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Abstract
Introduction Healthcare systems face the challenge of managing limited resources while addressing the growing demand for care and the need for equitable access. Traditional cost-effectiveness analyses focus on maximising health benefits but often fail to account for how these benefits are distributed across various populations, potentially increasing health inequities. As a result, there is increasing interest in distributional cost-effectiveness analysis (DCEA), which incorporates equity considerations by explicitly assessing how health outcomes and costs are shared among diverse populations. This scoping review explores the practical application of DCEA methodology in evaluating programs and interventions. We seek to learn more about the barriers to DCEA’s application, highlighting its practical challenges, limited use globally and the steps necessary to integrate equity more effectively into implementing and adopting programs and interventions into healthcare policy and resource allocation.
Methods and analysis To evaluate the use of DCEA in the literature, a scoping review will follow Preferred Reporting Items for Systematic Reviews and Meta-Analyses—Scoping Review Extension guidelines. Systematic searches will be performed across scientific databases (MEDLINE, SCOPUS, BASE, APA Psych and JSTOR), grey literature sources (Google Custom Search Engine), and handsearching to identify eligible articles published from January 2015 to March 2025. No limits will be placed on language. Reviewers will independently chart data from eligible studies using standardised data abstraction. The collected information will be synthesised both quantitatively and narratively.
Ethics and dissemination Formal ethical approval is not necessary as this study will not collect primary data. The findings will be shared with professional networks, published in conference proceedings and submitted for peer-reviewed publication.
- Health Equity
- HEALTH ECONOMICS
- Health Care Costs
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Strengths and limitations of this study
The findings will provide valuable insights for policy-makers on the tools needed to assess the potential impacts of different programmes on public health while also addressing the issue of health inequities.
Our search strategy will include all language peer-reviewed academic publications, including books, editorials and commentary papers (previous reviews have focused only on English-language peer-reviewed academic publications and excluded books, editorials and commentary papers).
We foresee that studies may not report the implementation of distributional cost-effectiveness analysis (DCEA) due to variations in the quality of available data, especially in lower-income settings where DCEA has been less commonly used.
Introduction
Publicly funded healthcare systems must navigate the opportunity cost of deciding which treatments to fund and provide to patients. This decision-making process occurs within limited budgets amid an ever-increasing demand for healthcare services.1 As a result, it is crucial to establish priorities regarding what should be covered by public healthcare resources and what should be left to the individual decisions of patients. When determining and prioritising treatments, healthcare policy-makers typically aim to enhance overall social efficiency, minimise unjust health disparities and improve the health of the entire population.2 Health inequality refers to differences in the health status of individuals or groups, encompassing any measurable aspect of health that varies among individuals or socially relevant clusters. Health inequity, on the other hand, explicitly denotes an unfair difference in health.3 They are systematic variations in health that could be prevented through reasonable methods.4 Allowing these inequities to persist is unjust, as they represent avoidable and unnecessary distinctions. The crucial distinction between health inequality and health inequity is that the former is simply a descriptive term used when unequal quantities exist. At the same time, the latter involves a moral judgement that inequality is unjust.5
Policy-makers frequently use economic assessments to maximise health benefits and enhance healthcare efficiency. Economic evaluations involve comparing interventions based on their cost and outcomes. These evaluations may be conducted through empirical trials, mathematical models or both.6 Achieving equity and efficiency in a health intervention is challenging due to the trade-offs and limited resources and choices. Consequently, policy-makers must often strike a balance between equity and efficiency and decide whether to prioritise delivering more equitable health outcomes or more efficient health interventions.7 Decision-makers may prioritise equal access to essential healthcare over efficiency, but efficiency often precedes equity.8 A standard economic evaluation tool is the cost-effectiveness analysis (CEA), which compares interventions by roughly calculating the costs to obtain a unit of health outcomes (eg, another year of life, death prevented).9 Traditional CEA has been successful in improving efficiency in healthcare; however, it has its limitations in addressing equity issues.8 10
Distributional cost-effective analysis (DCEA) includes the idea of health equity by including information about equity while discussing the effects, distribution of costs and the value for money. The two main stages in DCEA include (1) modelling the different interventions related to social distributions and (2) assessing these social distributions of health to help reduce health inequality and improve society’s overall health.2 DCEA can explore a wide range of implications, such as whether a health programme prefers improving the health of people who are programme recipients or non-recipients. They can also look at the distribution of health burdens and benefits within the population by geography, socioeconomic status, race and age. This is to gather new information about the equity aspect of the analysis rather than just adding value judgements regarding equity.2 Traditional cost-effectiveness studies usually make value judgments about equity in a way that is implicit. For example, believing that every health-adjusted life-year is equally important is an example of DCEA making these judgements more explicit and known. It specifies the different distributional consequences that may arise and proposes ways to address them.11 In their study on DCEA, Dawkins et al noted that urban populations are far wealthier than rural populations and that rural populations experience worse lifetime health. They showed how prioritising rural populations can be seen as more equitable. They analysed this trade-off between cost-effectiveness and equity using a parameter that symbolises the strength of the person making the decisions of concern to lower health inequalities.12
DCEA studies are a relatively recent development, with most studies published after 2015. These newer studies have emphasised disease classifications, interventions and various populations.11 For example, a case study used DCEA to compare potential redesigns of a bowel cancer screening programme in England.13 The adoption of DCEA poses geographical challenges, as evidenced by its predominant use in England.14 This highlights the limited utilisation of DCEA methods in other countries, possibly attributed to its status as a relatively new concept or its complexity compared with other economic evaluation studies.11
The implementation of DCEA highlights several challenges, particularly in including equity considerations in current economic evaluation studies. These challenges include estimating the differences among different socioeconomic groups and unfamiliarity with DCEA among policy-makers.2 The challenges associated with DCEA studies stem primarily from the limited data available compared with other economic evaluation studies. Additionally, many researchers rely on health information from high-income countries, making conducting DCEA in low-income settings more difficult. Another significant challenge is data collection; when carrying out a DCEA, it is often challenging to incorporate evidence of differential uptake and evaluate the differing effectiveness between distinct groups.13 Lastly, the selection of health outcome metrics in DCEA can lead to discrimination against marginalised groups. Research indicates that metrics such as Healthy Life Expectancy may overlook health impacts among low-income populations. Ensuring high-quality data are crucial for understanding the inequalities within the studied population and assessing any changes following the intervention.10
Despite these challenges, DCEA remains one of the only methods that has not raised alarming concerns regarding its methodologies. However, it is relatively new and requires more literature to strengthen its application.10 15 It opens the door for a deeper investigation and understanding of the potential impact of this method.10 15 This study aims to explore the usage of DCEA in literature, focusing on its geographical application, implementation strategies and relevance across various fields. Furthermore, we aim to identify gaps in its utilisation, including the reasons behind its limited adoption and the challenges related to its implementation. In contrast to prior studies primarily concentrating on theoretical frameworks, we aim to demonstrate how DCEA can be implemented accurately and effectively to promote more equitable decision-making within Canadian and possibly other healthcare systems. By showcasing real-world applications, we aim to reduce the gap between theory and practice, informing policy-makers with the necessary knowledge to use DCEA in their evaluations. We aspire to make a meaningful contribution to discussions on health equity by offering actionable insights that have the potential to lead to more equitable healthcare outcomes.
Methods and analysis
This scoping review will follow Arksey and O’Malley’s modified six-step framework.16 17 The reporting of this review will be guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews standards.18
Information sources and search strategy
To identify relevant studies through a systematic search of the MEDLINE (Ovid), SCOPUS, BASE, APA Psych, JSTOR and CEA Registry databases from January 2015 (when the first DCEA was performed) to March 2025 will be performed. These databases were chosen because they contain the most articles on health economics and public health. The database search will be supplemented with hand-searching reference lists of included reviews. Grey literature will be searched using Google Custom Search Engine strategies to narrow search results and allow for more targeted results.19 20
The search strategy for the DCEA concept was adapted from Steijger et al’s systematic review of the challenges and limitations of DCEA.10 Unlike Steijger et al, our search strategy will include all language peer-reviewed academic publications, books, editorials and commentary papers.21 The Steijger et al review focused only on English-language peer-reviewed academic publications and excluded books, editorials and commentary papers.
We will use the keywords “distributional cost-effectiveness analysis,” “DCEA,” “distributional economic evaluation” and “inequality analysis” as search terms. These search terms will be tailored to each electronic database’s specific search features (eg, wildcards (*), truncations and the ability to perform complex searches). A search strategy has been developed for Medline (Ovid interface), detailed in the online supplemental appendix.
Supplemental material
Eligibility criteria
A screening checklist was created to guide this scoping review. A ‘no’ response to any study inclusion criteria (online supplemental appendix) is grounds for exclusion from the scoping review. Studies may include any population, disease area or intervention related to screening, immunisation and similar topics. Additionally, to be included, studies must follow the specific methodology outlined by Asaria et al (ie, estimating a baseline population health distribution, distribution of intervention uptake, distribution of opportunity cost and measures inequality in resulting health distributions).13 Finally, studies should provide information about the equity impacts of health technologies and programmes and the trade-offs between equity and efficiency. No limits were placed on study design, language or publication period. Non-English studies will be translated by the authors, and language translation software will be used when necessary.22
Study selection and screening process
The selection and screening studies will involve multiple steps, including searching the literature, refining the search strategy and reviewing articles for study inclusion. Three reviewers (TF, BT and AS) will examine all references independently for inclusion using the Covidence software platform for systematic reviews.23 The reviewers will retrieve the full texts of potentially eligible studies and assess their eligibility using a standardised inclusion screening checklist. Any disagreements with the reviewer were resolved through discussion, with input from a fourth author (VER) if needed. Inter-rater reliability measured using Cohen’s kappa coefficient will be evaluated at each stage of the scoping review, specifically after the title and abstract review and after the full-text review.
Extracting the data
The reviewers (TF, BT and AS) will independently extract data from eligible full-text studies using a standardised data extraction tool in Covidence. The tool will capture critical items of information from primary research reports, including study characteristics (eg, author, year of publication, location of study, study design, aim of study), DCEA-related information (eg, DCEA purpose, data collection methodology, description of intervention, outcomes assessed) and the implications of using DCEA (eg, equity effects, policy impact). Any discrepancies among reviewers will be resolved through consensus.
Collating, summarising and reporting the results
Data will be analysed and summarised descriptively. The study characteristics will be presented in tabular and graphical formats, along with a narrative summary. A narrative synthesis will be employed to outline the characteristics of DCEA studies. The process of this narrative synthesis includes three stages: (1) developing the preliminary synthesis, (2) comparing themes within and across studies and (3) classifying themes.24 In alignment with our objectives, the thematic analysis will concentrate on the application of DCEA in the literature, exploring its geographical reach, implementation strategies, data collection methodologies, interventions and impacts on equity.
Patient and public involvement
None.
Ethics and dissemination
Formal ethical approval is not required as this study will not collect primary data. The results will be shared with professional networks, published in conference proceedings and submitted for open-access peer-reviewed publication.
Discussion
The scoping review will explore the practical application of the DCEA methodology in the evaluation of programs and interventions. We will generate new insights into the global practical application of the DCEA methodology, as previous reviews have only examined English-language peer-reviewed academic publications. We will seek to provide more comprehensive information on practical challenges/barriers to DCEA’s application. Based on our findings, we will seek to recommend future steps and practical considerations of integrating equity more effectively into economic assessment programs and interventions. As policy-makers are interested in equity in health and looking to capture the broader value of assets, the DCEA Scoping Review will demonstrate the equity impact of interventions on population groups of interest. This review may be of value to policy-makers as they could be interested in how people’s health may change if a particular programme is provided. They also might be interested in whether those changes in health are the same or different across different population groups. By focusing on the equity impact and health outcomes, this review may potentially impact the implementation and design of future policies that are effective, ensuring more targeted policies. A potential limitation we anticipate is that studies may not report on the implementation of DCEA due to disparities in the quality of available data, especially in lower-income settings where DCEA has been less frequently employed. Additionally, it is worth noting that many studies using DCEA tend to originate from European settings, which may limit the methodology’s generalisability to other contexts.
Ethics statements
Patient consent for publication
Acknowledgments
We would like to acknowledge that this project was supported by the UHN Women’s Health Program Summer Studentship and UHN Pathway to Research Programme.
Footnotes
AS and VER are joint senior authors.
AS and VER contributed equally.
Contributors TF, BT, AS and VER were involved in conceptualising the project, designing the methodology, writing the original draft and reviewing and editing it. AS will serve as the guarantor.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.