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Methods in health systems and policy research (Editorial).
|Verlag||Health Policy 104(3):
One year ago, we refocused the scope of this journal. At that time, I wrote that Health Policy is especially interested in articles aiming to explore (1) what is happening in terms of policies, reforms, regulation, etc. of health systems, (2) from where the ideas are coming, (3) why it is happening, (4) the actors involved, (5) intended and, especially, unintended effects of these policies or reforms in terms of access, appropriateness, costs, effectiveness, quality, patient experience and equity, etc.; and (6) their final consequences in terms of health outcomes, financial protection and responsiveness to the population's legitimate expectationshttp://www.healthpolicyjrnl.com/article/S0168-8510%2812%2900021-8/fulltext#bib0005. I further explained that “we will put an emphasis on papers which employ a sound methodology, i.e. articles based on simple cross-sectional data will be increasingly rejected”http://www.healthpolicyjrnl.com/article/S0168-8510%2812%2900021-8/fulltext#bib0005, a statement which was not undisputed among the editorial team as many data sets analysed are cross-sectional by nature (e.g. surveys). In addition, many articles are, at least from an empirical standpoint, descriptive.
While this is not necessarily bad per se – and Health Policy is inviting such shorter papers on the first four topics listed above – sound assessments of effects and outcomes of health policies and reforms require other methodological approaches. Especially for comparative health systems research indicators of health systems performance need to be further developed and refined. (NB: There is also a need to further develop multidisciplinary study methods to address the variety of questions related to health systems functioning and performance.) Based on their analysis of the producers, methods and contents of 27,000 articles published between 2004 and 2009 on health systems in Europe, Velasco Garrido et al. found that in almost two-thirds of the articles, it was not possible to identify a dependent variable (in the title or abstract) used for analysing effects or outcomes – with utilisation or costs being the most frequently used dimension (in 14%), followed by satisfaction (5%), while health outcomes were analysed by a mere 4%. Thus, they came to the conclusion that there is a need to define criteria to identify high quality research (i.e. research with high validity) in health systems in a similar way as it has been done for clinical research by the evidence based medicine movement.
However, what exactly means “high quality research” when analysing health systems? Can the same criteria be applied as for assessing the effectiveness of drugs for which randomised controlled trials (RCTs) are demanded? Probably most scientists and policy-makers alike will agree that this is not possible, for example, if a new measure (say, an increase in co-payments) is legally introduced for the entire population at the same time. Does that mean we should not insist on knowing as much as possible about both the intended effects of such a policy (on utilisation and costs) as well as unintended effects (e.g. on increased inequity due to worsening access for particular groups)? Of course, we should – and this is what Health Policy is about after all. But then, what constitutes good evidence? If RCTs are impossible, should we insist on other at least (non-randomised) controlled trials, other controlled before-and-after studies, and interrupted times series only, as the Cochrane Collaboration's Effective Practice and Organisation of Care Group (EPOC) recommends? Or should other study designs be “allowed” as well to improve the scope and depth of the evidence? These are the questions which the group led by Till Bärnighausen addresses in this issue based on a meta-review of systematic reviews of health system researchhttp://www.healthpolicyjrnl.com/article/S0168-8510%2812%2900021-8/fulltext#bib0010.