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Conference item

Automated differentiation of incident and prevalent cases in primary care computerised medical records (CMR)

Abstract:

Identifying incident (first or new) episodes of illness is critical in sentinel networks to inform about the seasonal onset of diseases and to give early warning of epidemics, as well as differentiating change in health service utilization from change in pattern of disease. The most reliable way of differentiating incident from prevalent cases is through the clinician assigning episode type to the patient's computerized medical record (CMR). However, episode type assignment is often made inco...

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Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.3233/978-1-61499-852-5-151

Authors


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Role:
Author
ORCID:
0000-0002-6503-3001
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Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
Primary Care Health Sciences
Role:
Author
ORCID:
0000-0002-7717-8486
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Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
Primary Care Health Sciences
Role:
Author
ORCID:
0000-0003-4856-3075
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Publisher:
IOS Press Publisher's website
Journal:
Studies in Health Technology and Informatics Journal website
Volume:
247
Pages:
151-155
Host title:
Studies in Health Technology and Informatics
Publication date:
2019-04-24
Acceptance date:
2019-04-24
Event location:
Netherlands
DOI:
ISSN:
0926-9630
Pmid:
29677941
Source identifiers:
1013718
ISBN:
9781614998518
Language:
English
Keywords:
Pubs id:
pubs:1013718
UUID:
uuid:37dc69b5-fbd6-442b-8fd3-d04831a9eff0
Local pid:
pubs:1013718
Deposit date:
2019-12-16

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