IMPROVING POPULATION HEALTH INSIGHTS THROUGH ADMINISTRATIVE AND REGISTRY DATA INTEGRATION: A 2005–2016 ANALYSIS

Authors

  • Thomas Andrew Mitchell Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia

DOI:

https://doi.org/10.5281/zenodo.17405210

Keywords:

Invasive fungal disease, haematological malignancy, haematopoietic stem cell transplantation, data linkage, epidemiologyMichelle R. Ananda-Rajah

Abstract

Background: Little is known about the morbidity and mortality of invasive fungal disease (IFD) at a population level. The aim of this study was to determine the incidence, trends and outcomes of IFD in all haematology-oncology patients by linking Victorian hospital data to state-based registries.

Methods: Episodes of IFD complicating adult haematological malignancy (HM) and haematopoietic stem cell transplantation (HSCT) patients admitted to Victorian hospitals from 1st July 2005 to 30th June 2016 were extracted from the Victorian Admitted Episodes Dataset and linked to the date of HM diagnosis from the Victorian Cancer Registry and mortality from the Victorian Death Index. Descriptive analyses and regression modelling were used.

Results: There were 619,702 inpatient-episodes among 32,815 HM and 1,765 HSCT-patients. IFD occurring twelvemonths from HM-diagnosis was detected in 669 (2.04%) HM-patients and 111 (6.29%) HSCT-recipients, respectively. Median time to IFD-diagnosis was 3, 5, 15 and 22 months in acute myeloid leukaemia, acute lymphoblastic leukaemia, Hodgkin lymphoma and multiple myeloma, respectively. Median survival from IFD-diagnosis was 7, 7 and 3 months for invasive aspergillosis, invasive candidiasis and mucormycosis, respectively. From 2005-2016, IFD incidence decreased 0.28% per 1,000 bed-days. Fungal incidence coincided with spring peaks on time-series analysis.

Conclusions: Data linkage is an efficient means of evaluating the epidemiology of a rare disease, however the burden of IFD is likely underestimated, arguing for better quality hospital level surveillance data to improve management strategies

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Published

2025-07-12

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