Open-access Cost-effectiveness analysis in healthcare: documentary study of theses and dissertations

Abstract

Objective  To characterize Brazilian theses and dissertations that used cost-effectiveness analysis methods in health technologies and the respective decision models.

Method  This documentary and quantitative study was carried out in February 2023 with a search in the Catalog of Theses and Dissertations (Coordination for the Improvement of Higher Education Persons) in the period 2011-2022 using the term “cost-effectiveness”. After applying the inclusion and exclusion criteria, 81 studies were included in the study and then a quantitative analysis of theses and dissertations was carried out.

Results  The majority of studies were doctoral theses (54.3%), defended in 2018 (22.2%) in southeastern Brazil (60.5%) and conducted in a hospital setting (42.0%). The Markov Decision Tree model (37.0%) (28.4%) was adopted, followed by other models. Furthermore, most theses followed the recommendations of good practices in economic cost-effectiveness analysis: they met a largely (55.6%), minimally (25.9%) and partially (18.5%) of the necessary items and recommendations.

Conclusion  The cost-effectiveness studies carried out in the theses analyzed used the Decision Tree model and followed best practice recommendations in their development.

Cost-effectiveness analysis; Health evaluation; Markov chains; Models, econometrics; Health postgraduate programs

Resumo

Objetivo  Caracterizar as teses e dissertações brasileiras que usaram métodos de análise de custo-efetividade em tecnologias de saúde e os respectivos modelos de decisão.

Métodos  Este estudo documental e quantitativo foi realizado em fevereiro de 2023 com busca no Catálogo de Teses e Dissertações (Coordenação de Aperfeiçoamento de Pessoas de Nível Superior) no período 2011-2022 usando o termo “custo-efetividade”. Após a aplicação dos critérios de inclusão e exclusão, 81 produções foram incluídas no estudo e então foi realizada a análise quantitativa das teses e dissertações.

Resultados  A maioria das produções era de teses de doutorado (54,3%) defendidas em 2018 (22,2%) na região sudeste do Brasil (60,5%) e conduzidas em ambiente hospitalar (42,0%). Foi adotado o modelo de Árvore de Decisão (37,0%) de Markov (28,4%), seguido de outros modelos. Além disso, a maioria das teses seguiu as recomendações de boas práticas na análise econômica de custo-efetividade: elas atenderam grande parte (55,6%), minimamente (25,9%) e parcialmente (18,5%) os itens necessários e recomendações.

Conclusão  Os estudos de custo-efetividade realizados nas teses analisadas usaram o modelo de Árvore de Decisão e seguiram as recomendações de boas práticas em seu desenvolvimento.

Análise de custo-efetividade; Avaliação em saúde; Cadeias de Markov; Modelos econométricos; Programa de pós-graduação em saúde

Resumen

Objetivo  Caracterizar las tesis de doctorado y de maestría brasileñas que utilizaron métodos de análisis de costo-efectividad en tecnologías de salud y los respectivos modelos de decisión.

Métodos  Este estudio documental y cuantitativo fue realizado en febrero de 2023 con búsqueda en el Catálogo de Tesis de Doctorado y de Maestría (Coordinación de Perfeccionamiento de Personas de Nivel Superior) durante el período 2011-2022 usando el término “costo-efectividad”. Después de aplicar los criterios de inclusión y exclusión, se incluyeron 81 producciones en el estudio y luego se realizó el análisis cuantitativo de las tesis de doctorado y de maestría.

Resultados  La mayoría de las producciones fue de tesis de doctorado (54,3 %) defendidas en 2018 (22,2 %) en la región Sudeste de Brasil (60,5 %) y llevadas a cabo en ambiente hospitalario (42,0 %). Se adoptó el modelo de Árbol de Decisión (37,0 %) de Markov (28,4 %), seguido por otros modelos. Además, la mayoría de las tesis siguió las recomendaciones de buenas prácticas en el análisis económico de costo-efectividad: cumplieron gran parte (55,6 %), mínimamente (25,9 %) y parcialmente (18,5 %) los ítems necesarios y recomendaciones.

Conclusión  Los estudios de costo-efectividad realizados en las tesis analizadas utilizaron el modelo de Árbol de Decisión y siguieron las recomendaciones de buenas prácticas en su desarrollo.

Análisis de costo-efectividad; Evaluación en salud; Cadenas de Markov; Modelos econométricos; Programas de posgrado en salud

Introduction

The escalation in healthcare spending has been presented as a problem within national financial constraints. Furthermore, there is a lack of knowledge about the real cost of providing healthcare services to users in a scenario of population aging with overlapping acute and chronic conditions.1,2 Thus, health systems, which have limited resources, are facing increasing pressure to meet growing population demand. To do this, they need to improve their efficiency, avoid wasting resources by applying economic assessment methods.3

In parallel with financial restrictions, the launch of new technologies and the pressure for their incorporation in the healthcare sector attract attention around the world. National health systems seek to protect the sector by reducing the negative economic impact and ensuring access to users. In Brazil, technology assessment methods have been developed to manage their introduction into the Brazilian Health System (SUS – Sistema Único de Saúde).4

Health technology assessment (HTA) is a comprehensive process through which the clinical, social and economic impacts of health technologies are assessed. Its objective is to help in making assertive decisions about the incorporation of new technologies into the system.5 Thus, the HTA process assessed safety, efficacy, effectiveness, clinical indications and the benefiting population considering the burden of the disease and its impact on society. HTA’s economic aspect consists of assessing costs with cost-effectiveness (CEA), cost-utility, cost-benefit, cost-minimization and budgetary impact analysis. As for patients, the following items are considered: characteristics and social impact of the disease, relevance and benefit of technologies already used, demands not yet addressed, including acceptability, convenience and ethical aspects regarding the incorporation of a new product or process.6HTA’s organizational aspect also includes assessment of dissemination feasibility, professional training, optimized use of resources, monitoring of results and sustainability of the new technology.7

Health technologies’ CEA allows to compare costs (in monetary units) and results (in non-monetary units). In other words, it deals with clinical impacts, the relationship between costs and benefits of a given health treatment.8 CEA-type economic assessment studies are relevant as they simultaneously assess the costs and effectiveness of the technology used. Furthermore, economic issues (such as cost-effectiveness) must be considered when choosing a technology, as this contributes to the most appropriate option for both patients (regarding the most effective technology) and institutions when choosing the most cost-effective technology.9

Therefore, it is important to know the academic production (theses and dissertations) on methodologies used in CEA of health technologies in the country. Furthermore, it is essential to assess how these studies were conducted in terms of best practice recommendations. Considering the academic role of generating scientific knowledge, studies must present specific items to be transparent, replicable, interpretable and understandable.9 More than that, such studies can identify gaps in existing knowledge, thus contributing to adopting the methodological rigor recommended by good practices and enabling more robust and quality approaches and results for more assertive health decisions.10,11

Therefore, we questioned the following: what are the characteristics of Brazilian academic production that applied CEA methods in health technologies and what decision models were adopted? Therefore, this study aimed to characterize Brazilian theses and dissertations that used CEA methods in health technologies and the respective decision models.

Methods

This was a documentary study with a quantitative approach carried out after searching the Thesis and Dissertation Catalog (Coordination for the Improvement of Higher Education Personnel, CAPES CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior); Ministry of Education). The search was carried out in February 2023 by the main researcher using the term “cost-effectiveness” (structured vocabulary from the Health Sciences Descriptors (DeCS)). Filters were applied in the large knowledge area “health sciences” and temporal fields to restrict the theses and dissertations defended in the period 2011-2022. The year 2011 was chosen because it was the year when the Brazilian National Commission for the Incorporation of Technologies into the Brazilian Health System (CONITEC - Comissão Nacional de Incorporação de Tecnologias no Sistema Único de Saúde) was established in Brazil (Decree 7,646; 12/21/2011).6

Theses and dissertations on CEA, linked to the area of health sciences, developed in Brazil and defended from 2011 onwards, were included. Theses and dissertations that did not present CEA with the respective decision model in the abstracts were excluded. Furthermore, those where the file was not available in full were excluded. To collect the data, an instrument was developed that included the following characterization items: year of defense; study design; geographic region of the university of origin; institution; graduate program; methodological approach; method; target population; study perspective; context; time horizon; technology (intervention and comparator); willingness to pay threshold; discount rate; currency; costs; effectiveness; sensitivity analysis; budgetary impact; model assumptions; and decision model used. The items listed in the instrument were based on the components recommended for preparing CEA according to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS).9 Thus, to classify the level of quality of the findings based on an economic assessment study,12 the following stratification parameters were adopted: meet the recommendations minimally (<40% of items: reasonable quality), partially (41-80% of items: moderate quality), and largely (>80% of items: good quality).

The initial search yielded 43,676 results, 4,229 of them were linked to the broad area of health sciences, resulting in a final sample of 932 studies (including studies from 2011 onwards). The selection of this material was carried out independently by two reviewers, and the result of their consensus is presented in a flowchart in Figure 1 (adapted from Preferred Reporting Items for Systematic Review and Meta-Analyses, PRISMA).13 To access full texts, database tools and Google searches were used.

Figure 1
Theses and dissertations selection process (adapted from PRISMA)

Data analysis consisted of extracting information from each thesis or dissertation. To describe the selected studies, a synoptic table prepared for this purpose was used with year of publication, institution, area of knowledge, study design, participants and research setting, level of academic training, as well as the model of decision used for CEA. Descriptive statistical analysis (absolute and relative frequencies) was performed using the Excel program (Microsoft Office, 2010).

As this study was documentary research, and all information is in the public domain, it was not necessary to be assessed by a Research Ethics Committee. However, ethical aspects related to authorship and insertion of citations were respected.

Results

The study included 81 academic productions (theses and dissertations) that applied the CEA methodology to assess technologies for the health sector (8.7% of the total studies in the period investigated). Most studies were presented in 2018 (22.2%); they were theses (44; 54.3%) and dissertations (37; 45.7%) from institutions in the Southeast (48; 60.5%), South (17; 19.8%), Midwest (10; 12.3%) and Northeast (6; 7.4%). The Universidade de São Paulo presented the highest production (20; 24.7%), followed by the Universidade Federal do Rio Grande do Sul (8; 9.8%), Universidade Federal do Estado do Rio de Janeiro (6; 7.4 %) and Universidade Federal do Paraná (5; 6.1%), these being the five most observed institutions. The five graduate programs with the highest production were health sciences (20; 24.7%), followed by public health (19; 23.4%), nursing (11; 13.6%), pharmaceutical sciences (9; 11.1%), dentistry (3; 3.8%), HTA (2; 2.5%) and health assessment (1; 1.2%). Concerning the method used, observational (21; 25.9%), hypothetical cohort (14; 17.2%), economic assessment (11; 13.6%), systematic review (9; 11.1%), clinical trial (4; 5.0%), followed by other method studies (one study for each method; 22; 27.2% predominated). Most of studies were carried out in a hospital setting (42.0%), involving patients undergoing treatment (42.0%). In relation to the types of decision model for CEA, the Decision Tree was the most used model (30; 37.0%), followed by the Markov model (23; 28.4%). The Markov Model and the Decision Tree were used together (3; 3.7%), and the Dynamic Model was used alone (1; 1.2%) in the analyses. In some studies, other methods were used to assess cost-effectiveness (4; 5.0%); in other studies, the model used was not specified (20; 24.7%). In terms of compliance, the studies largely (45; 55.6%), minimally (21; 25.9%) and partially (15; 18.5%) met the items recommended by CHEERS 9 (Chart 1).

Chart 1
Synthesis of studies included in the study and compliance with the items recommended in CHEERS

Table 1 presents a compilation of recommendations and/or items to prepare an economic analysis (including cost-effectiveness). The majority of productions presented the recommended items for preparing CEA as recommended by CHEERS.

Table 1
Items recommended by good practices for preparing cost-effectiveness analyzes presented in Brazilian theses and dissertations in health

Discussion

In Brazil, higher education institutions offer lato sensu, stricto sensu and short-term courses to improve knowledge in the area of economic assessment in health. They also offer courses that make it possible to assess technologies relevant to the healthcare system. Graduate programs in = health play a fundamental role in advancing technical and scientific knowledge, contributing to training qualified human resources. Thus, people can be trained in economic analysis and more assertive decision-making, positively influencing the implementation of SUS actions and services and promoting their sustainability.14

Brazilian researchers who carry out investigations in health economics are mostly doctors.15Our findings agree with this statement because theses are more available in the CAPES thesis and dissertation catalog. Furthermore, the large area of knowledge in which health assessment research groups operate (where economic assessments are inserted) is predominantly health sciences.16

The year 2018 was highlighted by a greater number of theses and dissertations defenses (18; 22.2%) that used CEA methodologies in health technologies. This number may be related to the economic crisis in the Brazilian healthcare sector that began in 2016 with the implementation of a spending cap. This ceiling limited spending in several health sectors and may have influenced the carrying out of studies on economic assessment. Furthermore, 2018 was marked by a significant increase in the incorporation of new health technologies into the Brazilian market. This reinforces the idea that production and questioning about health costs and effectiveness have expanded among researchers and professionals working in the area.17

The number of graduate programs and research groups on economic assessment in southeastern Brazil is significantly greater, mainly in São Paulo. This is seen as a disparity in the national distribution of programs due to their high concentration in this region of the country.16,18 This scenario can also be seen in the data from the present study, with the vast majority of studies developed in this region, and almost a quarter produced at the Universidade de São Paulo. Regarding the graduate program from which the studies originated, the area of health sciences was highlighted (24.7%). Our results agree with this highlight.

A quantitative methodological approach was adopted in thesis and dissertation analysis, reflecting the methodologies applied. This is because the quantitative approach is the most used statistical method to analyze results as well as to develop models and verify costs and consequences in economic studies.11 In relation to the method adopted, observational studies (25.9%), followed by hypothetical cohort studies (17.2%), stood out. Furthermore, there are many possible data sources to develop economic assessments as primary source data from research and secondary data obtained from the literature can be used.11

As for Decision Models, the majority of theses and dissertations (75.3%) adopted some type of model. It is recommended to describe the structure of the chosen model and justify the choice. Furthermore, it is advisable to consider time horizon and the nature of the technology assessed (whether linked to chronic or acute diseases). It is recommended to make a graphical presentation of the model structure and patient flow throughout the model.9In theses and dissertations, the decision model most used for CEA was the Decision Tree, followed by the Markov Model. The Decision Tree is a simple assessment method, appropriate for acute events and short time horizons, and is suitable for individuals with similar attributes. The model requires little data preparation (numerical or categorical) and can be validated through statistical tests.19 Furthermore, the Decision Tree can be easily interpreted and understood, helping to reduce the time needed to make a decision regarding the most cost-effective treatment.20 Differently, the Markov method is used in chronic conditions or over a longer time horizon, and its elaboration, calculation and analysis are relatively accessible.19, 21

Most (45; 55.6%) studies followed good practices in conducting CEA, having presented the recommended items for these analyzes.9 Regarding recommended items, most studies had patients undergoing treatment as their target population (34; 42.0%). In economic assessments, the target population description is essential as its description can modify the economic impact of any intervention. Furthermore, costs and consequences can vary significantly depending on participant and research setting and/or context characteristics.9

As for the perspective, most studies adopted the SUS perspective, which refers to the point of view from which the problem is judged (i.e., the payer of the services described in the analysis). The objective of this study is directly linked to the perspective, as both will indicate the costs that will be measured.10 Brazil is a country that invests in health technologies (mainly within the scope of SUS) to ensure the constitutional right to universal access to health. Therefore, managers must engage with economic issues, a necessary aspect for health system sustainability.14 In 2018, the SUS presented an annual expenditure (on purchases of products and technologies) greater than 20 billion reais (Brazilian currency).22 Therefore, it is understandable that all these factors may have considered study development in this perspective.

This study took place predominantly at hospitals. This follows a review that revealed the existence of hospitals in Brazil with HTA centers. Furthermore, hospital institutions are partners in this type of research to help managers make assertive decisions.23 Knowledge about hospital costs can help develop a more comprehensive and prepared approach to organizing and optimizing patient care and resource allocation.11,24,25

In most studies, a time horizon of 1-4 years was adopted. In general, time horizon presents the relationship with the natural course of the health condition analyzed to assess the potential impact of interventions, thus representing the study duration.10

Most studies assessed pharmacological (38; 46.9%) technologies (intervention and comparators), reflecting a global scenario of significant increase in the production and incorporation of hard technologies (equipment, medicines, procedures, etc.)10 In relation to interventions and comparators, a detailed description of their complexity, forms of presentation, application and/or use, and duration of administration (in the case of medication dosage) is necessary as they are directly linked and influence costs and effectiveness.9

Willingness to pay threshold was not adopted in the majority of studies (51; 62.9%); it refers to the amount that the institution is willing to pay for incorporating the new technology. Care must be taken with this item as not all study designs apply to or reflect willingness to pay.9 As for discount rate (45; 55.6%), studies did not present this item in the study. Although its value varies depending on the country of origin of the research, its use is relevant as adjusting costs and the consequences of inflation help to reflect changes in prices over time.11 As for currency, the vast majority (53; 65.4%) did not specify this in studies. In general, it is recommended that currency be the first piece of information when valuing cost items.10In addition, it is necessary to describe the year of conversion, dates of unit costs and estimates made as well as price adjustment methods (when used).9

Concerning costs, healthcare service production basically involves human, material, service and structural resources. In general, each assistance provided to a patient uses several resources that may vary and be repeated in other services; hence, the difficulty in determining the costs of a specific service and the need for methodologies to systematize the cost calculation process. Furthermore, cost is a relevant factor for study reproducibility; therefore, the items included in the analysis, selection criteria and data source must be described.10

Effectiveness is an essential factor in developing a health economic assessment (especially in CEA), as this method requires selecting one or more outcome measures that reflect harm and effectiveness. The studies analyzed (69; 85.2%) described this item as it is necessary to inform what will be considered effective and the methods for measuring effectiveness.9

The study identified sensitivity analysis (52; 64.2%) in studies. The method for analyzing this item may vary. Most studies use Monte Carlo simulation as it is one of the most traditionally used metrics. However, other methods (such as Tornado Diagram) are increasingly being reported.9 Monte Carlo simulation is a technique for assessing the uncertainty regarding any covariate included in the economic model. Uncertainty is an inherent factor in any economic assessment, and it is necessary to analyze its impact on the result.26,27 Budget impact refers to one of the final stages of HTA, being an assessment of the financial consequences caused by the adoption and/or incorporation of a health technology in a given scenario within up to five years. This type of analysis helps managers make decisions because it estimates the financial feasibility of a certain technology in a healthcare service or system.28 However, only 8 (9.9%) of studies analyzed assessed the budgetary impact.

The model’s premises are based on the assumptions that will be adopted by the author and/or researcher in relation to the outcome of their analysis. This may cause concern as the choice of one parameter over another (or the formulation of a specific assumption) may induce bias in the model, influencing technology assessment in a favorable or unfavorable way.26

The function of economic assessment is to provide clear information to support decision-making. Its role is to determine the investment necessary to obtain specific benefits in a group of patients with different health problems.29 CEA has become an important tool for professionals and managers in the public health system,30 as it helps institutions with sustainability. To achieve this, it is important to create partnerships with educational institutions to train qualified human resources.10 CEA applicability is relevant to providing assistance and managing health as it enables greater assertiveness in decision-making regarding health technology use.

As limitations of this study, it is important to consider that the search for studies was restricted to the CAPES portal, and some analyzes were hampered by the lack of clarity in the methodological path presentation in some studies. However, this survey provided a comprehensive view of CEA methodologies and the decision model most used in health research in the context of Brazilian graduate studies. Knowing this scenario is essential to improve research, clinical practice and health management. The results of this study allow to identify opportunities, challenges and trends, in addition to encouraging the adoption of best practices in the development of robust and quality CEA, thus contributing to a more efficient, effective and sustainable health system.

The findings presented contribute to identifying gaps in Brazilian academic production on the topic. For instance, there was a lack of production assessing the cost-effectiveness of non-pharmacological technologies. Therefore, conducting studies focused on this methodology is essential to train human resources to make good health decisions. Furthermore, it is important that researchers adopt best practice recommendations for carrying out health economic assessments. This will allow the development of more transparent studies, which are easy to understand, interpret and replicate.

Conclusion

Brazilian academic production in health analyzed the cost-effectiveness of health technologies, with a peak in 2018. Most studies were carried out at a doctoral level within graduate programs in southeastern Brazil, mainly at the Universidade de São Paulo. In the methodological design, observational studies stood out using the Decision Tree model to analyze the cost-effectiveness relationship (CEA). Most studies followed good practice recommendations for CEA, presenting the main items recommended for developing this type of study.

Acknowledgements

For financial support from the CAPES of the Ministry of Education (Code 001).

References

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Edited by

Publication Dates

  • Publication in this collection
    04 Oct 2024
  • Date of issue
    2024

History

  • Received
    10 Oct 2023
  • Accepted
    6 May 2024
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