Exploring the identification, validation, and categorization of the cost and benefits of criminal justice in mental health: the PECUNIA project.

Criminal justice intersectoral costs and benefits Health economics research Mental health Methodology PECUNIA Societal perspective

Journal

International journal of technology assessment in health care
ISSN: 1471-6348
Titre abrégé: Int J Technol Assess Health Care
Pays: England
ID NLM: 8508113

Informations de publication

Date de publication:
27 Jul 2020
Historique:
entrez: 28 7 2020
pubmed: 28 7 2020
medline: 28 7 2020
Statut: aheadofprint

Résumé

Mental health disorders and their treatments produce significant costs and benefits in both healthcare and non-healthcare sectors. The latter are often referred to as intersectoral costs and benefits (ICBs). Little is known about healthcare-related ICBs in the criminal justice sector and how to include these in health economics research. The triple aim of this study is (i) to identify healthcare-related ICBs in the criminal justice sector, (ii) to validate the list of healthcare-related ICBs in the criminal justice sector on a European level by sector-specific experts, and (iii) to classify the identified ICBs. A scientific literature search in PubMed and an additional grey literature search, carried out in six European countries, were used to retrieve ICBs. In order to validate the international applicability of the ICBs, a survey was conducted with an international group of experts from the criminal justice sector. The list of criminal justice ICBs was categorized according to the PECUNIA conceptual framework. The full-text analysis of forty-five peer-reviewed journal articles and eleven grey literature sources resulted in a draft list of items. Input from the expert survey resulted in a final list of fourteen unique criminal justice ICBs, categorized according to the care atom. This study laid further foundations for the inclusion of important societal costs of mental health-related interventions within the criminal justice sector. More research is needed to facilitate the further and increased inclusion of ICBs in health economics research.

Sections du résumé

BACKGROUND BACKGROUND
Mental health disorders and their treatments produce significant costs and benefits in both healthcare and non-healthcare sectors. The latter are often referred to as intersectoral costs and benefits (ICBs). Little is known about healthcare-related ICBs in the criminal justice sector and how to include these in health economics research.
OBJECTIVES OBJECTIVE
The triple aim of this study is (i) to identify healthcare-related ICBs in the criminal justice sector, (ii) to validate the list of healthcare-related ICBs in the criminal justice sector on a European level by sector-specific experts, and (iii) to classify the identified ICBs.
METHODS METHODS
A scientific literature search in PubMed and an additional grey literature search, carried out in six European countries, were used to retrieve ICBs. In order to validate the international applicability of the ICBs, a survey was conducted with an international group of experts from the criminal justice sector. The list of criminal justice ICBs was categorized according to the PECUNIA conceptual framework.
RESULTS RESULTS
The full-text analysis of forty-five peer-reviewed journal articles and eleven grey literature sources resulted in a draft list of items. Input from the expert survey resulted in a final list of fourteen unique criminal justice ICBs, categorized according to the care atom.
CONCLUSION CONCLUSIONS
This study laid further foundations for the inclusion of important societal costs of mental health-related interventions within the criminal justice sector. More research is needed to facilitate the further and increased inclusion of ICBs in health economics research.

Identifiants

pubmed: 32715991
doi: 10.1017/S0266462320000471
pii: S0266462320000471
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-8

Auteurs

Luca M M Janssen (LMM)

Department of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences (FHML), Maastricht University, Maastricht, The Netherlands.

Irina Pokhilenko (I)

Department of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences (FHML), Maastricht University, Maastricht, The Netherlands.

Silvia M A A Evers (SMAA)

Department of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences (FHML), Maastricht University, Maastricht, The Netherlands.
Trimbos Institute Centre of Economic Evaluation & Machine Learning, Utrecht, The Netherlands.

Aggie T G Paulus (ATG)

Department of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences (FHML), Maastricht University, Maastricht, The Netherlands.

Judit Simon (J)

Department of Health Economics, Centre for Public Health, Medical University of Vienna, Vienna, Austria.
Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK.

Hans-Helmut König (HH)

Department of Health Economics and Health Services Research, University Medical Center Hamburg, Hamburg, Germany.

Valentin Brodszky (V)

Department of Health Economics, Corvinus University of Budapest, Budapest, Hungary.

Luis Salvador-Carulla (L)

Centre for Mental Health Research, Research School of Population Health, ANU College of Health and Medicine, Australian National University, Canberra, Australia.
Menzies Centre for Health Policy, School of Public Health, University of Sydney, Sydney, Australia.

A-La Park (AL)

London School of Economics (LSE), Department of Health Policy, London School of Economics and Political Science, London, UK.

W Hollingworth (W)

Health Economics, Bristol Medical School: Population Health Sciences, Bristol, UK.

Ruben M W A Drost (RMWA)

Department of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences (FHML), Maastricht University, Maastricht, The Netherlands.

Classifications MeSH