Evidence map›Paper›PMID 30382489›Full record

ArticleHealth economics review2018

CancerCostMod: a model of the healthcare expenditure, patient resource use, and patient co-payment costs for Australian cancer patients.

Nicole Bates, Emily Callander, Daniel Lindsay, Kerrianne Watt

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Health economics review, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
7.5field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 30 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. End-of-life healthcare use and associated costs for First Nations Australians diagnosed with cancer in Queensland, Australia.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
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  11. DAta Linkage to Enhance Cancer Care (DaLECC): Protocol of a Large Australian Data Linkage Study.International journal of environmental research and public health · 2023
    Article
  12. Article
  13. Article
  14. Article
  15. Quantifying the hospital and emergency department costs for women diagnosed with breast cancer in Queensland.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2022
    Article
  16. Article
  17. Patient co-payments for women diagnosed with breast cancer in Australia.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2020
    Article
  18. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Nicole BatesCollege of Public Health, Medical and Veterinary Sciences (CPHMVS), James Cook University, Townsville, Australia. Nicole.bates@my.jcu.edu.au.ORCID 0000-0002-9628-1462
Emily CallanderAustralian Institute of Tropical Health and Medicine (AITHM), James Cook University, Townsville, QLD, Australia.
Daniel LindsayCollege of Public Health, Medical and Veterinary Sciences (CPHMVS), James Cook University, Townsville, Australia.
Kerrianne WattCollege of Public Health, Medical and Veterinary Sciences (CPHMVS), James Cook University, Townsville, Australia.
Australian Institute of Tropical Health and Medicine · AUJames Cook University · AU

Funding

National Health and Medical Research Council APP1052742
6 · The paper itself

Abstract

Although cancer survival in general has improved in Australia over the past 30 years, Indigenous Australians, socioeconomically disadvantaged persons, and people living in remote areas still experience poorer health outcomes. This paper aims to describe the development of CancerCostMod, and to present the healthcare expenditure and patient co-payments for the first 12-months post-diagnosis. The base population is a census of all cancer diagnoses (excluding non-melanoma skin cancer) in Queensland, Australia between 1 July 2011 and 30 June 2012 (N = 25,553). Each individual record was linked to their Queensland Health Admitted Patient Data Collection, Emergency Department Information System, Medicare Benefits Schedule, and Pharmaceutical Benefits Scheme records from 1 July 2011 to 30 June 2015. Indigenous status was recorded for 87% of participants in our base population. Multiple imputation was used to assign Indigenous status to records where Indigenous status was missing. This base population was then weighted, using a programmed SAS macro (GREGWT) to be representative of the Australian population. We adopted a national healthcare perspective to estimate the cost of cancer for hospital episodes, ED presentations, primary healthcare, and prescription pharmaceuticals. We also adopted an individual perspective, to estimate the primary healthcare and prescription pharmaceutical patient co-payments. Once weighted, our sample represents approximately 123,900 Australians (1.7% Indigenous Australians). The total healthcare system cost of all cancers during the first 12-months post diagnosis was $4.8 billion, [corrected] and patient co-payments costs were $127 million. After adjusting for sex, age at diagnosis, Indigenous status, rurality, socioeconomic status, and broad cancer type, significant differences in costs were observed for population groups of interest within the first year post-diagnosis. This paper provides a more recent national estimate of the cost of cancer, and addresses current research gaps by highlighting the distribution of healthcare and individual costs by Indigenous status, rurality, and socioeconomic status.

Indexed as

CancerCancerCostModCostEconomic burdenHealthcare systemPatient co-payment

Identifiers

PMID30382489
PMCPMC6742917
OpenAlexW4211241668

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.