ArticlePloS one2020
Classification performance of administrative coding data for detection of invasive fungal infection in paediatric cancer patients.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 12 citations in OpenAlex.
- Impact of Evolving Evidence on Pharmacological Therapy for Alcohol-Associated Hepatitis in Alberta: A Population-Based Study of Practice Trends and MELD-Stratified Effectiveness of Corticosteroids.Alimentary pharmacology & therapeutics · 2026Article
- Updating the Epidemiology of Blastomycosis and Histoplasmosis in the United States, Using National Electronic Health Record Data, 2013-2023.The Journal of infectious diseases · 2025Article
- Accuracy of pathogen diagnostic codes for acute hematogenous musculoskeletal infections in children.Journal of hospital medicine · 2025Article
- Automating the overburdened clinical coding system: challenges and next steps.NPJ digital medicine · 2023Article
- Low Sensitivity ofOpen forum infectious diseases · 2022Article
- Article
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Authors and funding
8 authors at 5 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundInvasive 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.
objectiveTo 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.
methodsICD-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.
resultsOf 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.
conclusionICD-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.
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