Background

Evidence-to-decision (EtD) frameworks provide a structured and transparent approach for groups of experts to use when formulating recommendations or making decisions. While extensively used for clinical and public health recommendations, EtD frameworks are not in widespread use in environmental health. This review sought to identify, compare and contrast key EtD frameworks for decisions on interventions used in clinical medicine, public health or environmental health. This information can be used to develop an EtD framework suitable for formulating recommendations for interventions in environmental health.

Methods

We identified a convenience sample of EtD frameworks used by a range of organizations. We searched Medline for systematic reviews of frameworks. We summarized the decision criteria in the selected frameworks and reviews in a qualitative manner.

Findings

Fourteen organizations provided 18 EtD frameworks; most frameworks focused on clinical medicine or public health interventions; four focused on environmental health and three on economic considerations. Harms of interventions were examined in all frameworks and benefits in all but one. Other criteria included certainty of the body of evidence (15 frameworks), resource considerations (15), feasibility (13), equity (12), values (11), acceptability (11), and human rights (2). There was variation in how specific criteria were defined. The five identified systematic reviews reported a similar spectrum of EtD criteria.

Interpretation

The EtD frameworks examined encompassed similar criteria, with tailoring to specific audience needs. Existing frameworks are a useful starting point for development of one tailored to decision-making in environmental health.

Funder

JPB Foundation.

Objective

To assess the effectiveness of interventions aimed to increase retinal screening among people with diabetes.

Methods

A systematic literature search was conducted of multiple electronic bibliographic databases up to May 2005. Studies were included if interventions were used to promote screening for diabetic retinopathy in any language and with any study design.

Results

Forty-eight studies (12 randomized controlled trials [RCTs], four nonrandomized studies, and 32 pre-post studies) with a total of 162,157 participants, examined a wide range of interventions, which focused on one or more of the following: (1) patients or populations, (2) providers or practices, and (3) healthcare system infrastructure and processes. Four of five RCTs focusing on patients demonstrated that interventions increased screening significantly, with relative risk ranging from 1.05 (95% confidence interval [CI]=1.01-1.08) to 2.01 (95% CI=1.48-2.73). Five RCTs with a focus on the system all demonstrated significant increases in screening with relative risk ranging from 1.12 (95% CI=1.03-1.22) to 5.56 (95% CI=2.19-14.10). Thirty-six non-RCTs, which included interventions with single or multiple foci, also generally demonstrated positive effects.

Conclusions

Increasing patient awareness of diabetic retinopathy, improving provider and practice performance, and improving healthcare system infrastructure and processes, can significantly increase screening for diabetic retinopathy. Further research should explore strategies for increasing the rate of retinal screening among diverse or disadvantaged populations and the economic efficiency of effective interventions in large community populations.

Mathematical modeling studies are frequently conducted to guide policy in global health. However, the contribution of mathematical modeling studies to World Health Organization (WHO) guideline recommendations, and the quality of evidence contributed by these studies remains unknown. We conducted a systematic review of the WHO Guidelines Review Committee database to identify guideline recommendations that included evidence from mathematical modeling studies since inception of the Guidelines Review Committee on 1 December, 2007. We included WHO guideline recommendations citing a mathematical modeling study in the primary evidence base. We defined a mathematical model as a framework that predicted epidemiologic, health or economic impact of an intervention or decision in the clinical or public health context. The primary outcome was inclusion of evidence from mathematical modeling studies in a guideline recommendation. We evaluated each unique modeling study across multiple domains of quality. Between 1 December 2007 and 1 April 2019, the WHO Guidelines Review Committee approved 154 guidelines providing 1619 guideline recommendations. Mathematical modeling studies informed 46 WHO guidelines (29.9%) and 101 unique guideline recommendations (6.2%). Modeling evidence addressed topics related to infectious diseases in 38 guidelines (82.6%) and 81 recommendations (80.2%), most commonly for HIV and tuberculosis. Evidence from modeling studies was assessed in the GRADE evidence profile for 12 recommendations (12.9%) and GRADE evidence-to-decision framework for 45 recommendations (44.6%). Modeling-informed recommendations were more likely than other recommendations within the same guidelines to be issued with a "conditional" rather than "strong" strength of recommendation (53.5% versus 37.8%), and the evidence underlying modeling-informed recommendations was more likely to be assessed as very low quality (41.6% versus 24.1%). Upon review of individual modeling studies, we estimated that 33.8% of models performed a calibration, 29.4% of models performed a validation of results, and 20.6% of models reported a change in the study conclusion in the sensitivity analysis. While policy recommendations in WHO guidelines are informed by evidence from modeling studies, the validity of modeling studies included in guidelines development is heterogeneous. Quality assessment is needed to support the evaluation and incorporation of evidence from mathematical modeling studies in guidelines development.

Background

In February 2021, over one hundred scientists and policy experts participated in a web-based Workshop to discuss the ways that divergent evaluations of evidence and scientific uncertainties are used to delay timely protection of human health and the environment from exposures to hazardous agents. The Workshop arose from a previous workshop organized by the European Environment Agency (EEA) in 2008 and which also drew on case studies from the EEA reports on 'Late Lessons from Early Warnings' (2001, 2013). These reports documented dozens of hazardous agents including many chemicals, for which risk reduction measures were delayed for decades after scientists and others had issued early and later warnings about the harm likely to be caused by those agents.

Results

Workshop participants used recent case studies including Perfluorooctanoic acid (PFOA), Extremely Low Frequency - Electrical Magnetic Fields (ELF-EMF fields), glyphosate, and Bisphenol A (BPA) to explore myriad reasons for divergent outcomes of evaluations, which has led to delayed and inadequate protection of the public's health. Strategies to overcome these barriers must, therefore, at a minimum include approaches that 1) Make better use of existing data and information, 2) Ensure timeliness, 3) Increase transparency, consistency and minimize bias in evidence evaluations, and 4) Minimize the influence of financial conflicts of interest.

Conclusion

The recommendations should enhance the production of "actionable evidence," that is, reliable evaluations of the scientific evidence to support timely actions to protect health and environments from exposures to hazardous agents. The recommendations are applicable to policy and regulatory settings at the local, state, federal and international levels.