Evidence map›Paper›PMID 39383152›Full record

ArticlePloS one2024

Cancer impact on lower-income patients in Malaysian public healthcare: An exploration of out-of-pocket expenses, productivity loss, and financial coping strategies.

Farhana Aminuddin, Sivaraj Raman, Mohd Shahri Bahari, Nur Amalina Zaimi, Mohd Shaiful Jefri Mohd Nor Sham Kunusagaran, Nur Azmiah Zainuddin, Marhaini Mostapha, Tan Yui Ping, Nor Zam Azihan Mohd Hassan

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

9 authors.

Farhana AminuddinInstitute for Health Systems Research, Centre of Health Economics Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam, Selangor, Malaysia.ORCID 0000-0003-2958-5017
Sivaraj RamanInstitute for Health Systems Research, Centre of Health Economics Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam, Selangor, Malaysia.ORCID 0000-0002-2010-5593
Mohd Shahri BahariInstitute for Health Systems Research, Centre of Health Economics Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam, Selangor, Malaysia.ORCID 0000-0002-6530-8677
Nur Amalina ZaimiInstitute for Health Systems Research, Centre of Health Economics Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam, Selangor, Malaysia.ORCID 0000-0002-7157-8235
Mohd Shaiful Jefri Mohd Nor Sham KunusagaranInstitute for Health Systems Research, Centre of Health Economics Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam, Selangor, Malaysia.
Nur Azmiah ZainuddinInstitute for Health Systems Research, National Institutes of Health, Centre of Health Policy Research, Ministry of Health Malaysia, Shah Alam, Selangor, Malaysia.
Marhaini MostaphaInstitute for Health Systems Research, Centre of Health Economics Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam, Selangor, Malaysia.ORCID 0000-0001-8865-0777
Tan Yui PingInstitute for Health Systems Research, Centre of Health Economics Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam, Selangor, Malaysia.ORCID 0000-0001-7097-8336
Nor Zam Azihan Mohd HassanInstitute for Health Systems Research, Centre of Health Economics Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam, Selangor, Malaysia.ORCID 0000-0002-0683-1249

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer patients often grapple with substantial out-of-pocket (OOP) expenses and productivity loss, with the ramifications being particularly crucial for lower-income households. This study aims to estimate OOP costs incurred by cancer patients, assess their productivity loss, and analyse the financial coping mechanisms employed by individuals within the lower-income bracket. The study employed face-to-face interviews among cancer patients aged 40 years and above, currently undergoing treatment, and belonging to the lower-income group. Participants were recruited from six public cancer referral hospitals. OOP expenses, encompassing medical and non-medical costs, along with productivity loss, were measured. A generalized linear model was applied to identify potential OOP determinants. Additionally, the coping mechanisms employed by individuals to finance their cancer OOP expenses were also determined. Among the 430 participants recruited, predominantly female (63.5%), and aged 60 or older (53.9%). The annual mean total cancer costs per patient were US$ 2,398.28 (±2,168.74), including 15% for medical costs US$ 350.95 (±560.24), 34% for non-medical costs US$820.24 (±818.24), and 51% for productivity loss costs US$1,227.09 (±1,809.09). Transportation, nutritional supplements, outpatient treatment, and medical supplies were notable cost contributors to total OOP expenditures. Ethnicity (β = 1.44; 95%CI = 1.15-1.79), household income (β = 1.40; 95%CI = 1.10-1.78), annual outpatient visits (β = 1.00; 95%CI = 1.00-1.01), age (β = 0.74; 95%CI = 0.56-0.98), and employment status (β = 0.54; 95%CI = 0.72-1.34) were identified as significant predictors of OOP costs among cancer patients. Notably, 91% of participants relied on household salaries and savings, while 15% resorted to interest-free borrowing, 11% sold possessions, and 0.5% borrowed with interest to finance their expenses. This study offers crucial insights into the economic impact of cancer on individuals and their families, providing policymakers with valuable information to tackle challenges faced in their journey. Despite substantial public healthcare subsidies, the study revealed that cancer costs can remain a potential barrier to accessing essential treatment. Therefore, there is a need for reinforced system-level infrastructure to facilitate targeted financial navigation services.

Indexed as

Health ExpendituresNeoplasmsAdaptation, PsychologicalAdultAgedCoping SkillsCost of IllnessEfficiencyFemaleHumansIncomeMalaysiaMaleMiddle AgedPoverty

Identifiers

PMID39383152
PMCPMC11463769

What OpenQuestion holds

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LicenceCC BY
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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.