Visual Analytics for Public Health: Supporting Knowledge Construction and Decision-Making

Author(s):  
Samar Al-Hajj ◽  
Ian Pike ◽  
Bernhard Riecke ◽  
Brian Fisher
Author(s):  
Bronwyn Ashton ◽  
Cassandra Star ◽  
Mark Lawrence ◽  
John Coveney

Summary This research aimed to understand how the policy was represented as a ‘problem’ in food regulatory decision-making in Australia, and the implications for public health nutrition engagement with policy development processes. Bacchi’s ‘what’s the problem represented to be?’ discourse analysis method was applied to a case study of voluntary food fortification policy (VFP) developed by the then Australia and New Zealand Food Regulation Ministerial Council (ANZFRMC) between 2002 and 2012. As a consultative process is a legislated aspect of food regulatory policy development in Australia, written stakeholder submissions contributed most of the key documents ascertained as relevant to the case. Four major categories of stakeholder were identified in the data; citizen, public health, government and industry. Predictably, citizen, government and public health stakeholders primarily represented voluntary food fortification (VF) as a problem of public health, while industry stakeholders represented it as a problem of commercial benefit. This reflected expected differences regarding decision-making control and power over regulatory activity. However, at both the outset and conclusion of the policy process, the ANZFRMC represented the problem of VF as commercial benefit, suggesting that in this case, a period of ‘formal’ stakeholder consultation did not alter the outcome. This research indicates that in VFP, the policy debate was fought and won at the initial framing of the problem in the earliest stages of the policy process. Consequently, if public health nutritionists leave their participation in the process until formal consultation stages, the opportunity to influence policy may already be lost.


2021 ◽  
pp. medethics-2020-107134
Author(s):  
Thana Cristina de Campos-Rudinsky ◽  
Eduardo Undurraga

Although empirical evidence may provide a much desired sense of certainty amidst a pandemic characterised by uncertainty, the vast gamut of available COVID-19 data, including misinformation, has instead increased confusion and distrust in authorities’ decisions. One key lesson we have been gradually learning from the COVID-19 pandemic is that the availability of empirical data and scientific evidence alone do not automatically lead to good decisions. Good decision-making in public health policy, this paper argues, does depend on the availability of reliable data and rigorous analyses, but depends above all on sound ethical reasoning that ascribes value and normative judgement to empirical facts.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Margaret M. Padek ◽  
Stephanie Mazzucca ◽  
Peg Allen ◽  
Emily Rodriguez Weno ◽  
Edward Tsai ◽  
...  

Abstract Background Much of the disease burden in the United States is preventable through application of existing knowledge. State-level public health practitioners are in ideal positions to affect programs and policies related to chronic disease, but the extent to which mis-implementation occurring with these programs is largely unknown. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Methods A 2018 comprehensive survey assessing the extent of mis-implementation and multi-level influences on mis-implementation was reported by state health departments (SHDs). Questions were developed from previous literature. Surveys were emailed to randomly selected SHD employees across the Unites States. Spearman’s correlation and multinomial logistic regression were used to assess factors in mis-implementation. Results Half (50.7%) of respondents were chronic disease program managers or unit directors. Forty nine percent reported that programs their SHD oversees sometimes, often or always continued ineffective programs. Over 50% also reported that their SHD sometimes or often ended effective programs. The data suggest the strongest correlates and predictors of mis-implementation were at the organizational level. For example, the number of organizational layers impeded decision-making was significant for both continuing ineffective programs (OR=4.70; 95% CI=2.20, 10.04) and ending effective programs (OR=3.23; 95% CI=1.61, 7.40). Conclusion The data suggest that changing certain agency practices may help in minimizing the occurrence of mis-implementation. Further research should focus on adding context to these issues and helping agencies engage in appropriate decision-making. Greater attention to mis-implementation should lead to greater use of effective interventions and more efficient expenditure of resources, ultimately to improve health outcomes.


2021 ◽  
Vol 6 (3) ◽  
pp. e005207
Author(s):  
Keyrellous Adib ◽  
Penelope A Hancock ◽  
Aysel Rahimli ◽  
Bridget Mugisa ◽  
Fayez Abdulrazeq ◽  
...  

Early on in the COVID-19 pandemic, the WHO Eastern Mediterranean Regional Office recognised the importance of epidemiological modelling to forecast the progression of the COVID-19 pandemic to support decisions guiding the implementation of response measures. We established a modelling support team to facilitate the application of epidemiological modelling analyses in the Eastern Mediterranean Region (EMR) countries. Here, we present an innovative, stepwise approach to participatory modelling of the COVID-19 pandemic that engaged decision-makers and public health professionals from countries throughout all stages of the modelling process. Our approach consisted of first identifying the relevant policy questions, collecting country-specific data and interpreting model findings from a decision-maker’s perspective, as well as communicating model uncertainty. We used a simple modelling methodology that was adaptable to the shortage of epidemiological data, and the limited modelling capacity, in our region. We discuss the benefits of using models to produce rapid decision-making guidance for COVID-19 control in the WHO EMR, as well as challenges that we have experienced regarding conveying uncertainty associated with model results, synthesising and comparing results across multiple modelling approaches, and modelling fragile and conflict-affected states.


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
E Clark ◽  
S Neil-Sztramko ◽  
M Dobbins

Abstract Issue It is well accepted that public health decision makers should use the best available research evidence in their decision-making process. However, research evidence alone is insufficient to inform public health decision making. Description of the problem As new challenges to public health emerge, there can be a paucity of high quality research evidence to inform decisions on new topics. Public health decision makers must combine various sources of evidence with their public health expertise to make evidence-informed decisions. The National Collaborating Centre for Methods and Tools (NCCMT) has developed a model which combines research evidence with other critical sources of evidence that can help guide decision makers in evidence-informed decision making. Results The NCCMT's model for evidence-informed public health combines findings from research evidence with local data and context, community and political preferences and actions and evidence on available resources. The model has been widely used across Canada and worldwide, and has been integrated into many public health organizations' decision-making processes. The model is also used for teaching an evidence-informed public health approach in Masters of Public Health programs around the globe. The model provides a structured approach to integrating evidence from several critical sources into public health decision making. Use of the model helps ensure that important research, contextual and preference information is sought and incorporated. Lessons Next steps for the model include development of a tool to facilitate synthesis of evidence across all four domains. Although Indigenous knowledges are relevant for public health decision making and should be considered as part of a complete assessment the current model does not capture Indigenous knowledges. Key messages Decision making in public health requires integrating the best available evidence, including research findings, local data and context, community and political preferences and available resources. The NCCMT’s model for evidence-informed public health provides a structured approach to integrating evidence from several critical sources into public health decision making.


Author(s):  
Shehzad Afzal ◽  
Sohaib Ghani ◽  
Hank C. Jenkins-Smith ◽  
David S. Ebert ◽  
Markus Hadwiger ◽  
...  

2019 ◽  
Vol 35 (S1) ◽  
pp. 48-48
Author(s):  
Leonor Varela-Lema ◽  
Janet Puñal-Riobóo ◽  
Paula Cantero-Muñoz ◽  
Maria José Faraldo-Vallés

IntroductionDecision making regarding national population-based prenatal and newborn screening policies is recognized to be highly challenging. This paper aims to describe the formalized collaboration that has been established between the Spanish National Public Health Screening Advisory Committee (PHSAC) and the Spanish Network of Health Technology Assessment (HTA) agencies to support the development of evidence- and consensus-based recommendations to support this process.MethodsIn-depth description and analysis of the strategic and methodological processes that have been implemented within the Spanish National Health System prenatal and newborn screening frameworks, with special emphasis on the role, actions, and responsibilities of HTA agencies.ResultsThe role of HTA agencies is threefold: (i) support the PHSAC by providing evidence on safety, effectiveness and cost/effectiveness of the screening tests/strategies, as well as contextualized information regarding costs, organizational, social, legal and ethical issues; (ii) collaborate with the PHSAC in the development of formal evidence- and consensus-based recommendations for defining population screening programs, when required; (iii) analyze real-world data that is generated by piloted programs. This paper will provide real-life examples of how these processes were implemented in practice, with a special focus on the development of the non-invasive prenatal testing (NIPT) policy. Recommendations for NIPT were developed by a multidisciplinary group based on the European network for Health Technology Assessment (EUnetHTA) rapid assessment report and the predictive models that were built using national statistics and other contextualized data.ConclusionsThe current work represents an innovative approach for prenatal and newborn screening policymaking, which are commonly difficult to evaluate due to the low quality of evidence and the confounding public health issues. The paper raises awareness regarding the importance of joint collaborations in areas where evidence is commonly insufficient for decision making.


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