Cost-effectiveness of internet-based cognitive-behavioural therapy for obsessive-compulsive disorder

Osborne, Debra; Meyer, Denny; Moulding, Richard; Kyrios, Michael; Bailey, Eleanor; Nedeljkovic, Maja

doi:10.1016/j.invent.2019.100277

Cited by 23 publications

(26 citation statements)

References 29 publications

(51 reference statements)

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“…Therapist drift is a common pattern during face-to-face CBT sessions [ 73 ], hence, reduced therapist contact during interventions coulddecrease this phenomenon potentially. Moreover, technology-delivered interventions increase cost-effectiveness [ 74 ].…”

Section: Discussionmentioning

confidence: 99%

Low intensity technology-delivered cognitive behavioral therapy for obsessive-compulsive disorder: a meta-analysis

et al. 2021

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Background Cognitive behavioral therapy (CBT) is a well-established treatment for people suffering from obsessive-compulsive disorder (OCD) and technology-based CBT applications are an emerging treatment option for people with OCD. These applications involve treatment protocols with automated content delivery and relatively low clinical contact. Whilst such CBT applications are promising, however, further investigation is needed to establish the efficacy of this treatment approach for individuals with OCD. The aim of the present study was to review the efficacy of technology-delivered CBT with minimal clinician support for OCD using a meta-analytic approach. Methods Randomized controlled trials (RCT) were identified through PsycINFO, Medline and Scopus resulting in 18 eligible studies (n = 1707). Control conditions comprised both passive (namely no treatment, other treatments and waitlist controls) and active. Measurement of OCD symptoms improvement was the outcome in each study. Results Participants in the technology-delivered CBT group scored lower on Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) (g = − 0.59, 95% CI = [− 0.99, − 0.18], p = 0.01), Y-BOCS and Dimensional Obsessive-Compulsive Scale (DOCS) combined (g = − 0.55, 95% CI = [− 0.87, − 0.24], p = 0.003) and Obsessive-Compulsive-Inventory-Revised (OCI-R) (g = − 0.36, 95% CI = [− 0.62, − 0.09], p = 0.02) at post-treatment than passive control groups. There were no significant findings when compared to controls with other treatments. Conclusions This meta-analysis suggests that technology-delivered CBT with low personal contact intensity, relative to passive control groups, is an efficacious and promising treatment option for individuals with OCD. Further research is needed to allow for a comparison with control groups with other treatments.

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Section: Discussionmentioning

confidence: 99%

Low intensity technology-delivered cognitive behavioral therapy for obsessive-compulsive disorder: a meta-analysis

et al. 2021

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“…As a result of the updated literature search, we identified 10 additional studies that met the inclusion criteria of our review and had been published over the preceding 2 years, [113][114][115][116][117][118][119][120][121][122] as shown in Figure 7. All 10 additional studies used DIs based on CBT delivered via the web/internet 113,114,[116][117][118][119]121,122 or via VR 120 or a mobile app. 115 One study used a non-CBT DI (progressive muscle relaxation).…”

Section: Updated Literature Searches and Additional Studies Retrievedmentioning

confidence: 99%

Digital interventions in mental health: evidence syntheses and economic modelling

Gega

Janković

Gonçalves

et al. 2022

Health Technol Assess

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Background Economic evaluations provide evidence on whether or not digital interventions offer value for money, based on their costs and outcomes relative to the costs and outcomes of alternatives. Objectives (1) Evaluate and summarise published economic studies about digital interventions across different technologies, therapies, comparators and mental health conditions; (2) synthesise clinical evidence about digital interventions for an exemplar mental health condition; (3) construct an economic model for the same exemplar mental health condition using the previously synthesised clinical evidence; and (4) consult with stakeholders about how they understand and assess the value of digital interventions. Methods We completed four work packages: (1) a systematic review and quality assessment of economic studies about digital interventions; (2) a systematic review and network meta-analysis of randomised controlled trials on digital interventions for generalised anxiety disorder; (3) an economic model and value-of-information analysis on digital interventions for generalised anxiety disorder; and (4) a series of knowledge exchange face-to-face and digital seminars with stakeholders. Results In work package 1, we reviewed 76 economic evaluations: 11 economic models and 65 within-trial analyses. Although the results of the studies are not directly comparable because they used different methods, the overall picture suggests that digital interventions are likely to be cost-effective, compared with no intervention and non-therapeutic controls, whereas the value of digital interventions compared with face-to-face therapy or printed manuals is unclear. In work package 2, we carried out two network meta-analyses of 20 randomised controlled trials of digital interventions for generalised anxiety disorder with a total of 2350 participants. The results were used to inform our economic model, but when considered on their own they were inconclusive because of the very wide confidence intervals. In work package 3, our decision-analytic model found that digital interventions for generalised anxiety disorder were associated with lower net monetary benefit than medication and face-to-face therapy, but greater net monetary benefit than non-therapeutic controls and no intervention. Value for money was driven by clinical outcomes rather than by intervention costs, and a value-of-information analysis suggested that uncertainty in the treatment effect had the greatest value (£12.9B). In work package 4, stakeholders identified several areas of benefits and costs of digital interventions that are important to them, including safety, sustainability and reducing waiting times. Four factors may influence their decisions to use digital interventions, other than costs and outcomes: increasing patient choice, reaching underserved populations, enabling continuous care and accepting the ‘inevitability of going digital’. Limitations There was substantial uncertainty around effect estimates of digital interventions compared with alternatives. This uncertainty was driven by the small number of studies informing most comparisons, the small samples in some of these studies and the studies’ high risk of bias. Conclusions Digital interventions may offer good value for money as an alternative to ‘doing nothing’ or ‘doing something non-therapeutic’ (e.g. monitoring or having a general discussion), but their added value compared with medication, face-to-face therapy and printed manuals is uncertain. Clinical outcomes rather than intervention costs drive ‘value for money’. Future work There is a need to develop digital interventions that are more effective, rather than just cheaper, than their alternatives. Study registration This study is registered as PROSPERO CRD42018105837. Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 1. See the NIHR Journals Library website for further project information.

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“…For instance, a cost‐utility analysis found that MindSpot was dominant relative to usual care when treating depression and anxiety — that is, it produced net cost savings and positive QALYs relative to the comparator (Lee et al 2017a). Only one cost‐effectiveness analysis has examined the impact of Mental Health Online when delivered to individuals with obsessive‐compulsive disorder (Osborne et al 2019). However, the interpretation of these study findings is hindered by the absence of an incremental analysis.…”

Section: What Is the ‘Output’ Of The Mental Health Sector And What Ismentioning

confidence: 99%

The Productivity Commission Inquiry Report into Mental Health—A Commentary from a Health Economics Perspective

Mihalopoulos¹,

Lee²,

Engel³

et al. 2021

Australian Economic Review

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The Productivity Commission's Inquiry Report into Mental Health makes extensive recommendations to improve population mental health as a means of further enhancing productivity and economic growth. While providing an invaluable high‐level vision for reforming current mental health and social systems at a programmatic level, it lacks supporting evidence that would guide implementation of specific recommendations. We discuss important methodological considerations used to measure the output of the mental health sector and present clinical and cost‐effectiveness evidence, supporting selected recommendations. We suggest the development of a broad‐based health technology assessment process to facilitate consistent decision making across health and other government sectors.

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Cost-effectiveness of internet-based cognitive-behavioural therapy for obsessive-compulsive disorder

Cited by 23 publications

References 29 publications

Low intensity technology-delivered cognitive behavioral therapy for obsessive-compulsive disorder: a meta-analysis

Low intensity technology-delivered cognitive behavioral therapy for obsessive-compulsive disorder: a meta-analysis

Digital interventions in mental health: evidence syntheses and economic modelling

The Productivity Commission Inquiry Report into Mental Health—A Commentary from a Health Economics Perspective

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