Evidence map›Paper›PMID 39730997›Full record

ArticleBMC medical research methodology2024

Toward value-based care using cost mining: cost aggregation and visualization across the entire colorectal cancer patient pathway.

Maura Leusder, Sven Relijveld, Derya Demirtas, Jon Emery, Michelle Tew, Peter Gibbs, Jeremy Millar, Victoria White, Michael Jefford, Fanny Franchini and 1 more

Abstract read
In one paragraph

Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Maura Leusder *Erasmus School of Health Policy and Management, Erasmus University Rotterdam, Rotterdam, the Netherlands.ORCID 0000-0001-7134-1003
Sven Relijveld *Industrial Engineering and Business Information Systems, University of Twente, Enschede, the Netherlands.ORCID 0000-0002-1599-7515
Derya DemirtasIndustrial Engineering and Business Information Systems, University of Twente, Enschede, the Netherlands.ORCID 0000-0003-4064-484X
Jon EmeryUniversity of Melbourne Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia.ORCID 0000-0002-5274-6336
Michelle TewCentre for Health Policy, Melbourne School of Public and Global Health, Faculty of Medicine, Dentistry and Health Sciences, Parkville, VIC, Australia.ORCID 0000-0003-3009-8056
Peter GibbsUniversity of Melbourne Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia.ORCID 0000-0003-1423-4484
Jeremy MillarCancer Research Program, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.ORCID 0000-0001-8202-8602
Victoria WhiteSchool of Psychology, Faculty of Health, Deakin University, Melbourne, VIC, Australia.ORCID 0000-0001-6619-8484
Michael JeffordDepartment of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.ORCID 0000-0002-8792-7807
Fanny Franchini *University of Melbourne Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia.ORCID 0000-0002-4522-3385
Maarten IJzerman *Erasmus School of Health Policy and Management, Erasmus University Rotterdam, Rotterdam, the Netherlands. ijzerman@eshpm.eur.nl.ORCID 0000-0001-5788-5805

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this study is to develop a method we call "cost mining" to unravel cost variation and identify cost drivers by modelling integrated patient pathways from primary care to the palliative care setting. This approach fills an urgent need to quantify financial strains on healthcare systems, particularly for colorectal cancer, which is the most expensive cancer in Australia, and the second most expensive cancer globally.

methodsWe developed and published a customized algorithm that dynamically estimates and visualizes the mean, minimum, and total costs of care at the patient level, by aggregating activity-based healthcare system costs (e.g. DRGs) across integrated pathways. This extends traditional process mining approaches by making the resulting process maps actionable and informative and by displaying cost estimates. We demonstrate the method by constructing a unique dataset of colorectal cancer pathways in Victoria, Australia, using records of primary care, diagnosis, hospital admission and chemotherapy, medication, health system costs, and life events to create integrated colorectal cancer patient pathways from 2012 to 2020.

resultsCost mining with the algorithm enabled exploration of costly integrated pathways, i.e. drilling down in high-cost pathways to discover cost drivers, for 4246 cases covering approx. 4 million care activities. Per-patient CRC pathway costs ranged from $10,379 AUD to $41,643 AUD, and varied significantly per cancer stage such that e.g. chemotherapy costs in one cancer stage are different to the same chemotherapy regimen in a different stage. Admitted episodes were most costly, representing 93.34% or $56.6 M AUD of the total healthcare system costs covered in the sample.

conclusionsCost mining can supplement other health economic methods by providing contextual, sequence and timing-related information depicting how patients flow through complex care pathways. This approach can also facilitate health economic studies informing decision-makers on where to target care improvement or to evaluate the consequences of new treatments or care delivery interventions. Through this study we provide an approach for hospitals and policymakers to leverage their health data infrastructure and to enable real time patient level cost mining.

Indexed as

AlgorithmsColorectal NeoplasmsHealth Care CostsAustraliaCritical PathwaysData MiningHumansPalliative CarePrimary Health CareVictoriaColorectal cancerCosts of carePatient pathwaysProcess miningValue-based healthcare

Identifiers

PMID39730997
PMCPMC11681630

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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.