The limits of evidence-based anti-bribery law

2021 ◽  
Author(s):  
Kevin E. Davis
Keyword(s):  
Decision Making ◽  
Best Practice ◽  
Decision Makers ◽  
Systematic Research ◽  
Evidence Based ◽  
Causal Relationships ◽  
Causal Inferences ◽  
Business Regulation

Evidence-based regulation is a term of art that refers to the process of making decisions about regulation based on evidence generated through systematic research. There is increasing pressure to treat evidence-based regulation as a global best practice, including in the area of anti-bribery law. Too little attention has been paid to the fact that under certain conditions evidence-based regulation is likely to be a less appealing method of decision making than the alternative – namely, relying on judgment. Those conditions are: it is difficult to collect data on either interventions or outcomes; accurate causal inferences are difficult to draw; there is little warrant for believing that the same causal relationships will apply in a new context; or the decision makers in question lack the capacity to undertake one of these tasks. These conditions are likely to be present in complex, transnational, decentralized, and dynamic forms of business regulation such as the global anti-bribery regime.

EBM: Rationalist Fever Dreams

2018 ◽  
Vol 12 (3) ◽  
pp. 227-230 ◽  
Author(s):  
Devorah Klein ◽  
David Woods ◽  
Gary Klein ◽  
Shawna Perry
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Evidence Based Medicine ◽  
Best Practice ◽  
Decision Makers ◽  
Evidence Based ◽  
Naturalistic Decision Making ◽  
The Face ◽  
Based Medicine

In 2016, we examined the connection between naturalistic decision making and the trend toward best practice compliance; we used evidence-based medicine (EBM) in health care as an exemplar. Paul Falzer’s lead paper in this issue describes the historical underpinnings of how and why EBM came into vogue in health care. Falzer also highlights the epistemological rationale for EBM. Falzer’s article, like our own, questions the rationale of EBM and reflects on ways that naturalistic decision making can support expertise in the face of attempts to standardize practice and emphasize compliance. Our objectives in this commentary are first to explain the inherent limits of procedural approaches and second to examine ways to help decision makers become more adaptive.

CAN BAYESIAN METHODS MAKE DATA AND ANALYSES MORE RELEVANT TO DECISION MAKERS?

2001 ◽  
Vol 17 (1) ◽  
pp. 114-122 ◽  
Author(s):  
Steven H. Sheingold
Keyword(s):  
Decision Making ◽  
Bayesian Methods ◽  
Paradigm Shift ◽  
Relevant Information ◽  
Decision Makers ◽  
Evidence Based ◽  
Critical Importance ◽  
Bayesian Approaches ◽  
Bayesian Analyses ◽  
And Performance

Decision making in health care has become increasingly reliant on information technology, evidence-based processes, and performance measurement. It is therefore a time at which it is of critical importance to make data and analyses more relevant to decision makers. Those who support Bayesian approaches contend that their analyses provide more relevant information for decision making than do classical or “frequentist” methods, and that a paradigm shift to the former is long overdue. While formal Bayesian analyses may eventually play an important role in decision making, there are several obstacles to overcome if these methods are to gain acceptance in an environment dominated by frequentist approaches. Supporters of Bayesian statistics must find more accommodating approaches to making their case, especially in finding ways to make these methods more transparent and accessible. Moreover, they must better understand the decision-making environment they hope to influence. This paper discusses these issues and provides some suggestions for overcoming some of these barriers to greater acceptance.

scholarly journals 18.H. Workshop: Bringing evidence during public health emergencies: addressing the challenge through HTA

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
◽  
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Emergency Preparedness ◽  
Public Health Emergency ◽  
Decision Makers ◽  
Evidence Based ◽  
Public Health Emergencies ◽  
Response Planning ◽  
Emergency Preparedness And Response ◽  
Public Health Emergency Preparedness

Abstract Evidence-based decision-making is central to public health. Implementing evidence-informed actions is most challenging during a public health emergency as in an epidemic, when time is limited, scientific uncertainties and political pressures tend to be high, and irrefutable evidence may be lacking. The process of including evidence in public health decision-making and for evidence-informed policy, in preparation, and during public health emergencies, is not systematic and is complicated by many barriers as the absences of shared tools and approaches for evidence-based preparedness and response planning. Many of today's public health crises are also cross-border, and countries need to collaborate in a systematic and standardized way in order to enhance interoperability and to implement coordinated evidence-based response plans. To strengthen the impact of scientific evidence on decision-making for public health emergency preparedness and response, it is necessary to better define mechanisms through which interdisciplinary evidence feeds into decision-making processes during public health emergencies and the context in which these mechanisms operate. As a multidisciplinary, standardized and evidence-based decision-making tool, Health Technology Assessment (HTA) represents and approach that can inform public health emergency preparedness and response planning processes; it can also provide meaningful insights on existing preparedness structures, working as bridge between scientists and decision-makers, easing knowledge transition and translation to ensure that evidence is effectively integrated into decision-making contexts. HTA can address the link between scientific evidence and decision-making in public health emergencies, and overcome the key challenges faced by public health experts when advising decision makers, including strengthening and accelerating knowledge transfer through rapid HTA, improving networking between actors and disciplines. It may allow a 360° perspective, providing a comprehensive view to decision-making in preparation and during public health emergencies. The objective of the workshop is to explore and present how HTA can be used as a shared and systematic evidence-based tool for Public Health Emergency Preparedness and Response, in order to enable stakeholders and decision makers taking actions based on the best available evidence through a process which is systematic and transparent. Key messages There are many barriers and no shared mechanisms to bring evidence in decision-making during public health emergencies. HTA can represent the tool to bring evidence-informed actions in public health emergency preparedness and response.

scholarly journals Engaging Multidisciplinary Stakeholders to Drive Shared Decision-Making in Oncology

2018 ◽  
Vol 34 (1) ◽  
pp. 29-31 ◽  
Author(s):  
Gabrielle Rocque ◽  
Ellen Miller-Sonnet ◽  
Alan Balch ◽  
Carrie Stricker ◽  
Josh Seidman ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Best Practices ◽  
Shared Decision Making ◽  
Best Practice ◽  
Care Delivery ◽  
Evidence Based ◽  
Shared Decision ◽  
Oncology Practice ◽  
Development And Validation

Although recognized as best practice, regular integration of shared decision-making (SDM) approaches between patients and oncologists remains an elusive goal. It is clear that usable, feasible, and practical tools are needed to drive increased SDM in oncology. To address this goal, we convened a multidisciplinary collaborative inclusive of experts across the health-care delivery ecosystem to identify key principles in designing and testing processes to promote SDM in routine oncology practice. In this commentary, we describe 3 best practices for addressing challenges associated with implementing SDM that emerged from a multidisciplinary collaborative: (1) engagement of diverse stakeholders who have interest in SDM, (2) development and validation of an evidence-based SDM tool grounded within an established conceptual framework, and (3) development of the necessary roadmap and consideration of the infrastructure needed for engendering patient engagement in decision-making. We believe these 3 principles are critical to the success of creating SDM tools to be utilized both within and outside of clinical practice. We are optimistic that shared use across settings will support adoption of this tool and overcome barriers to implementing SDM within busy clinical workflows. Ultimately, we hope that this work will offer new perspectives on what is important to patients and provide an important impetus for leveraging patient preferences and values in decision-making.

Evidence-Based Decision-Making (Part 1): Origins and Evolution in the Health Sciences

2009 ◽  
Vol 24 (4) ◽  
pp. 298-305 ◽  
Author(s):  
David A. Bradt
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Evidence Based Medicine ◽  
Strategic Decision ◽  
Systematic Research ◽  
Evidence Based ◽  
Clinical Expertise ◽  
Strength Of Evidence ◽  
Based Medicine ◽  
Evidence Based Decision Making

AbstractEvidence is defined as data on which a judgment or conclusion may be based. In the early 1990s, medical clinicians pioneered evidence-based decision-making. The discipline emerged as the use of current best evidence in making decisions about the care of individual patients. The practice of evidence-based medicine required the integration of individual clinical expertise with the best available, external clinical evidence from systematic research and the patient's unique values and circumstances. In this context, evidence acquired a hierarchy of strength based upon the method of data acquisition.Subsequently, evidence-based decision-making expanded throughout the allied health field. In public health, and particularly for populations in crisis, three major data-gathering tools now dominate: (1) rapid health assessments; (2) population based surveys; and (3) disease surveillance. Unfortunately, the strength of evidence obtained by these tools is not easily measured by the grading scales of evidence-based medicine. This is complicated by the many purposes for which evidence can be applied in public health—strategic decision-making, program implementation, monitoring, and evaluation. Different applications have different requirements for strength of evidence as well as different time frames for decision-making. Given the challenges of integrating data from multiple sources that are collected by different methods, public health experts have defined best available evidence as the use of all available sources used to provide relevant inputs for decision-making.

Introduction

2019 ◽  
pp. 1-18
Author(s):  
William B. Rouse
Keyword(s):  
Decision Making ◽  
Competitive Advantage ◽  
Computational Models ◽  
Decision Makers ◽  
Evidence Based ◽  
Leading Indicators ◽  
Tipping Points ◽  
Decision Making Models

Chapter 1 provides the introduction to this book. Predictions can seldom specify what will happen, so, inevitably, one addresses what might happen. There are often many possible futures, with leading indicators and potential tipping points for each scenario. Computational models can be used to explore designs of systems and policies to determine whether these designs will likely be effective and to aid in decision-making. Models are means to ends rather then ends in themselves. Decision-makers seldom crave models. They want their questions answered in an evidence-based manner. Decision-makers want insights that provide them with a competitive advantage. They want to understand possible futures to formulate robust and resilient strategies for addressing these futures.

scholarly journals What Is the Potential for Applying Cost-Utility Analysis to Facilitate Evidence-Based Decision Making in Schools?

2019 ◽  
Vol 48 (5) ◽  
pp. 287-295 ◽  
Author(s):  
Fiona Hollands ◽  
Yilin Pan ◽  
Maya Escueta
Keyword(s):  
Decision Making ◽  
Program Effectiveness ◽  
Multicriteria Decision Making ◽  
Cost Utility ◽  
Cost Utility Analysis ◽  
Decision Makers ◽  
Evidence Based ◽  
Utility Analysis ◽  
Local Conditions ◽  
Education Decision

Education decision makers routinely make choices among programs and strategies to implement. Policy demands increasingly require that such decisions are based on evidence regarding program effectiveness at improving student outcomes. However, research evidence is but one of the considerations that practitioners must juggle, along with local conditions, capacity, resource availability, and stakeholder values. We investigated the feasibility of applying a multicriteria decision-making framework based on cost-utility analysis to facilitate evidence-based decisions by educators. Working with a total of 183 aspiring school leaders in class settings, we determined to what extent they could implement the initial steps of the framework. We subsequently invited three educators to apply the full framework to substantive decisions in their schools and report the results.

scholarly journals Towards an Integrated Biodiversity Technology Program Supporting Transparent Decision Making in Australia

2019 ◽  
Vol 3 ◽  
Author(s):  
Chantal Huijbers ◽  
Sarah Richmond ◽  
Lee Belbin ◽  
Hamish Holewa
Keyword(s):  
Decision Making ◽  
Best Practice ◽  
Ecological Model ◽  
Expert Panel ◽  
Development Program ◽  
Decision Makers ◽  
Observation Data ◽  
Technology Program ◽  
Online Portal ◽  
Practice Methods

Effective management of our natural world under current and future conditions requires efficient, collaborative and complementary planning and decision-making processes with clear lines of accountability. While there has been significant progress in establishing national databases for the management of species observation data, these only represent samples of a species' total distribution. The need and challenge therefore is to model these point-based observation data to obtain estimates or projections of the total range and distribution of the species. Such Species Distribution Models (SDMs), also known as Environmental Niche Models (ENMs), and the geographic data (or “maps”) they generate, provide vital information needed by governments at all levels to meet various policy and statutory responsibilities and obligations. SDMs quantify the response of species occurrence to environmental conditions described by variables such as climate, substrate, productivity and vegetation. The outcomes of an SDM can be used to identify locations and regions with potentially suitable environmental conditions for a species, as well as assess how species may respond to projected future climate changes or habitat loss. While SDMs are widely used in many decision- and policy-making programs, investment in species distribution information has been fragmented and limited. In Australia, three different government departments joined forces with the Atlas of Living Australia and the Biodiversity and Climate Change Virtual Laboratory to develop a standard framework for modelling threatened species distributions for use in policy and environmental decision-making. The pilot program that will be conducted throughout 2019 includes three complementary pillars: An expert panel with both researchers and government practitioners who will review current SDM practices used in government and develop a set of best-practice methods. A technology program that includes the development of a new modelling platform that implements the best-practice methods for transparent and reproducible SDMs for decision making as established by the expert panel. Additionally, there will be an online portal for publishing ecological model outputs in a searchable catalogue to enhance cross-jurisdiction collaborations. Establishment of a training and skill development program to upskill decision makers using the new tools and methodology in practice. An expert panel with both researchers and government practitioners who will review current SDM practices used in government and develop a set of best-practice methods. A technology program that includes the development of a new modelling platform that implements the best-practice methods for transparent and reproducible SDMs for decision making as established by the expert panel. Additionally, there will be an online portal for publishing ecological model outputs in a searchable catalogue to enhance cross-jurisdiction collaborations. Establishment of a training and skill development program to upskill decision makers using the new tools and methodology in practice. This presentation will showcase the outcomes of this program and highlight how digital infrastructure can enhance decision making. In this case specifically, the collaboration across government departments ensures a) a consistent approach across jurisdictions, b) an increase in model quality, thereby leading to a decrease in unnecessary survey or consultation efforts, c) an increase in suitability, robustness and reproducibility of SDMs, and d) increased advocacy and coordination in national programs and resources.

scholarly journals A Framework for Evidence-Based Decision Making in Large-Scale Food Fortification Programs

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1802-1802
Author(s):  
Valerie Friesen ◽  
Mduduzi Mbuya ◽  
Lynnette Neufeld ◽  
Frank T Weiringa
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Program Design ◽  
Decision Makers ◽  
Evidence Based ◽  
Food Fortification ◽  
Impact Pathway ◽  
Gates Foundation ◽  
The Impact ◽  
Evidence Based Decision Making

Abstract Objectives The use of evidence on program performance and potential for impact for decision making in food fortification programs is limited and often done in isolation from other micronutrient interventions. We present a framework for fortification stakeholders responsible for making program recommendations and decisions to facilitate and document evidence-based decision making. Methods First, we reviewed the literature to define the key decision makers and decisions necessary for effective fortification program design and delivery, informed by a clear impact pathway. Then we classified decisions by domain, identified data sources and criteria for their assessment, and adapted the GRADE Evidence to Decision framework to summarize the results. Finally, we considered how the framework would apply to different country programs to test its utility. Results Policymakers, particularly government ministries, and the food producers themselves are the most important decision makers in a fortification program, while technical support agencies, donor agencies, and the research community play important roles in translating data and evidence into contextualized recommendations that meet the needs of different decision makers. The main fortification decision types were classified into five domains across the impact pathway: 1) program design (need, food vehicle(s)); 2) program delivery (compliance, quality, coverage); 3) program impact (nutrient intake and status); 4) overlapping micronutrient interventions and/or under-served populations; and 5) decisions to continue or stop programs. Important criteria for the assessment of each decision type included priority, benefits/risks, equity, acceptability, and feasibility among others. Country examples illustrated the importance of coordinating decision-making in the context of overlapping micronutrient interventions to ensure continued safety and impact over time. Conclusions This framework is a practical tool to enable evidence-based decision making by fortification stakeholders. Using evidence in a systematic and transparent way can enable more effective program design, delivery, and ultimately health impacts. Funding Sources Bill & Melinda Gates Foundation.

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