The missingness of CER in the national discourse on preconception care is a consequence of the pervasive lack of CER studies both in medicine and public health. Although CER is an integral part of the evidence-based practice paradigm [21
], nonetheless, it has historically received considerable less attention and allocation of resources compared to other forms of clinical and epidemiological research. Indeed, recent reviews indicate that less than a third of clinical studies (i.e., randomized trials, observational studies, and meta-analyses), meet the criteria for comparative effectiveness research [23
]. Furthermore, only 2 % integrated cost-effectiveness analysis, an important component of CER.
Insufficient funds and governmental support could have contributed to the inertia in the CER field, but this situation has changed recently. In 2009 the US Congress passed the American Recovery and Reinvestment Act, in which $1.1 billion was allocated to support CER studies through Agency for Health Research Quality and the National Institutes of Health [25
]. Subsequently, the Patient Protection and Affordable Care Act of 2010, led to the creation of the Patient-Centered Outcomes Research Institute [26
], an independent non-profit organization aimed at providing leadership in conducting and disseminating CER studies. In this context, researchers in the Maternal and Child Health field must not fall behind in taking advantage of these new developments, and should strive to address priorities for CER of preconception, interconception, antenatal, and postnatal care interventions.
Because CER is a relatively recent and rapidly evolving field, its conceptual basis and its role in healthcare decision making are just being recognized and integrated in all spheres of medicine and public health. For this reason, it is not surprising that CER is missing in the preconception care framework. In the MCH context, we must recognize that the lack of CER evidence represents a gap in knowledge of what works, for whom, and under particular conditions hindering the potential of maternal and child health interventions (including preconception care). In this regard, CER studies must be clearly differentiated from research assessing the efficacy and/or the effectiveness of a single intervention (e.g., comparing active treatment with inactive treatment) which are relatively abundant in the literature. Distinctively, CER encompasses comparison of two or more different interventions in regards to their real-world effects (relative effectiveness), with or without cost considerations, among different populations groups, and diverse settings (i.e., what works, for whom, and under what conditions) [27
An important reason for the missingness of CER relates to the reluctance to embrace one of its components, namely cost-effectiveness. Conducting research on preconception interventions was one recommendation of the CDC/ATSDR Preconception Care Work Group [1
], specifically highlighting the importance of designing and conducting analyses of costbenefit and cost-effectiveness. Despite its importance, there has been very limited integration of economic evaluations into the general framework of preconceptional care especially. This represents an especially acute challenge for the full realization and integration of CER into the preconception care framework [28
]. Contrary to other subtypes of CER studies (e.g., systematic reviews, observational studies, and pragmatic trials), there has been reluctance to use cost-effectiveness analyses (CEA) due to fear of rationing the health care system and ethical issues that may arise. At a time of economic difficulties, this idea needs reconsideration under the CER framework [29
Myriad competing healthcare practices of unproven value continue to consume resources inefficiently, which points to the pressing need of considering cost data as part of the CER strategic implementation. Results from cost-effectiveness analyses can assist patients, physicians, and payers in the decision making process (although not as the main driving force) by identifying interventions that provide greater value (i.e., more population and individual health gains per unit of cost) and inform the allocation of constrained resources. Therefore, CER with inclusion of cost data could be an optimal tool in the decision/policy making process to maximize health and healthcare efficiency. Thus, obstacles associated with utilizing cost data need to be overcome to fully realize the potential of CER.
Over the past few years some researchers also identified other factors that lead to the missingness or underutilization of CER in the decision making process of health care systems, which include: lack of understanding and/or mistrust of methods [30
], ethical reasons [31
], limited availability of comparable MCH measures and instruments [32
], methodological challenges [33
]; and insufficient workforce development in CER.
Lack of Understanding
Comparative effectiveness research is relatively new to health care professionals and most of them have no training in CER methods [34
]. Therefore, it could be difficult for the majority of health professionals to understand the analytical methods that CER provides and/or readily assimilate CER-related concepts, such as quality-adjusted life years [35
]. This has lead to considerable misconceptions, for example, the misunderstanding of the role of economic evaluation in CER for decision makers in the US [36
]. Lack of consistency in CER methods, particularly, in determining which types of study designs (RCTs vs. observational) would best provide comparative effectiveness data is one important challenge that further confounds the understanding of CER.
Clinicians argue that the inclusion of comparative effectiveness and comparative costs in the process of clinical decision making is unethical. This argument is flawed since rationing is part of what healthcare professionals do routinely when they assess the evidence and implement recommendations based on quality of the evidence. Also, cost represents adverse consequences upon others due to the decisions we make and ignoring this cannot be ethical [37
]. According to Williams [37
], the most important ethical issues are rather related to which costs and/or benefits to count and how to count them. Furthermore, several authors have indicated ways to successfully apply equity values and rightfully use cost-effectiveness data, which include the application of social justice principles and the incorporation of participatory approaches. Since continuous stakeholders’ involvement is a cornerstone of CER [38
], the shared decision making process will likely facilitate the resolution of ethical concerns.
Poor Availability of Comparable MCH Measures and Instruments
One important challenge in the comparison of effectiveness measures is the lack of a uniform comparability yardstick among diverse interventions that consider different diseases or specific health effects (e.g., preterm births prevented, number of maternal complications, days of hospitalization, reduction of neural tube defects, etc.) [32
]. There is a growing trend to evaluate interventions using a standard measure, which permits comparisons across diverse interventions and diseases. One approach is to measure health effects in terms of life expectancy and health-related quality of life. For instance, a ratio for each alternative can be calculated to reflect the years of life gained (as in cost-effectiveness analyses). Life expectancy, however, does not account for the quality of years gained (for instance, an added year of life with pain is the same as an added year without pain). Quality-adjusted life years (QALYs) can compensate this limitation by combining health-related quality of life with life expectancy (1 QALY = 1 year in perfect health) [39
]. Nonetheless, the absence of valid and reliable MCH-tailored health-related quality of life scales is one of the biggest challenges of integrating CER into preconceptional care.
Comparative effectiveness research studies carry unique methodological challenges because of the focus on real-world effects and stakeholder participation [33
]. Particularly observational studies may be more vulnerable to random error or confounding variables such as other concurrent health interventions, co-morbid conditions, or other unmeasured effects. Rigorous study designs must be combined with adequate statistical techniques for generating robust CER data, which should not only mitigate these biases (e.g., propensity scoring methods and multivariate adjustment) but also the quantification of the impact of uncertainty in the decision analysis (e.g., probabilistic sensitivity analyses). Other logistical issues include the access, utilization, and proper linkage of population-based databases enhanced with cost data and clinical information. Because of the emphasis of participatory approaches in CER studies, these may be also more susceptible to systematic errors such as selection bias (bias in recruitment), and challenges in obtaining institutional review board approvals. Nevertheless, these challenges are not insurmountable with capable research teams and infrastructure.
Insufficient Workforce Development in CER Methods
A major roadblock is the lack of infrastructure particularly related to workforce development capable to implement and utilize CER findings [40
]. Fortunately, this roadblock is starting to be surpassed with the implementation of renewed support for funding in CER [25
], which may propel several system-wide changes, such as the development of educational curricula in CER-related areas by academic institutions, increased demand for CER studies from health organizations, and greater involvement of the non-academic community into the implementation and utilization of CER studies [41