Natural and quasi-experiments

2021 ◽  
pp. 141-148
Author(s):  
Peter Craig

Natural experiments, defined as events or processes outwith the control of a researcher, which divide a population into exposed and unexposed groups, have long been used in epidemiology and public health. Evaluation methods that rely on observational rather than experimental data are classified as second best in conventional hierarchies of evidence. Natural experimental approaches have attracted renewed interest from public health researchers and decision-makers because they widen the range of interventions that can usefully be evaluated beyond those that are politically, ethically, or practically amenable to testing in randomized controlled trials. This chapter argues for seeing trials and natural experiments as part of a common toolkit for producers and users of evidence about the effectiveness of policies and programmes. It describes the most commonly used natural experimental approaches to evaluating population health interventions, and provides examples of their use in a wide range of countries and policy settings.

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
C You ◽  
V Lissillour ◽  
A Lefébure

Abstract Background The increase of life expectancy creates critical health needs that developed countries health systems have to deal with. They are also confronted to persistent health inequalities. A common vision of these issues may not be shared by the health care professionals, decision-makers and citizens. In the context of the launch of new public health laws in France, the French School of Public Health (EHESP) decided to offer a MOOC entitled “Public Health and Health System: transition and transformation” (2019). Objectives The MOOC intends to raise awareness and increase understanding of public health challenges. It is designed for a wide audience of professionals, decision-makers and citizens in the French speaking world. The content was designed by a multidisciplinary team of academics from the EHESP (N = 50) and a network of health professionals (N = 21). The 6 modules address major themes of the recent health policies, e.g. social and territorial inequalities in health, health care security, health pathways, innovation or health democracy. Results Over the course of 6 consecutive weeks, almost 7800 people have enrolled in this e-learning. They are provided with short teaching videos (109 capsules of 4-5’) and webinars, have access to a number of supplementary reading material and a variety of self-assessment. Active learning is enhanced via forum involving peers and teaching staff. The full course represents around 20 hours of teaching. So far, completion rate has attained 13% which compares well with usual rate for MOOCs. Participants include a wide range of professionals, students and citizens from 87 different countries (72% from France) and 50% had a master or higher degree. The overall satisfaction rate is 98%. Conclusions This MOOC attracted the attention of a wide and diverse audience regarding the major public health issues. Some public health agencies have expressed interest in implementing the MOOC into their professional development program of their staff. Key messages Health system reforms are constantly implemented to face new public health challenges. A multidisciplinary MOOC can help raise awareness and understanding of the issue being addressed by new policies.


2020 ◽  
Vol 40 (8) ◽  
pp. 978-989
Author(s):  
Allison L. Pitt ◽  
Jeremy D. Goldhaber-Fiebert ◽  
Margaret L. Brandeau

Background Evaluations of public health interventions typically report benefits and harms aggregated over the population. However, benefits and harms are not always evenly distributed. Examining disaggregated outcomes enables decision makers to consider health benefits and harms accruing to both intended intervention recipients and others in the population. Methods We provide a graphical framework for categorizing and comparing public health interventions that examines the distribution of benefit and harm between and within population subgroups for a single intervention and compares distributions of harm and benefit for multiple interventions. We demonstrate the framework through a case study of a hypothetical increase in the price of meat (5%, 10%, 25%, or 50%) that, via elasticity of demand, reduces consumption and consequently reduces body mass index. We examine how inequalities in benefits and harms (measured by quality-adjusted life-years) are distributed across a population of white and black males and females. Results A 50% meat price increase would yield the greatest net benefit to the population. However, because of reduced consumption among low-weight individuals, black males would bear disproportionate harm relative to the benefit they receive. With increasing meat price, the distribution of harm relative to benefit becomes less “internal” to those receiving benefit and more “distributed” to those not receiving commensurate benefit. When we segment the population by sex only, this result does not hold. Conclusions Disaggregating harms and benefits to understand their differential impact on subgroups can strongly affect which decision alternative is deemed optimal, as can the approach to segmenting the population. Our framework provides a useful tool for illuminating key tradeoffs relevant to harm-averse decision makers and those concerned with both equity and efficiency.


2019 ◽  
Vol 15 (1) ◽  
pp. 128-140 ◽  
Author(s):  
Emma Frew ◽  
Katie Breheny

AbstractLocal authorities in England have responsibility for public health, however, in recent years, budgets have been drastically reduced placing decision makers under unprecedented financial pressure. Although health economics can offer support for decision making, there is limited evidence of it being used in practice. The aim of this study was to undertake in-depth qualitative research within one local authority to better understand the context for public health decision making; what, and how economics evidence is being used; and invite suggestions for how methods could be improved to better support local public health decision making. The study included both observational methods and in-depth interviews. Key meetings were observed and semi-structured interviews conducted with participants who had a decision-making role to explore views on economics, to understand the barriers to using evidence and to invite suggestions for improvements to methods. Despite all informants valuing the use of health economics, many barriers were cited: including a perception of a narrow focus on the health sector; lack of consideration of population impact; and problems with translating long timescales to short term impact. Methodological suggestions included the broadening of frameworks; increased use of natural experiments; and capturing wider non-health outcomes that resonate with the priorities of multiple stakeholders.


2019 ◽  
Vol 74 (2) ◽  
pp. 203-208 ◽  
Author(s):  
David Ogilvie ◽  
Jean Adams ◽  
Adrian Bauman ◽  
Edward W. Gregg ◽  
Jenna Panter ◽  
...  

Despite smaller effect sizes, interventions delivered at population level to prevent non-communicable diseases generally have greater reach, impact and equity than those delivered to high-risk groups. Nevertheless, how to shift population behaviour patterns in this way remains one of the greatest uncertainties for research and policy. Evidence about behaviour change interventions that are easier to evaluate tends to overshadow that for population-wide and system-wide approaches that generate and sustain healthier behaviours. Population health interventions are often implemented as natural experiments, which makes their evaluation more complex and unpredictable than a typical randomised controlled trial (RCT). We discuss the growing importance of evaluating natural experiments and their distinctive contribution to the evidence for public health policy. We contrast the established evidence-based practice pathway, in which RCTs generate ‘definitive’ evidence for particular interventions, with a practice-based evidence pathway in which evaluation can help adjust the compass bearing of existing policy. We propose that intervention studies should focus on reducing critical uncertainties, that non-randomised study designs should be embraced rather than tolerated and that a more nuanced approach to appraising the utility of diverse types of evidence is required. The complex evidence needed to guide public health action is not necessarily the same as that which is needed to provide an unbiased effect size estimate. The practice-based evidence pathway is neither inferior nor merely the best available when all else fails. It is often the only way to generate meaningful evidence to address critical questions about investing in population health interventions.


2018 ◽  
Vol 108 ◽  
pp. 17-22 ◽  
Author(s):  
Peter Craig ◽  
Marcia Gibson ◽  
Mhairi Campbell ◽  
Frank Popham ◽  
Srinivasa Vittal Katikireddi

2018 ◽  
Author(s):  
Katherine Davis ◽  
Nicole Minckas ◽  
Virginia Bond ◽  
Cari Jo Clark ◽  
Tim Colbourn ◽  
...  

Abstract Background: Randomised controlled trials (RCTs) are widely used for establishing evidence of the effectiveness of interventions, yet public health interventions are often complex, posing specific challenges for RCTs. While there is increasing recognition that qualitative methods can and should be integrated into RCTs, few frameworks and practical guidance highlight which qualitative methods should be integrated and for what purposes. As a result, qualitative methods are often poorly or haphazardly integrated into existing trials and researchers rely heavily on standard interviews and focus group discussions. To improve current practice, we propose a framework for innovative qualitative research methods that can help address the challenges of RCTs for complex public health interventions. Methods: We used a stepped approach to develop a practical framework for researchers, which included: (1) a systematic review of the innovative qualitative methods mentioned in the health literature, (2) in-depth interviews with 23 academics from different methodological backgrounds working on RCTs of public health interventions in 11 different countries, and (3) framework development and group consensus-building process. Results: The findings are presented according to the CONSORT Statement categories for ease of use. The main challenges of RCTs for public health interventions are identified alongside each of the CONSORT categories and potential innovative qualitative methods that overcome each challenge are listed as part of a Framework for the Integration of Innovative Qualitative Methods into RCTs of Complex Health Interventions. Innovative qualitative methods raised in the interviews and discussed in detail include: rapid ethnographic appraisals, document analysis, diary methods, interactive voice responses and SMS, community mapping, spiral walks, public randomisation, pair interviews, visual participatory analysis, among others. Conclusions: The findings of this study point to the usefulness of observational and participatory methods for trials of complex public health interventions, offering a novel contribution to the broader literature about the need for mixed methods approaches. Integrating a diverse toolkit of qualitative methods can enable appropriate adjustments during RCTs, which in turn create more sustainable and effective interventions. However, this will require a cultural shift including the adoption of method-neutral research approaches, transdisciplinary collaborations, and a shift in publishing regimes.


2018 ◽  
Author(s):  
Christiana von Hippel

UNSTRUCTURED In the public health field, the design of interventions has long been considered to be the province of public health experts. In this paper, I explore an important complement to the traditional model: the design, prototyping, and implementation of innovative public health interventions by the public (users) themselves. These user interventions can then be incorporated by public health experts, who in turn design, support, and implement improvements and diffusion strategies as appropriate for the broader community. The context and support for this proposed new public health intervention development model builds upon user innovation theory, which has only recently begun to be applied to research and practice in medicine and provides a completely novel approach in the field of public health. User innovation is an assets-based model in which end users of a product, process, or service are the locus of innovation and often more likely than producers to develop the first prototypes of new approaches to problems facing them. This occurs because users often possess essential context-specific information about their needs paired with the motivation that comes from directly benefiting from any solutions they create. Product producers in a wide range of fields have, in turn, learned to profit from the strengths of these user innovators by supporting their grass-roots, leading-edge designs and field experiments in various ways. I explore the promise of integrating user-designed and prototyped health interventions into a new assets-based public health intervention development model. In this exploration, a wide range of lead user methods and positive deviance studies provide examples for identification of user innovation in populations, community platforms, and healthcare programs. I also propose action-oriented and assets-based next steps for user-centered public health research and practice to implement this new model. This approach will enable us to call upon the strengths of the communities we serve as we develop new methods and approaches to more efficiently and effectively intervene on the varied complex health problems they face.


Author(s):  
Rhiannon T. Edwards ◽  
Emma McIntosh

Chapter 3 opens with a discussion of the role of study design, the gold standard traditionally being a randomized controlled trial, and widens this to consider other types of study design such as cohort studies and natural experiments. Readers are introduced to the idea that many public health interventions are ‘complex interventions’ and there is a need for a ‘systems-based approach’ to understanding their potential effectiveness and cost-effectiveness. The chapter highlights the relevance of behavioural economics to the evaluation of public health interventions. This chapter goes on to summarize a range of challenges faced by economists, used to evaluate healthcare technologies in a healthcare setting, when they start evaluating public health interventions, which are often delivered outside the health sector in, for example, schools and workplaces. UK guidance from NICE is presented on good practice in economic evaluation of public health interventions along with ideas about how such evaluations are best reported in the literature.


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