Evidence map›Paper›PMID 33026633›Full record

ArticlePharmacoEconomics2021

The Relative Importance of Education and Criminal Justice Costs and Benefits in Economic Evaluations: A Best-Worst Scaling Experiment.

Irina Pokhilenko, Luca M M Janssen, Mickael Hiligsmann, Silvia M A A Evers, Ruben M W A Drost, Aggie T G Paulus, Leonarda G M Bremmers

Abstract read
In one paragraph

Article in PharmacoEconomics, 2021. 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. Unit Costs in Health Economic Evaluations: Quo Vadis, Austria?International journal of environmental research and public health · 2022
    Review
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

7 authors.

Irina Pokhilenko *Department of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands. i.pokhilenko@maastrichtuniversity.nl.ORCID http://orcid.org/0000-0001-6390-2851
Luca M M Janssen *Department of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.ORCID http://orcid.org/0000-0002-0184-3742
Mickael HiligsmannDepartment of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.ORCID http://orcid.org/0000-0003-4274-9258
Silvia M A A EversDepartment of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.ORCID http://orcid.org/0000-0003-1026-570X
Ruben M W A DrostDepartment of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.ORCID http://orcid.org/0000-0002-7428-040X
Aggie T G PaulusDepartment of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.ORCID http://orcid.org/0000-0002-2086-6106
Leonarda G M BremmersDepartment of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.ORCID http://orcid.org/0000-0003-0569-397X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesMental and behavioural disorders (MBDs) and interventions targeting MBDs lead to costs and cost savings in the healthcare sector, but also in other sectors. The latter are referred to as intersectoral costs and benefits (ICBs). Interventions targeting MBDs often lead to ICBs in the education and criminal justice sectors, yet these are rarely included in economic evaluations. This study aimed to investigate the attitudes held by health economists and health technology assessment experts towards education and criminal justice ICBs in economic evaluations and to quantify the relative importance of these ICBs in the context of MBDs.

methodsAn online survey containing open-ended questions and two best-worst scaling object case studies was conducted in order to prioritise a list of 20 education ICBs and 20 criminal justice ICBs. Mean relative importance scores for each ICB were generated using hierarchical Bayes analysis.

resultsThirty-nine experts completed the survey. The majority of the respondents (68%) reported that ICBs were relevant, but only a few (32%) included them in economic evaluations. The most important education ICBs were "special education school attendance", "absenteeism from school", and "reduced school attainment". The most important criminal justice ICBs were "decreased chance of committing a crime as a consequence/effect of mental health programmes/interventions", "jail and prison expenditures", and "long-term pain and suffering of victims/victimisation".

conclusionsThis study identified the most important education and criminal justice ICBs for economic evaluations of interventions targeting MBDs and suggests that it could be relevant to include these ICBs in economic evaluations.

Indexed as

Criminal LawMental DisordersBayes TheoremCost-Benefit AnalysisHealth ServicesHumans

Identifiers

PMID33026633
PMCPMC7790798

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.