Factors impacting hospitalisation and related health service costs in cancer survivors in Australia: Results from a population data linkage study in Queensland (COS‐Q)

• Published in: Cancer medicine (Malden, MA) Vol. 13; no. 17; pp. e70201 - n/a
• Main Authors: Merollini, Katharina M. D., Collins, Louisa G., Jones, Andrew T., Aitken, Joanne F., Kimlin, Michael G.
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01-09-2024; John Wiley and Sons Inc; Wiley
• Subjects: Adolescent; Adult; Aged; Aged, 80 and over; Australia; Cancer; cancer survivors; Cancer Survivors - statistics & numerical data; Child; Child, Preschool; Diagnosis related groups; DRGs; Female; Health Care Costs - statistics & numerical data; Health care expenditures; Health care policy; Health insurance; Health services; healthcare; hospital cost; Hospital costs; Hospital Costs - statistics & numerical data; Hospitalization; Hospitalization - economics; Hospitalization - statistics & numerical data; Humans; Infant; Infant, Newborn; Information Storage and Retrieval - economics; Male; Medical diagnosis; Medicare; Middle Aged; Neoplasms - economics; Neoplasms - epidemiology; Neoplasms - mortality; Neoplasms - therapy; Patients; Population studies; Public health; Queensland - epidemiology; Retrospective Studies; risk factors; Sociodemographics; treatment; Young Adult; Queensland; Queensland Australia; Australia; United States > US; hospital cost; treatment; risk factors; Australia; cancer survivors; healthcare
• ISSN: 2045-7634; 2045-7634
• DOI: 10.1002/cam4.70201

Background
The global economic cost of cancer and the costs of ongoing care for survivors are increasing. Little is known about factors affecting hospitalisations and related costs for the growing number of cancer survivors. Our aim was to identify associated factors of cancer survivors admitted to hospital in the public system and their costs from a health services perspective.
Methods
A population‐based, retrospective, data linkage study was conducted in Queensland (COS‐Q), Australia, including individuals diagnosed with a first primary cancer who incurred healthcare costs between 2013 and 2016. Generalised linear models were fitted to explore associations between socio‐demographic (age, sex, country of birth, marital status, occupation, geographic remoteness category and socio‐economic index) and clinical (cancer type, year of/time since diagnosis, vital status and care type) factors with mean annual hospital costs and mean episode costs.
Results
Of the cohort (N = 230,380) 48.5% (n = 111,820) incurred hospitalisations in the public system (n = 682,483 admissions). Hospital costs were highest for individuals who died during the costing period (cost ratio ‘CR’: 1.79, p < 0.001) or living in very remote or remote location (CR: 1.71 and CR: 1.36, p < 0.001) or aged 0–24 years (CR: 1.63, p < 0.001). Episode costs were highest for individuals in rehabilitation or palliative care (CR: 2.94 and CR: 2.34, p < 0.001), or very remote location (CR: 2.10, p < 0.001). Higher contributors to overall hospital costs were ‘diseases and disorders of the digestive system’ (AU$661 m, 21% of admissions) and ‘neoplastic disorders’ (AU$554 m, 20% of admissions).
Conclusions
We identified a range of factors associated with hospitalisation and higher hospital costs for cancer survivors, and our results clearly demonstrate very high public health costs of hospitalisation. There is a lack of obvious means to reduce these costs in the short or medium term which emphasises an increasing economic imperative to improving cancer prevention and investments in home‐ or community‐based patient support services.
In this population‐based, retrospective data linkage study we investigate a range of contributing socio‐demographic and clinical factors for cancer survivors relating to hospital admissions in the public system and their costs in Queensland, Australia. The objectives of this work were to (a) understand differences in characteristics of cancer survivors with hospitalisation versus without hospitalisation, (b) explore the relationship between a range of clinical and socio‐demographic factors and hospitalisation costs on a population level from a health service perspective and (c) identify factors contributing to high hospitalisation costs.