Dataset Information

A WHO tool for risk-based decision making on blood safety interventions.

ABSTRACT:

Background

Risk-based decision making is increasingly recognized as key to support national blood policy makers and blood operators concerning the implementation of safety interventions, especially to address emerging infectious threats and new technology opportunities. There is an urgent need for practical decision support tools, especially for low- and middle-income countries that may not have the financial or technical capability to develop risk models. WHO supported the development of such a tool for blood safety. The tool enables users to perform both a quantitative Multi-Criteria Decision Assessment and a novel step-by-step qualitative assessment.

Study design and methods

This paper summarizes the content, functionalities, and added value of the new WHO tool. A fictitious case study of a safety intervention to reduce the risk of HIV transmission by transfusion was used to demonstrate the use and usefulness of the tool.

Results

Application of the tool highlighted strengths and weaknesses of both the quantitative and qualitative approaches. The quantitative approach facilitates assessment of the robustness of the decision but lacks nuances and interpretability especially when multiple constraints are taken into consideration. Conversely, while unable to provide an assessment of robustness, the step-by-step qualitative approach helps structuring the thought process and argumentation for a preferred intervention in a systematic manner.

Conclusion

The relative strengths and weaknesses of the quantitative and step-by-step qualitative approach to risk-based decision making are complementary and mutually enhancing. A combination of the two approaches is therefore advisable to support the selection of appropriate blood safety interventions for a particular setting.

SUBMITTER: Janssen MP

PROVIDER: S-EPMC7898802 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A WHO tool for risk-based decision making on blood safety interventions.

Janssen Mart P MP Nuebling C Micha CM Lery François-Xavier FX Maryuningsih Yuyun S YS Epstein Jay S JS

Transfusion 20201225 2

<h4>Background</h4>Risk-based decision making is increasingly recognized as key to support national blood policy makers and blood operators concerning the implementation of safety interventions, especially to address emerging infectious threats and new technology opportunities. There is an urgent need for practical decision support tools, especially for low- and middle-income countries that may not have the financial or technical capability to develop risk models. WHO supported the development o ...[more]

PMID: 33368381

Similar Datasets

Project description:BACKGROUND:While systematic review (SR) methods are gaining traction as a method for providing a reliable summary of existing evidence for health risks posed by exposure to chemical substances, it is becoming clear that their value is restricted to a specific range of risk management scenarios - in particular, those which can be addressed with tightly focused questions and can accommodate the time and resource requirements of a systematic evidence synthesis. METHODS:The concept of a systematic evidence map (SEM) is defined and contrasted to the function and limitations of systematic review (SR) in the context of risk management decision-making. The potential for SEMs to facilitate evidence-based decision-making are explored using a hypothetical example in risk management priority-setting. The potential role of SEMs in reference to broader risk management workflows is characterised. RESULTS:SEMs are databases of systematically gathered research which characterise broad features of the evidence base. Although not intended to substitute for the evidence synthesis element of systematic reviews, SEMs provide a comprehensive, queryable summary of a large body of policy relevant research. They provide an evidence-based approach to characterising the extent of available evidence and support forward looking predictions or trendspotting in the chemical risk sciences. In particular, SEMs facilitate the identification of related bodies of decision critical chemical risk information which could be further analysed using SR methods, and highlight gaps in the evidence which could be addressed with additional primary studies to reduce uncertainties in decision-making. CONCLUSIONS:SEMs have strong and growing potential as a high value tool in resource efficient use of existing research in chemical risk management. They can be used as a critical precursor to efficient deployment of high quality SR methods for characterising chemical health risks. Furthermore, SEMs have potential, at a large scale, to support the sort of evidence summarisation and surveillance methods which would greatly increase the resource efficiency, transparency and effectiveness of regulatory initiatives such as EU REACH and US TSCA.

Project description:While increasing attention is placed on using evidence-based decision making (EBDM) to improve public health, there is little research assessing the current EBDM capacity of the public health workforce. Public health agencies serve a wide range of populations with varying levels of resources. Our survey tool allows an individual agency to collect data that reflects its unique workforce.Health department leaders and academic researchers collaboratively developed and conducted cross-sectional surveys in Kansas and Mississippi (USA) to assess EBDM capacity. Surveys were delivered to state- and local-level practitioners and community partners working in chronic disease control and prevention. The core component of the surveys was adopted from a previously tested instrument and measured gaps (importance versus availability) in competencies for EBDM in chronic disease. Other survey questions addressed expectations and incentives for using EBDM, self-efficacy in three EBDM skills, and estimates of EBDM within the agency.In both states, participants identified communication with policymakers, use of economic evaluation, and translation of research to practice as top competency gaps. Self-efficacy in developing evidence-based chronic disease control programs was lower than in finding or using data. Public health practitioners estimated that approximately two-thirds of programs in their agency were evidence-based. Mississippi participants indicated that health department leaders' expectations for the use of EBDM was approximately twice that of co-workers' expectations and that the use of EBDM could be increased with training and leadership prioritization.The assessment of EBDM capacity in Kansas and Mississippi built upon previous nationwide findings to identify top gaps in core competencies for EBDM in chronic disease and to estimate a percentage of programs in U.S. health departments that are evidence-based. The survey can serve as a valuable tool for other health departments and non-governmental organizations to assess EBDM capacity within their own workforce and to assist in the identification of approaches that will enhance the uptake of EBDM processes in public health programming and policymaking. Localized survey findings can provide direction for focusing workforce training programs and can indicate the types of incentives and policies that could affect the culture of EBDM in the workplace.

Project description:We argue that providing cumulative risk as an estimate of the uncertainty in dynamically changing risky environments can help decision-makers meet mission-critical goals. Specifically, we constructed a simplified aviation-like weather decision-making task incorporating Next-Generation Radar (NEXRAD) images of convective weather. NEXRAD radar images provide information about geographically referenced precipitation. NEXRAD radar images are used by both pilots and laypeople to support decision-making about the level of risk posed by future weather-hazard movements. Using NEXRAD, people and professionals have to infer the uncertainty in the meteorological information to understand current hazards and extrapolate future conditions. Recent advancements in meteorology modeling afford the possibility of providing uncertainty information concerning hazardous weather for the current flight. Although there are systematic biases that plague people's use of uncertainty information, there is evidence that presenting forecast uncertainty can improve weather-related decision-making. The current study augments NEXRAD by providing flight-path risk, referred to as the Risk Situational Awareness Tool (RSAT). RSAT provides the probability that a route will come within 20 NMI radius (FAA recommended safety distance) of hazardous weather within the next 45 min of flight. The study evaluates four NEXRAD displays integrated with RSAT, providing varying levels of support. The "no" support condition has no RSAT (the NEXRAD only condition). The "baseline" support condition employs an RSAT whose accuracy is consistent with current capability in meteorological modeling. The "moderate" support condition applies an RSAT whose accuracy is likely at the top of what is achievable in meteorology in the near future. The "high" support condition provides a level of support that is likely unachievable in an aviation weather decision-making context without considerable technological innovation. The results indicate that the operators relied on the RSAT and improved their performance as a consequence. We discuss the implications of the findings for the safe introduction of probabilistic tools in future general aviation cockpits and other dynamic decision-making contexts. Moreover, we discuss how the results contribute to research in the fields of dynamic risk and uncertainty, risk situation awareness, cumulative risk, and risk communication.

Project description:The current study, using a multi-factorial survey experiment with a sample of the general public (N = 800), investigates if and how types of risk information on crime and public safety, such as maps, graphs, or tables, commonly used and communicated by law enforcement elicit dual-process (affective and cognitive) risk information processing in risk-based decision-making, and if such processing or decision-making differs depending on the risk level, context, or the type or format of risk information communicated. Participants responded to a vignette in which they were asked to choose a ride-share pick-up point within a certain geographic area with varying risk levels of being involved in a pedestrian-automobile crash. Results showed that risk information related to crime and public safety elicits dual-process risk information processing, and that both affective and cognitive processing significantly predicted risk-based decision-making, regardless of the risk level or type of risk information examined. Interestingly, risk information was used to create an almost “black and white” distinction for participants, in which their lowest-risk choice was treated as their comparison point, relative to all other higher levels of risk, in risk processing and decision-making. Further, the risk level or type of risk information examined did affect the nature and level of affective and cognitive processing elicited, suggesting that different types or characteristics of risk information can change modes of processing and their effects on risk-based decisions. Our findings provide first-of-its-kind data that show members of the general public, as consumers of risk information in relation to crime and public safety, process and make decisions surrounding such information using the dual-process approach. Implications for communicating risk information in relation to crime and public safety to both the general public and police, as well as how to extend the current inquiry to future areas of research on police, are discussed.

Dataset Information

A WHO tool for risk-based decision making on blood safety interventions.

Background

Study design and methods

Results

Conclusion

Publications

A WHO tool for risk-based decision making on blood safety interventions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets