv / Issue 1/2016
Print ISSN: 0945-6317
Electronic ISSN: 1432-2307
DOI
https://doi.org/10.1007/s00428-015-1834-4

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