Evidence map›Paper›PMID 25884470›Full record

Observational studyImplementation science : IS2015

Resource use, costs and quality of end-of-life care: observations in a cohort of elderly Australian cancer decedents.

Julia M Langton, Preeyaporn Srasuebkul, Rebecca Reeve, Bonny Parkinson, Yuanyuan Gu, Nicholas A Buckley, Marion Haas, Rosalie Viney, Sallie-Anne Pearson, End-of-Life in Cancer Care (EoL-CC) Investigators

Abstract readObservational Study
In one paragraph

Observational study in Implementation science : IS, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Exploring advance care planning awareness, experiences, and preferences of people with cancer and support people: an Australian online cross-sectional study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2021
    Article
  4. Article
  5. Article
  6. Observational
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Julia M LangtonFaculty of Pharmacy, The University of Sydney, Sydney, NSW, Australia. julia.langton@sydney.edu.au.
Preeyaporn SrasuebkulFaculty of Pharmacy, The University of Sydney, Sydney, NSW, Australia. preeyaporn.srasuebkul@sydney.edu.au.
Rebecca ReeveCentre for Health Economics Research & Evaluation, The University of Technology Sydney, Sydney, NSW, Australia. rebecca.reeve@chere.uts.edu.au.
Bonny ParkinsonCentre for Health Economics Research & Evaluation, The University of Technology Sydney, Sydney, NSW, Australia. bonny.parkinson@chere.uts.edu.au.
Yuanyuan GuCentre for Health Economics Research & Evaluation, The University of Technology Sydney, Sydney, NSW, Australia. yuanyuan.gu@chere.uts.edu.au.
Nicholas A BuckleySydney Medical School, The University of Sydney, Sydney, NSW, Australia. nicholas.buckley@sydney.edu.au.
Marion HaasCentre for Health Economics Research & Evaluation, The University of Technology Sydney, Sydney, NSW, Australia. marion.haas@chere.uts.edu.au.
Rosalie VineyCentre for Health Economics Research & Evaluation, The University of Technology Sydney, Sydney, NSW, Australia. rosalie.viney@chere.uts.edu.au.
Sallie-Anne PearsonFaculty of Pharmacy, The University of Sydney, Sydney, NSW, Australia. sallie.pearson@sydney.edu.au.
End-of-Life in Cancer Care (EoL-CC) Investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe last year of life is one of the most resource-intensive periods for people with cancer. Very little population-based research has been conducted on end-of-life cancer care in the Australian health care setting. The objective of this program is to undertake a series of observational studies examining resource use, costs and quality of end-of-life care in a cohort of elderly cancer decedents using linked, routinely collected data. METHODS/

designThis study forms part of an ongoing cancer health services research program. The cohorts for the end-of-life research program comprise Australian Government Department of Veterans' Affairs decedents with full health care entitlements, residing in NSW for the last 18 months of life and dying between 2005 and 2009. We used cancer and death registry data to identify our decedent cohorts and their causes of death. The study population includes 9,862 decedents with a cancer history and 15,483 decedents without a cancer history. The median age at death is 86 and 87 years in the cancer and non-cancer cohorts, respectively. We will examine resource use and associated costs in the last 6 months of life using linked claims data to report on health service use, hospitalizations, emergency department visits and medicines use. We will use best practice methods to examine the nature and extent of resource use, costs and quality of care based on previously published indicators. We will also examine factors associated with these outcomes. DISCUSSION: This will be the first Australian research program and among the first internationally to combine routinely collected data from primary care and hospital-based care to examine comprehensively end-of-life care in the elderly. The research program has high translational value, as there is limited evidence about the nature and quality of care in the Australian end-of-life setting.

Indexed as

AgedAged, 80 and overAustraliaCase-Control StudiesCause of DeathCohort StudiesDelivery of Health CareDrug CostsEmergency Service, HospitalFemaleHealth Care CostsHumansMaleNeoplasmsQuality of Health CareRegistries

Identifiers

PMID25884470
PMCPMC4350285

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.