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Classification performance of administrative coding data for detection of invasive fungal infection in paediatric cancer patients
- Source :
- PLoS ONE, Vol 15, Iss 9 (2020)
- Publication Year :
- 2020
- Publisher :
- Public Library of Science (PLoS), 2020.
-
Abstract
- Background Invasive fungal infection (IFI) detection requires application of complex case definitions by trained staff. Administrative coding data (ICD-10-AM) may provide a simplified method for IFI surveillance, but accuracy of case ascertainment in children with cancer is unknown. Objective To determine the classification performance of ICD-10-AM codes for detecting IFI using a gold-standard dataset (r-TERIFIC) of confirmed IFIs in paediatric cancer patients at a quaternary referral centre (Royal Children’s Hospital) in Victoria, Australia from 1st April 2004 to 31st December 2013. Methods ICD-10-AM codes denoting IFI in paediatric patients (
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 15
- Issue :
- 9
- Database :
- Directory of Open Access Journals
- Journal :
- PLoS ONE
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.68cb2dd1cf3445baf22324e299ba4ab
- Document Type :
- article