ArticlePharmacoEconomics2024
Examining the Effect of Depicting a Patient Affected by a Negative Reimbursement Decision in Healthcare on Public Disagreement with the Decision.
Article in PharmacoEconomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe availability of increasingly advanced and expensive new health technologies puts considerable pressure on publicly financed healthcare systems. Decisions to not-or no longer-reimburse a health technology from public funding may become inevitable. Nonetheless, policymakers are often pressured to amend or revoke negative reimbursement decisions due to the public disagreement that typically follows such decisions. Public disagreement may be reinforced by the publication of pictures of individual patients in the media. Our aim was to assess the effect of depicting a patient affected by a negative reimbursement decision on public disagreement with the decision.
methodsWe conducted a discrete choice experiment in a representative sample of the public (n = 1008) in the Netherlands and assessed the likelihood of respondents' disagreement with policymakers' decision to not reimburse a new pharmaceutical for one of two patient groups. We presented a picture of one of the patients affected by the decision for one patient group and "no picture available" for the other group. The groups were described on the basis of patients' age, health-related quality of life (HRQOL) and life expectancy (LE) before treatment, and HRQOL and LE gains from treatment. We applied random-intercept logit regression models to analyze the data.
resultsOur results indicate that respondents were more likely to disagree with the negative reimbursement decision when a picture of an affected patient was presented. Consistent with findings from other empirical studies, respondents were also more likely to disagree with the decision when patients were relatively young, had high levels of HRQOL and LE before treatment, and large LE gains from treatment.
conclusionsThis study provides evidence for the effect of depicting individual, affected patients on public disagreement with negative reimbursement decisions in healthcare. Policymakers would do well to be aware of this effect so that they can anticipate it and implement policies to mitigate associated risks.
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