You are here

Article Text

Article menu
Health policy
Original research
Economic effects of priority setting in healthcare: a scoping review of current evidence
  1. Riikka-Leena Leskelä1,2,
  2. Antero Vanhala3,
  3. Katariina Gehrmann1,
  4. Erik Haapatalo1,
  5. Jussi Ranta2,
  6. Kristiina Patja1,
  7. Ilona Kousa4,5,
  8. Pasi Tapanainen5,
  9. Pantzar Mika3,
  10. K Tikkinen6,7,
  11. Eveliina Ignatius3,
  12. Tuomas Ojanen3,
  13. Paulus Torkki8
  1. 1Faculty of Medicine, University of Helsinki, Helsinki, Uusimaa, Finland
  2. 2Nordic Healthcare Group Oy, Espoo, Finland
  3. 3University of Helsinki, Helsinki, Uusimaa, Finland
  4. 4Faculty of Social Sciences, University of Helsinki, Helsinki, Uusimaa, Finland
  5. 5Etuma Ltd, Helsinki, Finland
  6. 6Department of Urology, Helsinki University Hospital, Helsinki, Finland
  7. 7Department of Surgery, South Karelian Central Hospital, Lappeenranta, Finland
  8. 8Faculty of Medicine, University of Helsinki, Helsinki, Finland
  1. Correspondence to Riikka-Leena Leskelä; riikka-leena.leskela{at}nhg.fi

Abstract

Objectives Study objective was to map the current literature on the economic effects of priority setting at the system level in healthcare.

Design The study was conducted as a scoping review.

Data sources Scopus electronic database was searched in June 2023.

Eligibility criteria We included peer-reviewed articles published 1 January 2020–1 January 2023. All study designs that contained empirical evidence on the financial effects or opportunity costs of healthcare priority setting were included excluding disease, condition, treatment, or patient group-specific studies.

Data extraction and synthesis Two independent researchers screened the articles, and two additional researchers reviewed the full texts and extracted data. We used Joanna Briggs Institute checklists to assess the quality of qualitative, quasi-experimental and economic evaluations and the mixed methods appraisal tool for the mixed method studies. Synthesis was done qualitatively and through descriptive statistics.

Results 8869 articles were screened and 15 fulfilled the inclusion criteria. The most common study focus was health technology assessment (7/15). Other contexts were opportunity costs, effects of programme budgeting and marginal analysis, and disinvestment initiatives. Priority setting activities analysed in the studies did not achieve cost savings or cost containment (4/15) or have mixed findings at best (8/15). Only five studies found some indication of cost savings, cost containment or increased efficiency. Also, many of the studies consider costs only indirectly or qualitatively.

Conclusions All in all, there is very little research addressing the pressing question of whether explicit priority setting and priority-setting methods can support cost containment on a health service system level (regional or national). There is limited evidence of the economic effects of priority setting.

  • Health Services
  • HEALTH ECONOMICS
  • Rationing
  • Health policy
  • Review

Data availability statement

Data are available upon reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information. All data relevant to the study are included in the tables in the article or in the online supplemental file 1. Extracted data are available on request to the corresponding author.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi-org.ezproxy.u-pec.fr/10.1136/bmjopen-2024-086342

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    STRENGTHS AND LIMITATIONS OF THIS STUDY

    • We included a broad range of different economic effects in the search including both direct effects such as cost savings, cost containment as well as indirect effects such as opportunity costs.

    • Our search phrase was long and included a large variety of terms related to priority setting and health economics.

    • Since the terminology used in the context of priority setting is heterogeneous and discussion is under different disciplines, it is possible that our search strategy has missed some relevant articles.

    Introduction

    Costs of healthcare and their growth have been debated a long time from the viewpoint of affordability.1 Healthcare costs correlate with economic growth. The relationship between health expenditure and gross domestic product (GDP) has been a prominent measure used in literature, as it captures many underlying economic and societal developments.2 Various approaches, such as budget policies, price controls, volume controls or market-oriented policies, have been used to improve the cost-effectiveness of healthcare or to limit the growth of health expenditure.1

    National healthcare systems in the developed countries are based on pooled funding, which is collected either through public or private insurances or taxes or a combination of them. The pooled funding system may enable the improvement of equity and effective allocation of resources based on commonly agreed principles. However, at the same time, it brings well-known incentives and mechanisms that may drive for continuous unsustainable growth of costs.3 As resources are always limited, the health authority responsible for decisions on resource allocation or service coverage applies a priority-setting system to balance between the growing demand and available resources.4 Health authorities can be national governmental or regional officials, or insurance companies, or combination of them, depending on the healthcare system.

    Although there is no unified definition for priority setting or prioritisation, most often it has been defined as all activities and decisions at different levels of health systems that allocate healthcare resources.4–6 For example, the systems may try to limit low-value care to maximise the effectiveness of the health system or resources can be allocated from lower priority service to higher priority service. Although priority setting may also have some other objectives such as equity or access to services, the main objective is to manage the healthcare costs and allocate resources at the system level and to ensure that treatments covered by the system offer high enough a value.7–10 This is partly to tackle the challenge posed by new low-value technologies that manufacturers are trying to bring into market and thereby increasing healthcare expenditure but providing little health benefits. Although discussion on priority setting started already in the 1990s,4 it has experienced a renaissance in the past decade, as healthcare systems in the high-income countries have struggled with low economic growth, ageing populations and ever-increasing possibilities to improve health with new and expensive treatments. Thus, explicit priority setting has been thought of as one means to support an economically sustainable and acceptable healthcare system. If the health authority does not define the priority-setting principles explicitly, priority setting will take place implicitly as actors at different levels of the healthcare system, such as regional decision-makers, hospital managers and individual professionals, make independent resource-committing decisions within the limits possible for them. This in turn may lead into inequalities and reduce the acceptance of the system in the eyes of the public.

    The scope of earlier reviews on priority setting has included, for example, methods,11 principles12 13 or stakeholder involvement.14 Cromwell et al noticed that fewer than half of the items included in their review explicitly included cost-effectiveness evidence in their decision-making process.15 In addition, Stadhouder et al concluded that there is very limited evidence of the effectiveness of many widely used policies in containing healthcare costs. Furthermore, many evaluations displayed a high risk of bias.1 Furthermore, there is limited evidence on the financial effects of system-level priority setting.

    Our study aims at mapping the current literature on the economic effects of priority setting at the system level. We considered economic effects to include effects on total healthcare costs, cost-effectiveness and opportunity costs.

    Materials and methods

    A systematic scoping review was carried out to assess the scientific evidence on the economic effects of healthcare priority setting on the macrolevel in high-income countries. A scoping review was chosen because our research question is broad, and the literature falls under different fields of study, and the terminology varies, and therefore a broad and iterative mapping of literature is justified. We reported the review according to the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews.16 The search strategy is described in the online supplemental file.

    Eligibility criteria

    All study designs that contained empirical evidence on the economic effects of healthcare priority setting were included except disease, condition, treatment, or patient group-specific studies. We included scientific articles published in peer-reviewed journals between 1 January 2010–1 January 2023. We developed the search strategy first between the authors of the paper and then validated it with the steering group of the research project17 consisting of government officials from the Ministry of Social Affairs and Health and the Ministry of Finance in Finland. We developed the final search phrase with the aid of an informatician .

    Outcomes

    The primary outcome measure was total healthcare costs. The secondary outcome measures were opportunity costs, cost-effectiveness or other cost measures. Both monetary measures and service or medicine usage-related measures were considered economic outcomes.

    Search methods for identification of studies

    We searched the Scopus electronic database for scientific peer-review articles in June 2023. The search string combined relevant keywords and Medical Subject Healdings thesaurus terms for (1) priority setting, (2) costs and (3) healthcare. We performed preliminary searches to find out the terms used in earlier studies. The full search strings are reported in online supplemental table 1. We limited the language of the articles to English, Finnish, Swedish, French, Spanish, German, Danish, Norwegian, Italian or Arabic. The title and abstract needed to be available in English. We did one-step snowballing of references from resulting articles manually.

    Study selection, data extraction and risk of bias

    Two reviewers (AV and EH) independently screened search results based on titles and abstracts and evaluated eligibility of the screened articles based on full texts. Finally, PT and R-LL reviewed the full texts and consensus on eligibility was reached through discussion. We included articles that considered the economic effects of methods and implementations of priority setting in healthcare systems at macrolevel. We focused on healthcare systems in high-income countries. We defined high-income countries by following the World Bank’s income groupings.18 The inclusion and exclusion criteria are shown in box 1.

    Box 1

    The inclusion criteria for the study

    Does the study underlying the item concern with priority setting in healthcare at macrolevel (ie, state, nation, administrative region or higher) or priority-setting method(s) in general and NOT a specific illness, intervention, treatment or patient group?

    Does the study underlying the item concern with investigating, assessing, or reviewing the healthcare cost impact, effects to costs, or opportunity costs of priority setting in healthcare?

    Does the study underlying the item concern a high-income country or countries as defined by World Bank income groups?

    Is the item a scientific article, review article, short survey or a conference paper?

    Is the item language English, Finnish, Swedish, French, Spanish, German, Danish, Norwegian, Italian or Arabic?

    Is the item published in or in press for a peer-reviewed scientific journal?

    Is the full text for the item accessible?

    Finally, we extracted the data of full-text articles to Ms Excel. Data extracted included

    • type of article (original study versus review),

    • countries considered,

    • focus of priority setting,

    • objectives of the study,

    • research methods,

    • main results (qualitative and quantitative),

    • conclusions.

    We categorised the studies according to their methodology and assessed their quality through the most suitable quality appraisal checklists. We used Joanna Briggs Institute checklists for Qualitative research,19 Quasi-experimental Studies20 and Economic Evaluations21 and mixed methods appraisal tool22 for the mixed method studies. The used checklist for each study is mentioned in the Results section. The quality of the reviews was assessed based on whether they have assessed the quality of the original articles included in the review, and what type of synthesis was done.

    Data synthesis

    We categorised the articles based on their focus and objectives of the study into four categories: (1) evaluation of the effect health technology assessment (HTA), (2) evaluation of disinvestment initiatives, (3) opportunity costs and (4) evaluation of programme budgeting and marginal analysis (PBMA) initiatives. We then listed the objectives/research questions of the studies and study outcome measures used to answer the questions. Some of the articles had also qualitative objectives in addition to economic effects (eg, identification of enabler or barriers). In these cases, we only considered the objectives related to economic effects, which was our research question.

    Finally, we collected the results of the studies for each outcome measure. The findings were categorised as ‘positive’, ‘negative’ and ‘mixed’ using the effect direction plot.23 Positive refers to a finding which supports our research question of cost savings or cost containment. This means, for example, that a disinvestment initiative resulted in a reduction of the use of a low-value treatment. Negative refers to a finding, where costs increased. Mixed refers to findings where cost savings or cost containment was achieved in some assessments or initiatives, but not in others.

    Patient and public involvement

    The study was part of a governmental programme, and ministry officials were involved in designing the study objectives. Because this review did not focus on any specific patient population, we felt it would not bring added value to involve patients in setting the research question or the outcome measures or in the design or implementation of the study. No patients were asked to advise on interpretation or writing up of results.

    Results

    In total, we included 15 studies for the qualitative synthesis. Figure 1 shows the study selection process and reasons for exclusion in the full-text screening. The most common reason for rejecting the studies in the final phase was that they did not consider impact on costs. After selecting the final articles for review, one article was added via snowballing.

    Figure 1
    Figure 1

    Study selection process: the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram detailing the database searches, the number of abstracts screened and the full texts retrieved.

    Of the 15 studies included in the review, 12 were original research articles and three reviews (table 1). The most common study focus was HTA and its impact on decision-making, total costs or usage of the evaluated technology (7/15). Other contexts were opportunity costs, effects of PBMA, and disinvestment initiatives.

    View this table:
    Table 1

    Characteristics of articles included in the review

    Most common study method in the original articles was case studies (6/13) (table 1). Most case studies (4/6) were qualitative, that is, based on interviews and/or document analysis whereas two case studies combined qualitative and quantitative data. Five studies were based on statistical analysis, mainly using national-level statistics. Three of the studies based on statistical analysis also used qualitative methods to explain the association discovered in the data analysis. In these cases, either document analysis or interviews were conducted. One article was based on a simulation model.

    The original studies10 24–34 were either of medium or high quality but the reviews35–37 were assessed to be of low quality since they did not assess the quality of the articles they reviewed, and they were more descriptive than summarising reviews (table 2).

    View this table:
    Table 2

    The quality assessment of the studies

    The objective in the HTA studies was most often to assess the effects of HTA on the use or costs of the evaluated technology. The opportunity cost studies investigated either how healthcare systems accommodate the cost increase brought on by new technologies,25 29 or whether a broader range of services covered was reflected in higher deductibles or higher healthcare spend.30 The studies on disinvestment initiatives investigated, whether the initiatives resulted in reduction in the use of low-value services or cost savings,28 36 37 and what were the barriers and enablers of disinvestments.28 The PBMA studies evaluated the impact of PBMA implementations on resource allocation10 32 and the potential for cost savings or service improvements.32

    The outcome variables measured in the original research articles are presented in table 3.

    View this table:
    Table 3

    Outcomes measured in the study articles

    The results of the studies (table 2) indicate that oftentimes priority-setting activities analysed in the studies did not achieve cost savings or cost containment (4/15) or studies had mixed findings at best (8/15). Only five studies found some indication of cost savings, cost containment or increased efficiency, but two of these (Wammes et al25 and Karlsberg Schaffer et al29), which report increased efficiency, also report increases in total costs and no identifiable displacement of services due to the adoption of new interventions.

    Discussion

    We aimed at reviewing the literature on economic effects related to priority setting. We found only 15 articles that studied the economic effects of priority setting, and some of them very indirectly through comparing service coverage and healthcare spend on a national level, or the opportunity cost in terms of foregone health benefits due to inequality.27 30 Only 5/15 studies found signs of cost savings or cost containment, and out of these, one was a simulation study (ie, not based on real-world observations)24 and two concluded that the observed efficiency gains were not attributable to priority setting alone, but to cost cutting pressures in general.25 29 On the other hand, 4/15 found costs to increase and 8/15 had mixed findings.

    A major challenge with many of the studies is that they consider costs only indirectly or qualitatively: only 10/15 report results either in monetary or service/treatment volume terms, and two of these studies report only potential cost savings but do not follow-up on whether they actually materialised, and one is a simulation study. Since the outcome measures are very diverse across studies, it is impossible to conduct any kind of meta-analysis.

    The quality of the studies was assessed to be high in 7/12 of the original studies, but the earlier reviews had low quality.

    What is worrisome is that there is little evidence of cost savings or cost containment. The opportunity cost studies even conclude that the reaction from the service provider to the adoption of new treatments is to increase costs rather than look for disinvestment opportunities. The evidence seems to be most convincing on the ability of disinvestment initiatives to achieve cost savings. Peng Lim et al28 report actual cost savings, and Zechmeister and Schumacher34 found that HTA reduces the use of low-value services when used for disinvestment purposes. However, not all disinvestment initiatives are successful: Chambers et al report that the use decreased only for 38% of the low-value services targeted in disinvestment initiatives.36 Also, the literature on disinvestments is scarce, so strong conclusions cannot be drawn.

    All in all, there is very little research addressing the pressing question of whether explicit priority setting and priority-setting methods can support cost containment on a health service system level (regional or national). Most studies focus on costs related to single treatments and do not consider implications for the whole service system or payer. Many HTA studies only report the effect of the HTA on the use or costs of the treatment in question but do not discuss economic effects on the system level, for example, whether the HTA recommendation supported cost containment. This is to be expected in the sense that the primary goal of HTA is to identify treatments that are safe and effective or cost-effective enough so that their use can be recommended.38 However, many healthcare systems are economically strained, and from that perspective it would be important to also assess the effect of HTA on healthcare expenditure as a whole.

    Only a few studies focus on the opportunity costs of new treatments, that is, what happens in a healthcare system, when new cost increasing treatments are adopted. However, their findings indicate that the solution is to increase costs rather than look for targets for disinvestments. Successful disinvestment initiatives naturally do support cost containment, but their significance in the whole social and healthcare spend is not addressed. The most holistic view is taken by the studies on PBMA, which is natural, since the PBMA approach is based on considering the health budget of an organisation as a whole and analysing the health effects caused by changes in resource allocation between budget items. The PBMA studies in this review consider the priority setting on a hospital or even regional health authority level and seem to report rather positive results. However, again, the literature is scarce, so no conclusions can be drawn.

    The current literature is scarce and mostly focusing on specific priority-setting methods such as HTA, PBMA or disinvestment initiatives. Almost half of the studies analyse the economic effects of HTA. HTA usually targets new treatments, which is only a small fraction of the whole service offering, and therefore its possibilities to affect total healthcare expenditure are limited. More comprehensive approach is taken by the opportunity cost analysis and PBMA, which consider resource allocation across all services.39 However, most of these studies are conducted at the level of a hospital and only a few on the regional health authority level. Thus, conclusions on the impact of systematic priority setting on costs on the national level cannot be derived from the current literature. Future research may benefit focusing on comparing systems or countries performing explicit priority setting in high-quality natural experiment settings to better understand the causal effects to the system level.

    Priority setting and how it is done depends on the context and type of healthcare system, and therefore the terminology used is heterogeneous. For example, insurance-based systems have a different way of conducting priority setting than tax funded systems. Also, scientific discussion related to priority setting is conducted under different disciplines. Therefore, it is possible that our search strategy has missed some relevant articles, which is a limitation of our study. Also, our search was limited to peer-reviewed publications only, which left out all policy documents and reports published by governmental agencies or research institutes such as Prioriteringscentrum in Sweden or National Institute for Health and Care Excellence (NICE) in the UK.40 41

    The need for priority setting arises from the fundamentals of economics: due to limited resources, prioritisation must always be done. Cost containment in healthcare is one of the leading policy challenges1 and discussions on priority setting have been ongoing for decades, so the scarcity of empirical literature on its effects on costs is puzzling. One reason for it can be that it is difficult to study effects of priority setting on cost development; causalities are difficult to discern, and many other phenomena affect the system level costs. However, the approaches of van der Wees et al (international comparison),30 Goodwin and Frew (regional level resource allocation)32 and Peng Lim et al (national initiative)28 show that it is possible to evaluate the cost implications of system-level priority setting.

    Conclusion

    There is very little research addressing the pressing question of whether explicit priority setting and priority-setting methods can support cost containment on a health service system level (regional or national). The evidence on economic effects of priority setting is too limited to draw conclusions from. To support explicit priority setting and systematic evaluation of resource allocation between new and old treatments, more high-quality empirical research is needed, especially on the macrolevel, to understand its impacts.

    Data availability statement

    Data are available upon reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information. All data relevant to the study are included in the tables in the article or in the online supplemental file 1. Extracted data are available on request to the corresponding author.

    Ethics statements

    Patient consent for publication

    Ethics approval

    Not applicable.

    References

    1. ↵
      1. Stadhouders N,
      2. Kruse F,
      3. Tanke M, et al
      . Effective healthcare cost-containment policies: A systematic review. Health Policy 2019;123:71–9. doi:10.1016/j.healthpol.2018.10.015
      OpenUrlPubMed
    2. ↵
      1. Schakel HC,
      2. Wu EH,
      3. Jeurissen P
      . Fiscal rules, powerful levers for controlling the health budget? Evidence from 32 OECD countries. BMC Public Health 2018;18:1–17. doi:10.1186/S12889-018-5198-Y/TABLES/10
      OpenUrlCrossRefPubMed
    3. ↵
      1. Or Z,
      2. Cases C,
      3. Lisac M, et al
      . Are health problems systemic? Politics of access and choice under Beveridge and Bismarck systems. Health Econ Policy Law 2010;5:269–93. doi:10.1017/S1744133110000034
      OpenUrlPubMed
    4. ↵
      1. Ham C
      . Priority setting in health care: learning from international experience. Health Policy 1997;42:49–66. doi:10.1016/S0168-8510(97)00054-7
      OpenUrlCrossRefPubMedWeb of Science
    5. ↵
      1. Cochrane M,
      2. Ham C,
      3. Heginbotham C, et al
      . Contemporary theme. Rationing: at the cutting edge. BMJ 1991;303:1039–42. doi:10.1136/bmj.303.6809.1039
      OpenUrlFREE Full Text
    6. ↵
      1. Kapiriri L,
      2. Razavi D
      . How have systematic priority setting approaches influenced policy making? A synthesis of the current literature. Health Policy 2017;121:937–46. doi:10.1016/j.healthpol.2017.07.003
      OpenUrlCrossRefPubMed
    7. ↵
      1. Murthy VNR,
      2. Okunade AA
      . Determinants of U.S. health expenditure: Evidence from autoregressive distributed lag (ARDL) approach to cointegration. Econ Model 2016;59:67–73. doi:10.1016/j.econmod.2016.07.001
      OpenUrl
    8. ↵
      1. Keehan SP,
      2. Cuckler GA,
      3. Sisko AM, et al
      . National health expenditure projections, 2014-24: Spending growth faster than recent trends. Health Aff 2015;34:1407–17. doi:10.1377/HLTHAFF.2015.0600/ASSET/IMAGES/LARGE/2015.0600FIGEX5.JPEG
      OpenUrlAbstract/FREE Full Text
    9. ↵
      1. Peacock SJ,
      2. Mitton C,
      3. Ruta D, et al
      . Priority setting in healthcare: towards guidelines for the program budgeting and marginal analysis framework. Expert Rev Pharmacoecon Outcomes Res 2010;10:539–52. doi:10.1586/erp.10.66
      OpenUrlCrossRefPubMed
    10. ↵
      1. Cornelissen E,
      2. Mitton C,
      3. Davidson A, et al
      . Determining and broadening the definition of impact from implementing a rational priority setting approach in a healthcare organization. Soc Sci Med 2014;114:1–9. doi:10.1016/j.socscimed.2014.05.027
      OpenUrlPubMed
    11. ↵
      1. Noorani HZ,
      2. Husereau DR,
      3. Boudreau R, et al
      . Priority setting for health technology assessments: a systematic review of current practical approaches. Int J Technol Assess Health Care 2007;23:310–5. doi:10.1017/s026646230707050x
      OpenUrlCrossRefPubMed
    12. ↵
      1. Gu Y,
      2. Lancsar E,
      3. Ghijben P, et al
      . Attributes and weights in health care priority setting: A systematic review of what counts and to what extent. Soc Sci Med 2015;146:41–52. doi:10.1016/j.socscimed.2015.10.005
      OpenUrlCrossRefPubMed
    13. ↵
      1. Shah KK
      . Severity of illness and priority setting in healthcare: a review of the literature. Health Policy 2009;93:77–84. doi:10.1016/j.healthpol.2009.08.005
      OpenUrlCrossRefPubMed
    14. ↵
      1. Grill C
      . Involving stakeholders in research priority setting: a scoping review. Res Involv Engagem 2021;7:1–18. doi:10.1186/S40900-021-00318-6/FIGURES/6
      OpenUrlPubMed
    15. ↵
      1. Cromwell I,
      2. Peacock SJ,
      3. Mitton C
      . Real-world health care priority setting using explicit decision criteria: A systematic review of the literature. BMC Health Serv Res 2015;15:1–11. doi:10.1186/S12913-015-0814-3/FIGURES/4
      OpenUrlCrossRefPubMed
    16. ↵
      1. Tricco AC,
      2. Lillie E,
      3. Zarin W, et al
      . PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med 2018;169:467–73. doi:10.7326/M18-0850
      OpenUrlCrossRefPubMed
    17. ↵
      1. Torkki P,
      2. Patja K,
      3. Ignatius E, et al
      . Terveydenhuollon palveluvalikoiman priorisointi. Valtioneuvoston selvitys- ja tutkimustoiminnan julkaisusarja. 2022.
    18. ↵
      World bank income groups. 2023. Available: https://ourworldindata.org/grapher/world-bank-income-groups [Accessed 12 Aug 2024].
    19. ↵
      1. Lockwood C,
      2. Munn Z,
      3. Porritt K
      . Qualitative research synthesis: methodological guidance for systematic reviewers utilizing meta-aggregation. Int J Evid Based Healthc 2015;13:179–87. doi:10.1097/XEB.0000000000000062
      OpenUrlCrossRefPubMed
    20. ↵
      1. Barker TH,
      2. Stone JC,
      3. Sears K, et al
      . The revised JBI critical appraisal tool for the assessment of risk of bias for randomized controlled trials. JBI Evd Synth 2023;21:494–506. doi:10.11124/JBIES-22-00430
      OpenUrl
    21. ↵
      1. Gomersall JS,
      2. Jadotte YT,
      3. Xue Y, et al
      . Conducting systematic reviews of economic evaluations. Int J Evid Based Healthc 2015;13:170–8. doi:10.1097/XEB.0000000000000063
      OpenUrlCrossRefPubMed
    22. ↵
      1. Hong QN,
      2. Pluye P,
      3. Fàbregues S, et al
      . Mixed methods appraisal tool (MMAT), version 2018. 2018.
    23. ↵
      1. Boon MH,
      2. Thomson H
      . The effect direction plot revisited: Application of the 2019 Cochrane Handbook guidance on alternative synthesis methods. Res Synth Methods 2021;12:29–33. doi:10.1002/jrsm.1458
      OpenUrlPubMed
    24. ↵
      1. Barlow E,
      2. Morton A,
      3. Dabak S, et al
      . What is the value of explicit priority setting for health interventions? A simulation study. Health Care Manag Sci 2022;25:460–83. doi:10.1007/S10729-022-09594-4/FIGURES/13
      OpenUrlPubMed
    25. ↵
      1. Wammes JJG,
      2. Frederix G,
      3. Govaert P, et al
      . Case-studies of displacement effects in Dutch hospital care. BMC Health Serv Res 2020;20:1–12. doi:10.1186/S12913-020-05086-9/FIGURES/1
      OpenUrlCrossRefPubMed
    26. ↵
      1. Corbacho B,
      2. Drummond M,
      3. Santos R, et al
      . Does the use of health technology assessment have an impact on the utilisation of health care resources? Evidence from two European countries. Eur J Health Econ 2020;21:621–34. doi:10.1007/s10198-020-01160-5
      OpenUrlPubMed
    27. ↵
      1. Love-Koh J,
      2. Cookson R,
      3. Gutacker N, et al
      . Aggregate Distributional Cost-Effectiveness Analysis of Health Technologies. V H 2019;22:518–26. doi:10.1016/j.jval.2019.03.006
      OpenUrl
    28. ↵
      1. Lim BP,
      2. Heng BH,
      3. Tai HY, et al
      . Health Technology Disinvestment in Singapore. Ann Acad Med Singap 2018;47:338–44. doi:10.47102/annals-acadmedsg.V47N8p338
      OpenUrlPubMed
    29. ↵
      1. Karlsberg Schaffer S,
      2. Sussex J,
      3. Hughes D, et al
      . Opportunity costs and local health service spending decisions: A qualitative study from Wales. BMC Health Serv Res 2016;16:1–13. doi:10.1186/S12913-016-1354-1/FIGURES/1
      OpenUrlCrossRefPubMed
    30. ↵
      1. van der Wees PJ,
      2. Wammes JJG,
      3. Westert GP, et al
      . The Relationship Between the Scope of Essential Health Benefits and Statutory Financing: An International Comparison Across Eight European Countries. Int J Health Policy Manag 2016;5:13–22. doi:10.15171/ijhpm.2015.166
      OpenUrl
    31. ↵
      1. Guthrie S,
      2. Bienkowska-Gibbs T,
      3. Manville C, et al
      . The impact of the National Institute for Health Research Health Technology Assessment programme, 2003-13: a multimethod evaluation. Health Technol Assess 2015;19:1–291. doi:10.3310/hta19670
      OpenUrlCrossRefPubMed
    32. ↵
      1. Goodwin E,
      2. Frew EJ
      . Using programme budgeting and marginal analysis (PBMA) to set priorities: reflections from a qualitative assessment in an English Primary Care Trust. Soc Sci Med 2013;98:162–8. doi:10.1016/j.socscimed.2013.09.020
      OpenUrlPubMed
    33. ↵
      1. Bennie M,
      2. Dear J,
      3. Hems S, et al
      . An investigation into the effect of advice from the Scottish Medicines Consortium on the use of medicines in Scotland’s Health Service. Br J Clin Pharmacol 2011;71:283–8. doi:10.1111/j.1365-2125.2010.03826.x
      OpenUrlPubMed
    34. ↵
      1. Zechmeister I,
      2. Schumacher I
      . The impact of health technology assessment reports on decision making in Austria. Int J Technol Assess Health Care 2012;28:77–84. doi:10.1017/S0266462311000729
      OpenUrlPubMed
    35. ↵
      1. Löblová O
      . What has health technology assessment ever done for us? J Health Serv Res Policy 2018;23:134–6. doi:10.2307/26747011
      OpenUrlPubMed
    36. ↵
      1. Chambers JD,
      2. Salem MN,
      3. D’Cruz BN, et al
      . A Review of Empirical Analyses of Disinvestment Initiatives. V Health 2017;20:909–18. doi:10.1016/j.jval.2017.03.015
      OpenUrl
    37. ↵
      1. Polisena J,
      2. Clifford T,
      3. Elshaug AG, et al
      . Case studies that illustrate disinvestment and resource allocation decision-making processes in health care: a systematic review. Int J Technol Assess Health Care 2013;29:174–84. doi:10.1017/S0266462313000068
      OpenUrlCrossRefPubMed
    38. ↵
      1. Berger ML,
      2. Bingefors K,
      3. Hedblom EC, et al
      . Health Care Cost, Quality, and Outcomes. ISPOR Book of Terms. Int Soc Pharmacoecon Outcomes Res 2003.
    39. ↵
      1. Viney R,
      2. Haas M,
      3. Mooney G
      . Program budgeting and marginal analysis: A guide to resource allocation. NSW Public Health Bull 1995;6:29. doi:10.1071/NB95011
      OpenUrl
    40. ↵
      Prioriteringscentrum - linköpings universitet. Available: https://liu.se/forskning/prioriteringscentrum [Accessed 12 Aug 2024].
    41. ↵
      1. NICE
      . Homepage. Available: https://www.nice.org.uk/ [Accessed 12 Aug 2024].

    Supplementary materials

    • Supplementary Data

      This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

    Footnotes

    • Contributors R-LL: design of the work, analysis of data, drafting manuscript and guarantor. AV, KG and PT: design of the work, analysis of data and drafting manuscript. EH: analysis of data and drafting manuscript. JR: design of the work, acquisition of data and reviewing manuscript. KP, IK, PT, PM, KT, EI and TO: design of the work and reviewing manuscript.

    • Funding This work was supported by Prime Minister’s Office of Finland, grant number VN/23818/2020. Open access was funded by Helsinki University Library.

    • 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.