Classification performance of administrative coding data for detection of invasive fungal infection in paediatric cancer patients
AuthorValentine, JC; Worth, LJ; Verspoor, KM; Hall, L; Yeoh, DK; Thursky, KA; Clark, JE; Haeusler, GM
Source TitlePLoS One
PublisherPUBLIC LIBRARY SCIENCE
University of Melbourne Author/sHaeusler, Gabrielle; Thursky, Karin; Valentine, Jake; Verspoor, Cornelia; Worth, Leon
AffiliationMedicine and Radiology
Computing and Information Systems
Sir Peter MacCallum Department of Oncology
Document TypeJournal Article
CitationsValentine, J. C., Worth, L. J., Verspoor, K. M., Hall, L., Yeoh, D. K., Thursky, K. A., Clark, J. E. & Haeusler, G. M. (2020). Classification performance of administrative coding data for detection of invasive fungal infection in paediatric cancer patients. PLOS ONE, 15 (9), https://doi.org/10.1371/journal.pone.0238889.
Access StatusOpen Access
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 (<18-years) with haematologic or solid tumour malignancies were extracted from the Victorian Admitted Episodes Dataset and linked to the r-TERIFIC dataset. Sensitivity, positive predictive value (PPV) and the F1 scores of the ICD-10-AM codes were calculated. RESULTS: Of 1,671 evaluable patients, 113 (6.76%) had confirmed IFI diagnoses according to gold-standard criteria, while 114 (6.82%) cases were identified using the codes. Of the clinical IFI cases, 68 were in receipt of ≥1 ICD-10-AM code(s) for IFI, corresponding to an overall sensitivity, PPV and F1 score of 60%, respectively. Sensitivity was highest for proven IFI (77% [95% CI: 58-90]; F1 = 47%) and invasive candidiasis (83% [95% CI: 61-95]; F1 = 76%) and lowest for other/unspecified IFI (20% [95% CI: 5.05-72%]; F1 = 5.00%). The most frequent misclassification was coding of invasive aspergillosis as invasive candidiasis. CONCLUSION: ICD-10-AM codes demonstrate moderate sensitivity and PPV to detect IFI in children with cancer. However, specific subsets of proven IFI and invasive candidiasis (codes B37.x) are more accurately coded.
- Click on "Export Reference in RIS Format" and choose "open with... Endnote".
- Click on "Export Reference in RIS Format". Login to Refworks, go to References => Import References