Evidence map›Paper›PMID 32803521›Full record

SynthesisApplied health economics and health policy2021

Systematic Review and Critique of Methods for Economic Evaluation of Digital Mental Health Interventions.

Dina Jankovic, Laura Bojke, David Marshall, Pedro Saramago Goncalves, Rachel Churchill, Hollie Melton, Sally Brabyn, Lina Gega

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Applied health economics and health policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 3 pooled it
2.0field-weighted citation impact, top 12% of its field
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

17 citing papers in PubMed, 3 syntheses or guidelines pooled it, 35 citations in OpenAlex.

  1. Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions: A Methodological Systematic Review.Medical decision making : an international journal of the Society for Medical Decision Making · 2023
    Pooled it
  2. Pooled it
  3. Digital interventions in mental health: evidence syntheses and economic modelling.Health technology assessment (Winchester, England) · 2022
    Pooled it
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  5. Observational
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  7. In varietate concordia - cluster analysis of EQ-5D-5L value sets in European Union countries.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
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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

8 authors at 1 institution in 1 country.

Dina JankovicCentre for Health Economics, The University of York, Alcuin College, A Block, York, YO10 5DD, UK. dina.jankovic@york.ac.uk.ORCID 0000-0002-9311-1409
Laura BojkeCentre for Health Economics, The University of York, Alcuin College, A Block, York, YO10 5DD, UK.ORCID 0000-0001-7921-9109
David MarshallCentre for Reviews and Dissemination, University of York, York, UK.ORCID 0000-0001-5969-9539
Pedro Saramago GoncalvesCentre for Health Economics, The University of York, Alcuin College, A Block, York, YO10 5DD, UK.ORCID 0000-0001-9063-8590
Rachel ChurchillCentre for Reviews and Dissemination, University of York, York, UK.ORCID 0000-0002-1751-0512
Hollie MeltonCentre for Reviews and Dissemination, University of York, York, UK.ORCID 0000-0003-3837-510X
Sally BrabynDepartment of Health Sciences, University of York, York, UK.ORCID 0000-0001-5381-003X
Lina GegaDepartment of Health Sciences and Hull York Medical School, University of York, York, UK.ORCID 0000-0003-2902-9256
University of York · GB

Funding

Department of Health 17/93/06
6 · The paper itself

Abstract

objectivesInvestment in digital interventions for mental health conditions is growing rapidly, offering the potential to elevate systems that are currently overstretched. Despite a growing literature on economic evaluation of digital mental health interventions (DMHIs), including several systematic reviews, there is no conclusive evidence regarding their cost-effectiveness. This paper reviews the methodology used to determine their cost-effectiveness and assesses whether this meets the requirements for decision-making. In doing so we consider the challenges specific to the economic evaluation of DMHIs, and identify where consensus and possible further research is warranted.

methodsA systematic review was conducted to identify all economic evaluations of DMHIs published between 1997 and December 2018. The searches included databases of published and unpublished research, reference lists and citations of all included studies, forward citations on all identified protocols and conference abstracts, and contacting authors researchers in the field. The identified studies were critiqued against a published set of requirements for decision-making in healthcare, identifying methodological challenges and areas where consensus is required.

resultsThe review identified 67 papers evaluating DMHIs. The majority of the evaluations were conducted alongside trials, failing to capture all relevant available evidence and comparators, and long-term impact of mental health disorders. The identified interventions are complex and heterogeneous. As a result, there are a number of challenges specific to their evaluation, including estimation of all costs and outcomes, conditional on analysis viewpoint, and identification of relevant comparators. A taxonomy for DMHIs may be required to inform what interventions can reasonably be pooled and compared.

conclusionsThis study represents the first attempt to understand the appropriateness of the methodologies used to evaluate the value for money of DMHIs, helping work towards consensus and methods' harmonisation on these complex interventions.

Indexed as

Mental HealthCost-Benefit AnalysisHumans

Identifiers

PMID32803521
OpenAlexW3067748910

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.