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Evolution of evidence-based medicine and its role in conducting economic health evaluations

Foto Esperanza Peña

Esperanza Peña Torres
MSc Administración en Salud
MSc Epidemiología Clínica

Untimely attention to diseases, as well as deficiencies in health care, increase the burden of disease (1). For thireason, it is necessary to make interventions at the individual and collective level. Evidence from research studies shows that timely interventions and the low occurrence of medical errors increase people’s welfare states, but there is still insufficient evidence on the most appropriate way to efficiently manage health systems to reduce or address the errors of health care attention (2).

Evidence-based Medicine (EBM) emerged in the early 1990s as an initiative allowing health professionals to correctly search for and understand the available literature about health care (3). This development permitted EBM to recognize that evidence in isolation is not enough. It expanded its framework to include the expertise of recognized professionals in the subject as well as patient values and preferences. By articulating all these components, EBM is a tool that generates confidence in clinical practice during diagnosis, therapy, and other health care matters (4, 5).


The benefits of using EBM, not only includes the improvement of health care but also its contribution to the realization of cost-effectiveness studies. Health Technology Assessment (HTA) aims to compare health care interventions in order to assess their  clinical and economic values. However, in the process of conducting a HTA, the type of evidence used for cost-effectiveness studies is frequently discussed(6).


The consensus on what evidence should be used to guide decision-making processes in health care is clear; randomized clinical trials (RCT) and systematic reviews of randomized trials are regarded as achieving the highest level of quality (3). Nonetheless, the restricted availability of information, which is still one of the main limitations in academic production in health areas; not only for the costs that this implies but for ethical limitations associated with the collection and analysis of the data, complicates collection of information for  the HTA. Even if it is possible to find these studies, they frequently have a high level of internal validity but low external validity. Furthermore, most of them are not considered suited to assess population health interventions (7).


Several researchers are currently studying the use of evidence not necessarily derived from RCTs. For example, non-comparative evidence, such as the one from uncontrolled cohort studies, single-arm trials, case series and case reports, mentioned by Griffiths et al., can be used as adequate clinical evidence for HTAs “when these study designs are justifiable and when treatment effect can be convincingly demonstrated” (6).


Another alternative is the use of real-world data, nevertheless, this data should be studied with caution, as it is associated with observation bias (7). Sometimes, the lack of information for the conduction of economic studies has led to natural experiments (randomized or not), even though the absence of a guide for making natural experiments on this area can generate inaccuracies in the design, data collection, and analysis(8, 9).


EBM still has major challenges ahead; however, the options are widened, and different levels of evidence should be considered at the moment of decision making. As several authors point out, the evidence never speaks for itself, but must be placed in a context that has performance goals in health and financial sustainability (3, 10).


A health economic evaluation is a tool that compares costs and consequences of interventions and can be used with an individual or collective perspective. HTAs are techniques for economic evaluation used for decision-making at macro level in developed countries. The traditional classification of the economic evaluation includes cost minimization, cost-effectiveness, cost-utility and cost-benefit analyses. For developing countries there is still uncertainty in conducting such economic evaluations , due to some doubts regarding the adoption of the methodology. The biggest challenge in this evolutionary method is the lack of understanding of the methods currently in use by all those involved in the provision and purchase of medical care. In some countries, this methodology has been used to address issues such as public subsidies for the purchase of medicines. There is currently insufficient evidence on the impact of the use of these tools on insurance systems and the benefits for developing countries, therefore progress on this field is necessary. However, the increase in chronic disease rates, the aging of the population, and the increase in available technologies urgently demand greater economic efficiency in health systems (11).


1. Makary MA, Daniel M. Medical error—the third leading cause of death in the US. Bmj. 2016;353:i2139.

2. Broughton EI. Methodological Issues & Statistical Help the ‘how’and ‘why’of Cost-Effectiveness Analysis for Care Pathways. International Journal of Care Pathways. 2011;15(3):76-81.

3. Straus SE, Glasziou P, Richardson WS, Haynes RB. Evidence-Based Medicine E-Book: How to Practice and Teach EBM: Elsevier Health Sciences; 2018.

4. Masic I, Miokovic M, Muhamedagic B. Evidence based medicine–new approaches and challenges. Acta Informatica Medica. 2008;16(4):219.

5. Djulbegovic B, Guyatt GH. Progress in evidence-based medicine: a quarter century on. The Lancet. 2017;390(10092):415-23.

6. Griffiths EA, Macaulay R, Vadlamudi NK, Uddin J, Samuels ER. The role of noncomparative evidence in health technology assessment decisions. Value in Health. 2017;20(10):1245-51.

7. Makady A, van Veelen A, Jonsson P, Moseley O, D’Andon A, de Boer A, et al. Using real-world data in health technology assessment (HTA) practice: a comparative study of five HTA agencies. Pharmacoeconomics. 2018;36(3):359-68.

8. Deidda M, Geue C, Kreif N, Dundas R, McIntosh E. A framework for conducting economic evaluations alongside natural experiments. Social Science & Medicine. 2019;220:353-61.

9. DiNardo J. Natural experiments and quasi-natural experiments. The new Palgrave dictionary of economics. 2016:1-12.

10. Culyer AJ. Cost-effectiveness thresholds in health care: a bookshelf guide to their meaning and use. Health Economics, Policy and Law. 2016;11(4):415-32.

11. Dang A, Likhar N, Alok U. Importance of economic evaluation in health care: An Indian perspective. Value in health regional issues. 2016;9:78-83.


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