Assessing the costs and cost-effectiveness of ICare internet-based interventions (protocol).

Cost-effectiveness Cost-utility Economic evaluation Internet-based interventions Mental health Service use

Journal

Internet interventions
ISSN: 2214-7829
Titre abrégé: Internet Interv
Pays: Netherlands
ID NLM: 101631612

Informations de publication

Date de publication:
Apr 2019
Historique:
received: 20 12 2017
accepted: 19 02 2018
entrez: 19 2 2019
pubmed: 19 2 2019
medline: 19 2 2019
Statut: epublish

Résumé

Mental health problems are common and place a burden on the individual as well as on societal resources. Despite the existence of evidence-based treatments, access to treatment is often prevented or delayed due to insufficient health care resources. Effective internet-based self-help interventions have the potential to reduce the risk for mental health problems, to successfully bridge waiting time for face-to-face treatment and to address inequities in access. However, little is known about the cost-effectiveness of such interventions. This paper describes the study protocol for the economic evaluation of the studies that form the ICare programme of internet-based interventions for the prevention and treatment of a range of mental health problems. An overarching work package within the ICare programme was developed to assess the cost-effectiveness of the internet-based interventions alongside the clinical trials. There are two underlying tasks in the ICare economic evaluation. First, to develop schedules that generate equivalent and comparable information on use of services and supports across seven countries taking part in clinical trials of different interventions and second, to estimate unit costs for each service and support used. From these data the cost per person will be estimated by multiplying each participant's use of each service by the unit cost for that service. Additionally, productivity losses will be estimated. This individual level of cost data matches the level of outcome data used in the clinical trials. Following the analyses of service use and costs data, joint analysis of costs and outcomes will be undertaken to provide findings on the relative cost-effectiveness of the interventions, taking both a public sector and a societal perspective. These analyses use a well-established framework, the Production of Welfare approach, and standard methods and techniques underpinned by economic theory. Existing research tends to support the effectiveness of internet-based interventions, but there is little information on their cost-effectiveness compared to 'treatment as usual'. The economic evaluation of ICare interventions will add considerably to this evidence base.

Sections du résumé

BACKGROUND BACKGROUND
Mental health problems are common and place a burden on the individual as well as on societal resources. Despite the existence of evidence-based treatments, access to treatment is often prevented or delayed due to insufficient health care resources. Effective internet-based self-help interventions have the potential to reduce the risk for mental health problems, to successfully bridge waiting time for face-to-face treatment and to address inequities in access. However, little is known about the cost-effectiveness of such interventions. This paper describes the study protocol for the economic evaluation of the studies that form the ICare programme of internet-based interventions for the prevention and treatment of a range of mental health problems.
METHODS METHODS
An overarching work package within the ICare programme was developed to assess the cost-effectiveness of the internet-based interventions alongside the clinical trials. There are two underlying tasks in the ICare economic evaluation. First, to develop schedules that generate equivalent and comparable information on use of services and supports across seven countries taking part in clinical trials of different interventions and second, to estimate unit costs for each service and support used. From these data the cost per person will be estimated by multiplying each participant's use of each service by the unit cost for that service. Additionally, productivity losses will be estimated. This individual level of cost data matches the level of outcome data used in the clinical trials. Following the analyses of service use and costs data, joint analysis of costs and outcomes will be undertaken to provide findings on the relative cost-effectiveness of the interventions, taking both a public sector and a societal perspective. These analyses use a well-established framework, the Production of Welfare approach, and standard methods and techniques underpinned by economic theory.
DISCUSSION/CONCLUSION CONCLUSIONS
Existing research tends to support the effectiveness of internet-based interventions, but there is little information on their cost-effectiveness compared to 'treatment as usual'. The economic evaluation of ICare interventions will add considerably to this evidence base.

Identifiants

pubmed: 30775260
doi: 10.1016/j.invent.2018.02.009
pii: S2214-7829(17)30133-1
pmc: PMC6364355
doi:

Types de publication

Journal Article

Langues

eng

Pagination

12-19

Références

Pharmacoeconomics. 1993 Nov;4(5):353-65
pubmed: 10146874
J Gen Intern Med. 2001 Sep;16(9):606-13
pubmed: 11556941
Health Econ. 2002 Jul;11(5):415-30
pubmed: 12112491
Stat Methods Med Res. 2002 Dec;11(6):455-68
pubmed: 12516984
J Ment Health Policy Econ. 2002 Mar;5(1):21-31
pubmed: 12529567
Psychol Med. 2003 Aug;33(6):977-86
pubmed: 12946082
J Occup Environ Med. 2004 Apr;46(4):398-412
pubmed: 15076658
Br J Psychiatry. 2005 Aug;187:106-8
pubmed: 16055820
Gesundheitswesen. 2005 Oct;67(10):736-46
pubmed: 16235143
Med J Aust. 2005 Nov 21;183(10 Suppl):S73-6
pubmed: 16296957
Arch Intern Med. 2006 May 22;166(10):1092-7
pubmed: 16717171
J Med Internet Res. 2006 Jun 23;8(2):e10
pubmed: 16867965
J Occup Rehabil. 2007 Sep;17(3):547-79
pubmed: 17653835
BMC Health Serv Res. 2007 Dec 19;7:206
pubmed: 18093289
Ann Behav Med. 2009 Aug;38(1):40-5
pubmed: 19834778
Expert Rev Pharmacoecon Outcomes Res. 2007 Jun;7(3):291-7
pubmed: 20528315
Br J Psychiatry. 2010 Oct;197(4):297-304
pubmed: 20884953
Soc Sci Med. 2011 Jan;72(2):185-92
pubmed: 21146909
Behav Res Ther. 2011 Nov;49(11):729-36
pubmed: 21851929
Eur Neuropsychopharmacol. 2011 Oct;21(10):718-79
pubmed: 21924589
J Med Internet Res. 2012 Nov 14;14(6):e152
pubmed: 23151820
Expert Rev Pharmacoecon Outcomes Res. 2012 Dec;12(6):745-64
pubmed: 23252357
Health Qual Life Outcomes. 2013 Sep 05;11:151
pubmed: 24010873
Patient. 2014;7(1):85-96
pubmed: 24271592
PLoS One. 2014 May 20;9(5):e98118
pubmed: 24844847
Gesundheitswesen. 2015 Jan;77(1):53-61
pubmed: 25025287
Psychol Med. 2015 Dec;45(16):3357-76
pubmed: 26235445
Am J Prev Med. 2016 Nov;51(5):852-860
pubmed: 27745685
J Affect Disord. 2018 Jan 1;225:733-755
pubmed: 28922737
Depress Anxiety. 2018 Mar;35(3):209-219
pubmed: 29329486
Int J Eat Disord. 1994 Dec;16(4):363-70
pubmed: 7866415
BMJ. 1996 Aug 3;313(7052):275-83
pubmed: 8704542
Psychol Med. 1998 May;28(3):551-8
pubmed: 9626712

Auteurs

Jennifer Beecham (J)

Personal Social Services Research Unit, London School of Economics and Political Science, Houghton Street, London WC2A 2AE, UK.
Personal Social Services Research Unit, University of Kent, Canterbury, UK.

Eva-Maria Bonin (EM)

Personal Social Services Research Unit, London School of Economics and Political Science, Houghton Street, London WC2A 2AE, UK.

Dennis Görlich (D)

Westfälische Wilhelms-Universität Münster, Institut für Biometrie und Klinische Forschung, Schmedingstraße 56, Münster, Germany.

Rosa Baños (R)

Universidad de Valencia, Spain.
CIBERObn, Instituto Salud Carlos III, Spain.

Ina Beintner (I)

TechnischeUniversität Dresden, School of Science, Faculty of Psychology, Chair ofClinical Psychology and E-Mental-Health, 01062 Dresden, Germany.

Claudia Buntrock (C)

Friedrich-Alexander Universität Erlangen-Nürnberg, Germany.

Felix Bolinski (F)

Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit Amsterdam, The Netherlands.
Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.

Cristina Botella (C)

CIBERObn, Instituto Salud Carlos III, Spain.
Jaume I University, Castellon, Spain.

David Daniel Ebert (DD)

Friedrich-Alexander Universität Erlangen-Nürnberg, Germany.

Rocio Herrero (R)

Jaume I University, Castellon, Spain.

Rachel Potterton (R)

King's College London, Institute of Psychiatry, Psychology and Neuroscience, Box P059, De Crespigny Park, London SE5 8AF, UK.

Heleen Riper (H)

Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit Amsterdam, The Netherlands.
Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.

Ulrike Schmidt (U)

King's College London, Institute of Psychiatry, Psychology and Neuroscience, Box P059, De Crespigny Park, London SE5 8AF, UK.

Karin Waldherr (K)

FernFH Distance Learning University of Applied Sciences, Zulingergasse 4, Wiener Neustadt, Austria.

Kiona Weisel (K)

Friedrich-Alexander Universität Erlangen-Nürnberg, Germany.

Anna-Carlotta Zarski (AC)

Friedrich-Alexander Universität Erlangen-Nürnberg, Germany.
Leuphana University, Innovation Incubator, Division Health Trainings Online, Lüneburg, Germany.

Michael Zeiler (M)

Medical University of Vienna, Department for Child and Adolescent Psychiatry, Waehringer Guertel 18-20, Vienna, Austria.

Corinna Jacobi (C)

TechnischeUniversität Dresden, School of Science, Faculty of Psychology, Chair ofClinical Psychology and E-Mental-Health, 01062 Dresden, Germany.

Classifications MeSH