Evidence map›Paper›PMID 38456119›Full record

ArticleThe Malaysian journal of medical sciences : MJMS2024

Telehealth Consultation for Malaysian Citizens' Willingness to Pay Assessed by the Double-Bounded Dichotomous Choice Method.

Tan Mey Mey, Katsuhiko Ogasawara

Abstract read
In one paragraph

Article in The Malaysian journal of medical sciences : MJMS, 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

2 authors.

Tan Mey MeyGraduate School of Health Sciences, School of Medicine, Hokkaido University, Hokkaido, Japan.
Katsuhiko OgasawaraGraduate School of Health Sciences, School of Medicine, Hokkaido University, Hokkaido, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Re-envisioning healthcare in technology tools includes robust utilisation of telehealth, improvement in access, quality, care efficiencies and cost-effectiveness of healthcare services. In reality, the technology's potential to transform healthcare may be limited by the ability to pay for it. This study aims to estimate Malaysian citizens' willingness to pay (WTP) for telehealth consultations and determine the factors contributing to it. This is vital to inform decision-making about expansion, preferences and deployment of a pricing strategy for telehealth services. Methods: A random sample of 220 adult Malaysians was surveyed using social network services (SNS). Three different WTP bid arrays were identified and each respondent received a randomly drawn bid price. The WTP fee for using the telehealth consultation for 30 min was measured and estimated using a Double-Bounded Dichotomous Choice (DBDC) and the Random Utility Logit Model. Result: The median WTP was estimated to be RM58 (JPY2,198), RM78 (JPY2,956) for 132 respondents' willingness to use telehealth consultation and RM26 (JPY985) for 51 respondents who were unwilling. Further analysis found that WTP is correlated with the perception and willingness of the respondents to use it. Conclusion: Despite most respondents being willing to pay for telehealth consultations, sociodemographic characteristics and affordability influenced the process of making decisions about WTP for telehealth consultation. This finding suggests that the private sector can play a crucial role in the deployment of telehealth. However, there may be a need to consider affordability and how to increase access and use of telehealth services.

Indexed as

contingent valuation methodsDouble-Bounded Dichotomous Choicetelehealthwillingness to pay

Identifiers

PMID38456119
PMCPMC10917602

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.