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Evidence Informed Policy Network (EVIPNet) is a network, sponsored by the World Health Organization (WHO), which attempts to improve public health, especially in developing countries, by coordinating the efforts of policymakers and health researchers.
== History ==
EVIPNet grew out of discussions at the Ministerial Summit on Health Research held in Mexico City, November 16–20, 2004. Following the Summit, the World Health Assembly which governs the World Health Organization passed Resolution 58.2, 4-5 endorsing the "Mexico Statement On Health Research: Knowledge for better health" developed during the Summit. In the statement, Ministers of Health and delegates called "for national governments to establish sustainable programs to support evidence-based public health and health care delivery systems, and evidence-based health related policies." Resolution 58.34 made a call "to establish or strengthen mechanisms to transfer knowledge in support of evidence-based public health and health-care delivery systems, and evidence-based health-related policies". Developments relevant to EVIPNet are regularly reported to the Advisory Committee on Health Research of the World Health Organization and of its Regional Offices.
In March 2009 the EVIPNet Secretariat presented to WHO's Advisory Committee on Health Research a capacity building strategy that assessed through a validated tool the knowledge needs with respect to a defined set of skills for EVIPNet teams, allowing a strategic and organized approach to capacity building. Similarly, WHO Regional Advisory Committees on Health Research monitor progress and provide key guidance to EVIPNet efforts.
EVIPNet gained great momentum in Africa where policy briefs soon became available. The enthusiasm had spread also to the Americas and the Eastern Mediterranean, and after a coordination meeting organized by WHO in Addis Ababa in October 2015, it gained traction in the European region as well. By then, the Global Steering Group, working with WHO Collaborating Centers (e.g. WHO Collaborating Centre for Evidence-Informed Policy, at McMaster University) and specialized centers such as BIREME, the Latin American and Caribbean Center on Health Sciences Information, had set up one-stop shops that enabled access to specialized collections of indexed policy briefs, systematic reviews, policy documents and other relevant resources, as one of the shared resources for the global EVIPNet networks, such as the free access portals (with registration) of Health Systems Evidence and Health Evidence.
In October 2016 The World Health Organization published an executive summary and document entitled "Evipnet 10 years 10 stories" with a selection of cases describing impacts of EVIPNet at country level.
In the meanwhile, the platform expanded especially in the European region.
In November-December 2016, PAHO's 46th Advisory Committee on Health Research convened and its report, issued in 2017, provided updates on EVIPNet and knowledge translation efforts in the Americas. The meeting was informed by a preliminary version of a Report on Strengthening Research Capacities in the Caribbean that described EVIPNet related technical cooperation in that region.
In July 2018 The BMJ published a special series on the policy on research for health of the Pan American Health Organization (that applies to the Secretariat and Member States) featuring EVIPNet in the article on "Advancing public health and health systems through evidence-informed policy in the Americas".
== Operation ==
EVIPNet operated by forming country or regional-level teams composed of policy makers, researchers and representatives from other sectors (e.g. science & technology, education, civil society organizations, patient advocates, topic experts, local networks, etc.). These teams identify and address country priority topics where a perceived need to strengthen the systematic use of research evidence to inform decisions about policies for health has been identified. EVIPNet therefore includes components relevant to research and development and claims to help strengthen national health research systems.
By providing a common purpose to team members EVIPNet facilitates that different sectors jointly address specific priorities and develop and use specific skills to assess research evidence and integrate it into policies. Frequent outputs of EVIPNet teams are policy briefs that integrate evidence with context and values on succinct and helpful documents that inform decisions by high level decision makers. Several EVIPNet teams have already delivered useful relevant outputs such as Policy Briefs and deliberative dialogues that have informed policy at national and local levels.
To join EVIPNet country health authorities establish a formal commitment with the Secretariat and develop a work proposal. The Secretariat of EVIPNet is composed by staff from the research policy teams of the World Health Organization (WHO) in Geneva and its Regional Offices. The EVIPNet Secretariat supports country teams so that they produce robust proposals. EVIPNet has Steering Groups (in the regional and global network) and resource groups in each region. These groups work with experts and networks to provide feedback and expertise to the country teams.
The Secretariat works with country teams to identify and address skill needs and deliver targeted capacity building activities in collaboration with networks and partners (e.g. SUPPORT Collaboration, McMaster Health Forum, Cochrane Collaboration, etc.)
== Reception and impact ==
As EVIPNet expands and develops it has been highlighted as a worthy approach featured in prominent strategy documents addressing development and capacity building for research for health. It remains relevant as reflected in the call to action issued at the Global Ministerial Forum on Research for Health in Bamako in November 2008 by ministers and ministerial representatives from 53 countries. EVIPNet was also featured in at least 12 different presentations at the First Global Symposium on Health Systems Research (Montreux, Switzerland, 2010), and is frequently featured at Colloquiums of the Cochrane and Campbell Collaborations, and Global Forums on Health Research (e.g. Bamako 2008, Havana 2009).
EVIPNet has also allowed for the development of customized resources that have helped advance their work and knowledge about health systems research. For example, the SUPPORT Tools for Evidence Informed Policy Making (available in various languages), the Evidence Portal, or the McMaster Database on Health Systems Evidence with >1800 systematic reviews on health systems evidence.
== PAHO/WHO technical programs ==
EVIPNet has also become a tool for PAHO/WHO technical programs offering an integrated approach to technical cooperation; in PAHO/WHO research focal points in country offices are part of EVIPNet teams, and technical programs have adopted EVIPNet methods to provide an integrated technical cooperation.
== References ==
== External links ==
EVIPNet Home

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The discipline of evidence-based toxicology (EBT) strives to transparently, consistently, and objectively assess available scientific evidence in order to answer questions in toxicology, the study of the adverse effects of chemical, physical, or biological agents on living organisms and the environment, including the prevention and amelioration of such effects. EBT has the potential to address concerns in the toxicological community about the limitations of current approaches to assessing the state of the science. These include concerns related to transparency in decision making, synthesis of different types of evidence, and the assessment of bias and credibility. Evidence-based toxicology has its roots in the larger movement towards evidence-based practices.
By analogy to evidence-based medicine (EBM), the umbrella term evidence-based toxicology (EBT) has been coined to group all approaches intended to better implement the above-mentioned evidence-based principles in toxicology in general and in toxicological decision-making in particular. Besides systematic reviews, the core evidence-based tool, such approaches include inter alia the establishment and universal use of a common ontology, justified design and rigorous conduct of studies, consistently structured and detailed reporting of experimental evidence, probabilistic uncertainty and risk assessment, and the development of synthesis methodology to integrate evidence from diverse evidence streams, e.g. from human observational studies, animal studies, in vitro studies and in silico modeling. A main initial impetus for translating evidence-based approaches to toxicology was the need to improve the performance assessment of toxicological test methods. The U.S. National Research Council (NRC) concurs that new means of assessment are needed to keep pace with recent advances in the development of toxicological test methods, capitalizing on enhanced scientific understanding through modern biochemistry and molecular biology.
A key tool in evidence-based medicine that holds promise for EBT is the systematic review. Historically, authors of reviews assessing the results of toxicological studies on a particular topic have searched, selected, and weighed the scientific evidence in a non-systematic and non-transparent way. Due to their narrative nature, these reviews tend to be subjective, potentially biased, and not readily reproducible. Two examples highlighting these deficiencies are the risk assessments of trichloroethylene and bisphenol A (BPA). Twenty-seven different risk assessments of the evidence that trichloroethylene causes cancer have come to substantially different conclusions. Assessments of BPA range from low risk of harm to the public to potential risks (for some populations), leading to different political decisions. Systematic reviews can help reducing such divergent views. In contrast with narrative reviews, they reflect a highly structured approach to reviewing and synthesizing the scientific literature while limiting bias. The steps to carrying out a systematic review include framing the question to be addressed; identifying and retrieving relevant studies; determining if any retrieved studies should be excluded from the analysis; and appraising the included studies in terms of their methodological quality and risk of bias. Ultimately the data should be synthesized across studies, if possible by a meta-analysis. A protocol of how the review will be conducted is prepared ahead of time and ideally should be registered and/or published.
Scientists have made progress in their efforts to apply the systematic review framework to evaluating the evidence for associations between environmental toxicants and human health risks. To date, researchers have shown that important elements of the framework established in evidence-based medicine can be adapted to toxicology with little change, and some studies have been attempted. Researchers using the systematic review methodology to address toxicological concerns include a group of scientists from government, industry, and academia in North America and the European Union (EU) who have joined together to promote evidence-based approaches to toxicology through the nonprofit Evidence-based Toxicology Collaboration (EBTC). The EBTC brings together the international toxicology community to develop EBT methodology and facilitate the use of EBT to inform regulatory, environmental and public health.
== Background ==
Evidence-based approaches were first conceived as a means of anchoring policy decisions, not to current practices or the beliefs of experts, but to experimental evidence. Evidence-based medicine (EBM) was launched slightly later. Its rise as a distinct discipline is generally credited to the work and advocacy of Scottish epidemiologist Archie Cochrane. The Cochrane Collaboration named in his honor was launched at Oxford University in 1993 to promote evidence-based reviews of clinical medical literature. More recently, EBM expanded to encompass evidence-based health care (EBHC).
EBM/HC involves the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients taking patients' preferences into account. Prior to EBM, medical decisions about diagnosis, prevention, treatment or harm were often made without a rigorous evaluation of the alternatives. Research in the 1970s and 1980s showed that different physicians regularly recommended different treatments and tests for patients with ailments that were essentially the same, and that large proportions of procedures being performed by physicians were considered inappropriate by the standards of medical experts.
EBM/HC supporters stress that while evidence always has been important to the practice of medicine, EBM/HC provides an enhanced approach of identifying, assessing, and summarizing evidence. EBT's supporters make a similar argument.
The idea of translating evidence-based approaches from medicine to toxicology has been percolating for two decades, with proponents in both medicine and toxicology. Three research papers published in 2005 and 2006 catalyzed what eventually became known as EBT by suggesting that EBM's established tools and concepts might serve as a prototype of evidence-based decision-making in toxicology.

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== Process and progress ==
The First International Forum Toward Evidence-Based Toxicology was held in 2007. The forum was organized by the European Commission and attended by 170 scientists from more than 25 European, American, and Asian countries. The goal was to explore the available concepts of EBT, and to launch an initiative to formally implement evidence-based assessment methods in toxicology.
The starting point for the discussions were two research papers suggesting that the tools and concepts established in evidence-based medicine could serve as a prototype of evidence-based decision-making for evaluating toxicological data. Apparent fundamental differences between medicine and toxicology were carefully considered during these discussions. Forum participants attempted to bridge the two disciplines in order to make use of the accrued wisdom and apply this approach to toxicology. (See [1] Archived 2017-07-29 at the Wayback Machine .)
The proceedings of this forum were published as a special issue in Human & Experimental Toxicology.
EBT's proponents include experts in EBM, public health, and toxicology who believe that EBT can help toxicologists to better serve the goals of health protection and safety assurance. They argue that EBT's methodologies for collecting, appraising, and pooling evidence can help ensure that all available information on a given topic is evaluated in a transparent, unbiased, and reproducible manner. They contend that EBT's concept of the systematic review could prove particularly helpful for the standardization and quality assurance of novel methodologies for evaluating toxicity, as well as for their formal validation. In this regard, EBT may prove particularly useful for assessing the performance of newer non-animal "21st century" toxicology tools. EBT can also help scientists integrate new toxicological test methods into test strategies being implemented across the globe.
In 2010, a group of EBT supporters joined together to convene a workshop titled "21st Century Validation for 21st Century Tools". The session on the potential for evidence-based approaches to assess the performance of the new generation of non-animal test methods inspired the formation of the EBTC. The EBTC was officially launched in the U.S. in 2011 at a Society of Toxicology conference and convened its first workshop in 2012. The EBTC's EU branch was officially opened during the 2012 Eurotox conference.
In 2014, the EBTC hosted a workshop on "The Emergence of Systematic Review and Related Evidence-based Approaches in Toxicology" with speakers representing US and European organizations that are implementing and promoting the use of systematic reviews for toxicological questions. The experts noted that the structured approach of systematic reviews increases objectivity and transparency but also made clear that the approach requires a substantial time investment, which is a challenge to its more widespread adoption. Consequently, the participants called for close collaboration of interested organizations, which they determined to be a pre-requisite for the broad and efficient introduction of systematic reviews in toxicology.
== Applications of EBT ==
=== Regulatory decision-making ===
Some scientists and policymakers would like EBT to help them combine information from various sources. Toxicological evidence can be assigned to evidence streams, sets of studies representing the same type or level of evidence, such as human (observational) studies, animal studies, in vitro or mechanistic studies. EBT can be applied both within one evidence stream, and it is especially well-suited to be applied across multiple evidence streams. Regulators often designate one study as "the lead study", then use later studies as additional information. Many perceive this as unsatisfying, but objective approaches to combine study results are lacking. The EBM concept of the systematic review has promise for this application, and some structured reviews serve as forerunners for this approach.
=== Evaluating effects of environmental exposures ===
The U.S. National Toxicology Program's Office of Health Assessment and Translation (OHAT) has started to use systematic review methodology for the program's evaluations. The first systematic review was completed in 2016, reviewing the effects of fluoride on learning and memory in animal studies. OHAT’s approach is tailored to its mandate, but its seems especially appropriate for substances with substantial yet conflicting literature, and hence the need for systematic reviews to sort out somewhat confusing situations.
=== Causation ===
One application of EBT focuses on causation. It addresses the challenge of tracing a health effect back to a toxicant, such as lung cancer to smoking. This approach is similar to legal arguments Some experts warn that this approach could increase the evidence burden for proving causation, and thereby increase the difficulty involved in banning toxic substances.
=== Clinical toxicology ===
Practitioners of clinical toxicology, which is concerned with the treatment of patients known to be exposed to toxic substances, are also beginning to use an EBM-style approach. Guidance documents based on this approach have already been published
=== 21st century toxicology ===
The National Research Council's (NRC) landmark 2007 publication, "Toxicity Testing in the 21st Century", has also been an impetus for EBT. EBT provides new tools for assessing test method performance. Also, as the focus of 21st-century toxicology shifts from animal biology to human biology, EBT provides a method for comparatively evaluating the results gleaned from new methods of investigating the effects of chemical exposure.
The Evidence-based Toxicology Collaboration has pioneered a number of projects aimed at applying EBT approaches and systematic reviews to test methods comparison.

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== Limitations and challenges ==
The specific differences between toxicology and medicine/health care cause challenges for implementing EBT. Evidence-based methodology of clinical research has been focused on a single type of study—randomized, controlled clinical trials, which are a direct measure of the effectiveness of the health care intervention under scrutiny. In contrast, toxicology employs a variety of different kinds of studies in three distinct evidence streams: human (observational) studies, animal studies, and non-animal studies. Because human evidence is frequently lacking most evidence is obtained by using animal and non-animal models, which—by definition—is more difficult to generalize and extrapolate to humans. This methodological heterogeneity complicates evidence integration within an evidence stream, such as when inconsistent evidence is obtained from different animal species, but even more so across evidence streams. Adding to the difficulty is the reality that much toxicological evidence, more so than in medicine and health care, is not readily accessible in the literature. Moreover, the role of expert judgment, especially in systematic reviews, needs to be clearly defined, as it is a common misperception that evidence-based approaches leave no room for it. Systematic reviews should strive to make expert judgments clear along with the scientific basis for those judgments in developing conclusions for a systematic review. Further issues to be worked out include exposures to multiple substances, the multitude of outcomes observed in some animal studies, and challenges in improving the experimental designs and reporting of studies.
== See also ==
Evidence-based medicine
Evidence-based practice
== References ==

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Examine.com is a Toronto-based company that runs an online encyclopedia covering health, nutrition and supplementation. The website collates scientific research using evidence-based practice methodology. Examine.com is led by Kamal Patel, and includes scientists, editors and peer reviewers.
== History ==
Examine.com was created in 2011 by University of Toronto alumnus Sol Orwell out of his frustration with users on Reddit asking the same questions over and over again. Kurtis Frank had posted on a public forum that he had been doing nutrition research, and wanted to improve accessibility to such information. He was contacted by Orwell, and they created the website, with Frank becoming co-founder. Orwell had already thought of the idea from his weight loss journey and frustration with info on supplements, but wanted an expert alongside. Frank left Examine sometime in 2018, when his name was removed from the site.
The company began with a focus on supplementation research, but expanded into nutrition as it continued to grow. During the initial research that led to the company's founding, Orwell noticed unsourced and incorrect marketing claims about nutrition and supplementation made it difficult to draw conclusions about health, which lead to the site's standard of evidence-based analysis.
In 2014, the company began directly reviewing nutrition research in a digest tailored to the "serious enthusiast or professional".
Men's Fitness named Orwell a 2014 Game Changer for his work on Examine.com and for providing "hype-free, science-sourced information relatable to the masses."
In 2015, Forbes interviewed Orwell about his "seven-figure business", and Fast Company included Examine.com as one of the top ten innovative companies in fitness. The company was incorporated in 2015, with Kamal Patel officially joining as co-founder.
As of September 2016, the website said that it had over 50,000 references.
By 2020, the website was being used by mainstream media such as The New York Times as a supplements reference in the context of strength-building advice and understanding the role of supplements during the COVID-19 pandemic. The same year, inspired by GiveWell, Examine.com started publicly disclosing the mistakes they had committed and how they were fixing them.
In 2020, Examine.com Director Kamal Patel was named #1 Most Influential Man in Health & Fitness by Men's Health UK.
== Company structure ==
Remaining unbiased is named as a priority in the site's mission statement. Examine.com only reviews research and supplement ingredients, rather than specific products. On the company blog, Examine.com publishes rebuttals to cases of exaggerated marketing of nutrition and supplementation products.
== See also ==
Natural Standard
Dietary supplement
Media transparency
Comparison of supplements by different brands:
ConsumerLab.com
Labdoor, Inc
== References ==
== External links ==
Official website

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The GRADE approach (Grading of Recommendations Assessment, Development and Evaluation) is a method of assessing the certainty in evidence (also known as quality of evidence or confidence in effect estimates) and the strength of recommendations in health care. It provides a structured and transparent evaluation of the importance of outcomes of alternative management strategies, acknowledgment of patients and the public values and preferences, and comprehensive criteria for downgrading and upgrading certainty in evidence. It has important implications for those summarizing evidence for systematic reviews, health technology assessments, and health guidelines as well as other decision makers.
== Background and history ==
The GRADE began in the year 2000 as a collaboration of methodologists, guideline developers, biostatisticians, clinicians, public health scientists and other interested members. GRADE developed and implemented a common, transparent and sensible approach to grading the quality of evidence (also known as certainty in evidence or confidence in effect estimates) and strength of recommendations in healthcare. GRADE follows careful methods to develop its guidance and other articles.
GRADE official articles, guidance group, project groups and centers, networks, and formalization of Evidence-to-Decision frameworks
As GRADE adoption expanded, the need for sustained methodological support and capacity building became apparent. Starting in 2010, the first GRADE Centers and Networks were established. These entities supported training, implementation, and feedback from diverse contexts, helping to ensure consistent application while allowing for contextual adaptation.
During the same period, the DECIDE Project, funded by the European Commission, played a central role in formalizing Evidence-to-Decision frameworks. DECIDE supported the development and testing of EtD frameworks for different types of decisions, the publication of EtD guidance articles, and the implementation of EtD frameworks within GRADEpro.9 This work transformed EtD from an early concept into a standardized and operational component of GRADE.
Governance, methodological stewardship, and the development of GRADE guidance
As GRADE matured and its applications expanded across clinical medicine, public health, diagnostics, and health systems by many influential organizations, the need for formal methodological stewardship and governance became increasingly apparent. What had initially functioned as an informal working group required clearer structures to ensure coherence, transparency, and consistency in how new methodological developments were proposed, debated, approved, and disseminated.
The GRADE Guidance Group
In response to this need, the GRADE Guidance Group (often referred to as G3) was established in the early 2010s as the core governance body of the GRADE Working Group. The Guidance Group provides strategic oversight and methodological stewardship for GRADE. Guided by its chair (currently: Holger Schünemann) its responsibilities include:
setting priorities for methodological development,
reviewing and approving proposals for new guidance or major updates,
ensuring consistency across guidance documents,
safeguarding the conceptual integrity of GRADE, and
coordinating across the growing number of contributors, centers, and networks.
The creation of the Guidance Group marked an important transition in GRADE’s evolution—from a predominantly informal collaboration to a self-governing methodological enterprise. Importantly, the Guidance Group does not replace the broader GRADE Working Group; rather, it provides structure and continuity, while maintaining GRADE’s collaborative and consensus-driven ethos. Current members (as of 2025) include: Elie Akl, Sue Brennan, Philipp Dahm, Marina Davoli, Monica Hultcrantz, Miranda Langendam, Joerg Meerpohl, Reem Mustafa, Ignacio Neumann, Holger Schünemann, Nicole Skoetz, Jun Xia.
GRADE Project Groups
At that time, substantive methodological advances within GRADE began to be developed through GRADE Project Groups. These groups are convened to address specific methodological questions or gaps, for example, how to apply GRADE to animal research, rare diseases, public health interventions, health systems decisions, or how to assess domains such as imprecision, publication bias, equity, or values.
Project groups are typically multidisciplinary and international, bringing together methodologists, content experts, and end users. Their work commonly involves:
reviewing existing methods and frameworks,
conducting empirical or conceptual methodological work,
testing proposals in real guideline or decision-making contexts,
and iteratively refining approaches through discussion and application.
Project groups operate under the oversight of the GRADE Guidance Group, which reviews proposals, monitors progress, and evaluates final outputs before endorsement. This structure has allowed GRADE to scale methodologically without fragmenting into competing or incompatible approaches.
Formalization of GRADE guidance and concept articles
As the volume and diversity of GRADE-related publications increased, the Working Group recognized the importance of clearly distinguishing official GRADE guidance from conceptual discussions, applications, or commentaries. In response, a formal article was published describing the processes by which GRADE Guidance and GRADE Concept articles are developed, reviewed, and approved.
That article clarified, among other points:
the distinction between GRADE Guidance articles, which provide authoritative, endorsed methodological instructions, and GRADE Concept articles, which explore ideas, extensions, or emerging areas without yet constituting formal guidance;
the role of the GRADE Guidance Group in approving guidance proposals and final manuscripts;
expectations regarding transparency, documentation of methods, and consensus-building; and
the importance of linking guidance development to real-world testing and application.
This formalization was a critical step in maintaining trust and clarity as GRADE became widely used. It helped readers, guideline developers, and organizations understand which publications represent official GRADE methods, which are exploratory or developmental, and how new guidance evolves from concept to endorsed standard.
== GRADE components ==
The GRADE approach separates recommendations following from an evaluation of the evidence as strong or weak. A recommendation to use, or not use an option (e.g. an intervention), should be based on the trade-offs between desirable consequences of following a recommendation on the one hand, and undesirable consequences on the other. If desirable consequences outweigh undesirable consequences, decision makers will recommend an option and vice versa. The uncertainty associated with the trade-off between the desirable and undesirable consequences will determine the strength of recommendations. The criteria that determine this balance of consequences are listed in Table 2. Furthermore, it provides decision-makers (e.g. clinicians, other health care providers, patients and policy makers) with a guide to using those recommendations in clinical practice, public health and policy. To achieve simplicity, the GRADE approach classifies the quality of evidence in one of four levels—high, moderate, low, and very low:

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=== Certainty of evidence ===
GRADE rates the certainty of evidence as follows:
The GRADE working group has developed a software application that facilitates the use of the approach, allows the development of summary tables and contains the GRADE handbook. The software is free for non-profit organizations and is available online.
The GRADE approach to assess the certainty in evidence is widely applicable, including to questions about diagnosis, prognosis, network meta-analysis and public health.
=== Strength of recommendation ===
Factors and criteria that determine the direction and strength of a recommendation:
Factors for which overlap is described are often not shown separately in a decision table.
== Usage ==
Over 100 organizations (including the World Health Organization, the UK National Institute for Health and Care Excellence (NICE), the Canadian Task Force for Preventive Health Care, the Colombian Ministry of Health and Social Protection, and the Saudi Arabian Ministry of Health) have endorsed and/or are using GRADE to evaluate the quality of evidence and strength of health care recommendations.
== Criticism ==
When used to summarize evidence from nutritional science, dietary, lifestyle, and environmental exposure, the use of the GRADE approach has been criticized. Critics argue that the GRADE system had focused on randomized controlled trials (RCT) to be rated as high evidence and rates all observational studies as low evidence because of their potential for confounding, but this is incorrect and observational studies can yield high certainty evidence which is made explicit in GRADE guidance Number 18. Such an approach could have dismissed the strength of observational studies when it comes to long-term effects of dietary and lifestyle factors while not reflecting the key limitations that RCTs have when it comes to long-term effects. One example of a slowly progressing disease that should, according to critics, preferably be studied with observational studies but not RCTs is atherosclerosis. Indeed, non-randomized studies may be rated as high certainty when using GRADE if they take measures to control for confounding. Furthermore, the GRADE Working Group has published other guidance that lays out how observational studies can be utilized in the context of long-term effects which does not dismiss the value of observational studies.
== References ==

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The German Agency for Quality in Medicine (AEZQ) (German: Ärztliches Zentrum für Qualität in der Medizin, ÄZQ), established in 1995 and located in Berlin, co-ordinates healthcare quality programmes with special focus on evidence-based medicine, medical guidelines, patient empowerment, patient safety programs, and quality management.
AEZQ is a non-profit organization owned by the German Medical Association and the National Association of Statutory Health Insurance Physicians.
== Activities ==
AEZQ initiated several quality programs for the German healthcare system:
It established the German Program for evidence based medical guidelines in the late 90s. Based upon guideline standards from the Scottish Intercollegiate Guideline Network and referring to experiences from the National Guideline Clearinghouse in the US, the agency founded a German Guideline Clearinghouse aiming at best practice in guideline production.
In 1998 AEZQ was co-founder of the German Network for Evidence Based Medicine.
The organization established the German Clearinghouse for Patient Information in order to promote scientifically based shared decision making in 1999.
In 2002, the agency set up the National Program for Disease Management Guidelines.
The development of reliable and consumer information is integral part of this guideline program.
AEZQ was co-founder of the Guidelines International Network in 2002 - under the leadership of Günter Ollenschläger, collaborating with other national healthcare quality agencies like the US Agency for Healthcare Research and Quality, the UK National Institute for Health and Clinical Excellence, the Australian National Health and Medical Research Council.
In the field of patient safety AEZQ was one of the first German organisations calling for effective patient safety programs. The agency was co-founder of the German Coalition for Patient Safety. AEZQ established a national web of Critical Incident Reporting Systems. The institution is partner of the international High 5 Project.
In 2010 the agency set up a Digital Library for physicians and other interested health professionals and lays - the German Medical eLibrary (www.arztbibliothek.de) - for reinforcement of reliable and unbiased knowledge management in healthcare.
AEZQ entertained the administrative offices of the Guidelines International Network, and of the German Network for Evidence Based Medicine until 2013. It hosts the editorial office of the German Journal for Evidence and Quality in Healthcare.
== References ==
== External links ==
German Agency for Quality in Medicine Official Website
National Program for Disease Management Guidelines Website
German Patient Information Clearinghouse Website
AQUMED Patient Safety Website
www.arztbibliothek.de - The German Medical e-Library

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The Global Appraisal of Individual Needs (GAIN) is a family of evidence-based instruments used to assist clinicians with diagnosis, placement, and treatment planning. The GAIN is used with both adolescents and adults in all kinds of treatment programs, including outpatient, intensive outpatient, partial hospitalization, methadone, short-term residential, long-term residential, therapeutic community, and correctional programs.
== History ==
The GAIN was developed to respond to the needs of substance abuse treatment personnel who are faced with the demands of assessing, documenting, treating, and monitoring clients. Researchers, clinicians, policymakers, and behavioral healthcare agencies worked to design assessment tools that could produce methodical data for mapping onto the Diagnostic and Statistical Manual of Mental Disorders (DSM) for diagnosis and the American Society of Addiction Medicine (ASAM) Patient Placement Criteria for placement, while following The Joint Commission (TJC) [formerly the Joint Commission on Accreditation of Healthcare Organizations (JCAHO)] for integrating assessments into treatment plans. Since its inception in 1993, application of the GAIN has expanded to thousands of users at agencies across the United States, Canada and several other countries.
== Family of assessments ==
GAIN Initial (GAIN-I) – a comprehensive standardized assessment that can be used for treatment placement and planning, outcome monitoring, economic analysis, program planning, and supporting motivational interviewing.
GAIN Monitoring 90 Days (GAIN-M90) – a subset of the GAIN-I used for quarterly follow-up to measure changes in participants throughout their treatment.
GAIN-Q3 – The GAIN-Q3 includes three separate versions that screen for the recency and frequency of behavior and service utilization in nine areas. Successive versions provide additional information, such as a six-item measure of life satisfaction or supplemental modules to collect information on reasons and readiness to change.
GAIN Short Screener (GAIN-SS) – a screener, not used for diagnosis or level of care placement, that quickly identifies clients likely to have mental health disorders, issues with crime/violence, and issues with substance use. The GAIN-SS is typically self-administered.
All these assessments can be used to generate reports to aid in diagnosis and treatment planning.
== Content ==
The GAIN-I has sections covering background, substance use, physical health, risk behaviors and disease prevention, mental and emotional health, environment and living situation, legal, and vocational. Within these sections are questions that address problems, services, client attitudes and beliefs, and the client's desire for services. Information on symptoms, which is used for diagnosis, is collected if the behavior has occurred in the last year. Information on behaviors, which is used for treatment monitoring, is collected if the same behavior occurred within the last 90 days. The items are combined into over 100 scales Scale (social sciences) and subscales that can be used for DSM-IV–based diagnoses, ASAM-based level-of-care placement, TJC-based treatment planning, and Drug Outcome Monitoring Study-based outcome monitoring. The GAIN also includes items that support most state and federal reporting requirements, which compare to community samples from the National Survey of Drug Use and Health (NSDUH [formerly the National Household Survey on Drug Abuse (NHSDA)]). As biopsychosocial assessments, The GAIN-I and GAIN-SS provide measures over four main categories of emotional and behavioral health problems—internalizing, externalizing, substance, and crime/violence. Among these categories are numerous scales and indices, which have demonstrated good reliability and internal consistency in studies.
== Response to criticism ==
The GAIN has been criticized for not having scales to assess response style. Critics say these face-valid questions are vulnerable to faked responses from participants. Although it would be impossible for interviewers to ensure that participants always provide genuine responses to questions, the benefit of semi-structured assessments, like the GAIN, is that they allow the interviewer to clarify participant responses. Additionally, helping participants understand how their responses will be used in specific areas of their treatment may encourage them to be truthful. The GAIN-I includes ratings at the end of each section that allow an interviewer to record whether a participant seemed to be doing some estimating, whether they did not understand the questions, whether they were in denial about the severity of a problem or whether they were misrepresenting information. These ratings can be used as flags to communicate problem areas to clinicians and can also assist in treatment planning.
== Notes ==
== External links ==
GAIN Coordinating Center Archived 25 April 2012 at the Wayback Machine
Chestnut Health Systems Archived 3 April 2011 at the Wayback Machine

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The Guidelines International Network (GIN) is an international scientific association of organisations and individuals interested and involved in development and application of evidence-based guidelines and health care information. The network supports evidence-based health care and improved health outcomes by reducing inappropriate variation throughout the world.
== Membership and Organisation ==
The Network's membership consists of 115 organisations working in the field of medical guidelines and other types of healthcare guidance as well as of around 130 individual experts (March 2021). The members represent about 47 countries from all continents.
The list of members is available on the GIN website
Being constituted as a Scottish Guarantee Company under Company Number SC243691, the Network is recognised as a Scottish Charity under Scottish Charity Number SC034047.
== History ==
Based upon the work of the international AGREE Collaboration for the quality of clinical practice guidelines, an organised network for organisations and experts working in the field of evidence-based guidelines was proposed in early 2002 at the first international guideline conference in Berlin, Germany. Guideline experts called for international standardized guideline methods, and information exchange in this field. The proposal was endorsed by health care agencies from all parts of the world such as AHRQ (USA), CBO (NL) German Agency for Quality in Medicine, NICE (UK), SIGN (UK), and NZGG (NZ).
Against this background the Guidelines International Network GIN was founded in November 2002 in Paris with Günter Ollenschläger as founding chairman.
== Mission and Aims ==
The goal of the network is to lead, strengthen and support collaboration and work within the guideline development, adaptation and implementation community.
GIN's main aims are:
Promoting best practice through the development of learning opportunities and capacity building, as well as the establishment of standards
Improving the efficiency and effectiveness of evidence-based guideline development, adaptation, dissemination and implementation
Building a Network and partnerships for guideline developing organisations, end users (such as health care providers, healthcare policy makers and consumers) and stakeholders.
== Activities ==
GIN has an International Guideline Library and registry, one of the world's largest guideline libraries, containing regularly updated guidelines and publications of the GIN membership, as well as other guideline developers. The registry is open for all guideline developers to register their guidelines. As of April 2021 around 3000 documents were available.
The network organises the annual GIN Conference around the globe:
2003 Edinburgh (UK), 2004 Wellington (NZ), 2005 Lyon (FR), 2007 Toronto (CA), 2008 Helsinki (FI), 2009 Lisbon (PT), 2010 Chicago (US), 2011 Seoul (KR), 2012 Berlin (DE), 2013 San Francisco (US), 2014 Melbourne (AU), 2015 Amsterdam (NL), 2016 Philadelphia (US), 2018 Manchester (UK) and 2019 Adelaide. In 2017, GIN was one of five organising partners of the first Global Evidence Summit.
GIN Projects are developed in several working groups focussing on the following topics, amongst many others:
Guideline Adaptation
Guideline Implementation
GIN Tech
Public and Patient involvement
== References ==
== External links ==
GIN Website
enGINe, the GIN Newsletter Archived 11 May 2021 at the Wayback Machine

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Health technology assessment (HTA) is a multidisciplinary process that uses systematic and explicit methods to evaluate the properties and effects of a health technology. Health technology is conceived as any intervention (test, device, medicine, vaccine, procedure, program) at any point in its lifecycle (pre-market, regulatory approval, post-market, disinvestment). The purpose of HTA is to inform "decision-making in order to promote an equitable, efficient, and high-quality health system". It has other definitions including "a method of evidence synthesis that considers evidence regarding clinical effectiveness, safety, cost-effectiveness and, when broadly applied, includes social, ethical, and legal aspects of the use of health technologies. The precise balance of these inputs depends on the purpose of each individual HTA. A major use of HTAs is in informing reimbursement and coverage decisions by insurers and national health systems, in which case HTAs should include benefit-harm assessment and economic evaluation." And "a multidisciplinary process that summarises information about the medical, social, economic and ethical issues related to the use of a health technology in a systematic, transparent, unbiased, robust manner. Its aim is to inform the formulation of safe, effective, health policies that are patient focused and seek to achieve best value. Despite its policy goals, HTA must always be firmly rooted in research and the scientific method".
== Purpose ==
Health technology assessment is intended to provide a bridge between the world of research and the world of decision-making. HTA is an active field internationally and has seen continued growth fostered by the need to support management, clinical, and policy decisions. It has also been advanced by the evolution of evaluative methods in the social and applied sciences, including clinical epidemiology and health economics. Health policy decisions are becoming increasingly important as the opportunity costs from making wrong decisions continue to grow. HTA is now also used in assessment of innovative medical technologies like telemedicine e.g. by use of the Model for assessment of telemedicine (MAST).
Health technology can be defined broadly as:
Any intervention that may be used to promote health, to prevent, diagnose or treat disease or for rehabilitation or long-term care. This includes the pharmaceuticals, devices, procedures and organizational systems used in health care.
== History ==
The discipline of HTA was first developed in the U.S. Office of Technology Assessment, which published its first report in 1976. The growth of HTA internationally can be seen in the expanding membership of the International Network of Agencies for Health Technology Assessment (INAHTA), a non-profit umbrella organization established in 1993. Organizations and individuals involved in the production of HTA publications may also affiliated with international societies such as Health Technology Assessment International (HTAi) and International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Academic courses, typically in Masters programs, are also offered in health technology assessment and management.
== By country ==
The World Health Organization provides an overview of countries and their corresponding HTA agencies.
=== United Kingdom ===
The United Kingdom's National Institute for Health and Care Research (NIHR) runs several research programmes that may be viewed as falling into the realm of Health Technology Assessment. Of particular note is the NIHR Health Technology Assessment programme, its longest running, which undertakes both conventional HTA in the form of Evidence Synthesis and modelling, and evidence generation with a large portfolio of pragmatic RCTs and cohort studies. The programme's research is regularly published in NIHR's journal Health Technology Assessment.
Also in the UK, the Multidisciplinary Assessment of Technology Centre for Healthcare carries out HTA in collaboration with the health service, the NHS and various industrial partners. MATCH is organised into four themes addressing key HTA topics including Health Economics, Tools for Industry, User Needs and Procurement and Supply chain.
=== Canada ===
Canada also has a health technology assessment body called Canada's Drug Agency, formerly called the Canadian Agency for Drugs and Technologies in Health (CADTH).
=== Italy ===
As of today, 11 Italian regions have issued specific regional laws or regulations to manage HTA activities and processes at regional level: Abruzzo, Basilicata, Emilia-Romagna, Lazio, Liguria, Lombardia, Piemonte, Puglia, Sicilia, Toscana, and Veneto. In another four regions (Calabria, Marche, Umbria, and Valle D'Aosta) and in the two autonomous provinces of Bolzano and Trento, HTA is performed at different levels, even if no legislation has yet been produced.
=== Germany ===
In Germany, Health Technology Assessment is overseen by the Federal Joint Committee (Gemeinsamer Bundesausschuss, G-BA), the highest decision-making body of the joint self-government of physicians, hospitals and health insurance funds.
The G-BA decides on the benefits package of the statutory health insurance system. As part of this role, it conducts benefit assessments of new medical interventions. The Institute for Quality and Efficiency in Health Care (IQWiG) provides scientific evaluations and reports that inform the G-BA's decisions.
== Impact of HTA implementation ==
A recent study explored the implementation of HTA in three middle-income countries (MICs) and its influence on health system objectives. The study investigated the impact of HTA globally through a systematic literature review. The study also surveyed stakeholders from the middle-income countries.
The results indicated that the benefits of HTA implementation in these countries largely outweigh the drawbacks. The major advantages identified include enhanced transparency and accountability in healthcare decisions, leading to more informed and equitable healthcare policies.
The study has shown that HTA has a positive impact on several aspects of healthcare systems:
Improved decision making: HTA aids in making better health financing decisions, including resource allocation and policy formulation.
Enhanced transparency and accountability: The most evident benefit of HTA is its role in improving the clarity and responsibility of healthcare decisions.
Economic impact: While HTA can generate cost savings in specific areas, its overall impact on the fiscal sustainability of healthcare systems in MICs remains unclear.
It was also noted that HTA's influence extends to the broader health system goals, such as health gain, equity in health, and responsiveness to patient needs. However, the impact on direct health gains and financial protection of households is less pronounced.
The study emphasizes the gradual adoption of HTA in MICs and the necessity for continuous assessment of its impact.
== See also ==
Horizon scanning
Pharmacoeconomics
== References ==
== External links ==
Health Technology Assessment International (HTAi)
International Network of Agencies for Health Technology Assessment (INAHTA)
European Network for Health Technology Assessment (EUnetHTA)

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A hierarchy of evidence, comprising levels of evidence (LOEs), that is, evidence levels (ELs), is a heuristic used to rank the relative strength of results obtained from experimental research, especially medical research. There is broad agreement on the relative strength of large-scale, epidemiological studies. More than 80 different hierarchies have been proposed for assessing medical evidence. The design of the study (such as a case report for an individual patient or a blinded randomized controlled trial) and the endpoints measured (such as survival or quality of life) affect the strength of the evidence. In clinical research, the best evidence for treatment efficacy is mainly from meta-analyses of randomized controlled trials (RCTs) and the least relevant evidence is expert opinion, including consensus of such. Systematic reviews of completed, high-quality randomized controlled trials – such as those published by the Cochrane Collaboration – rank the same as systematic review of completed high-quality observational studies in regard to the study of side effects. Evidence hierarchies are often applied in evidence-based practices and are integral to evidence-based medicine (EBM).
== Definition ==
In 2014, Jacob Stegenga defined a hierarchy of evidence as "rank-ordering of kinds of methods according to the potential for that method to suffer from systematic bias". At the top of the hierarchy is a method with the most freedom from systemic bias or best internal validity relative to the tested medical intervention's hypothesized efficacy.
In 1997, Greenhalgh suggested it was "the relative weight carried by the different types of primary study when making decisions about clinical interventions".
The National Cancer Institute defines levels of evidence as "a ranking system used to describe the strength of the results measured in a clinical trial or research study. The design of the study ... and the endpoints measured ... affect the strength of the evidence."
== Examples ==
A large number of hierarchies of evidence have been proposed. Similar protocols for evaluation of research quality are still in development. So far, the available protocols pay relatively little attention to whether outcome research is relevant to efficacy (the outcome of a treatment performed under ideal conditions) or to effectiveness (the outcome of the treatment performed under ordinary, expectable conditions). In 2025 Francis PT suggested that the Hierarchy of evidence pyramid for Therapeutic studies and Etiological studies be shown separately as they follow separate paths.
=== GRADE ===
The GRADE approach (Grading of Recommendations Assessment, Development and Evaluation) is a method of assessing the certainty in evidence (also known as quality of evidence or confidence in effect estimates) and the strength of recommendations. The GRADE began in the year 2000 as a collaboration of methodologists, guideline developers, biostatisticians, clinicians, public health scientists and other interested members.
Over 100 organizations (including the World Health Organization, the UK National Institute for Health and Care Excellence (NICE), the Canadian Task Force for Preventive Health Care, the Colombian Ministry of Health, among others) have endorsed and/or are using GRADE to evaluate the quality of evidence and strength of health care recommendations. (See examples of clinical practice guidelines using GRADE online).
GRADES rates quality of evidence as follows:
=== Guyatt and Sackett ===
In 1995, Guyatt and Sackett published the first such hierarchy.
Greenhalgh put the different types of primary study in the following order:
Systematic reviews and meta-analyses of "RCTs with definitive results".
RCTs with definitive results (confidence intervals that do not overlap the threshold clinically significant effect)
RCTs with non-definitive results (a point estimate that suggests a clinically significant effect but with confidence intervals overlapping the threshold for this effect)
Cohort studies
Case–control studies
Cross-sectional surveys
Case reports
=== Saunders et al. ===
A protocol suggested by Saunders et al. assigns research reports to six categories, on the basis of research design, theoretical background, evidence of possible harm, and general acceptance. To be classified under this protocol, there must be descriptive publications, including a manual or similar description of the intervention. This protocol does not consider the nature of any comparison group, the effect of confounding variables, the nature of the statistical analysis, or a number of other criteria. Interventions are assessed as belonging to Category 1, well-supported, efficacious treatments, if there are two or more randomized controlled outcome studies comparing the target treatment to an appropriate alternative treatment and showing a significant advantage to the target treatment. Interventions are assigned to Category 2, supported and probably efficacious treatment, based on positive outcomes of nonrandomized designs with some form of control, which may involve a non-treatment group. Category 3, supported and acceptable treatment, includes interventions supported by one controlled or uncontrolled study, or by a series of single-subject studies, or by work with a different population than the one of interest. Category 4, promising and acceptable treatment, includes interventions that have no support except general acceptance and clinical anecdotal literature; however, any evidence of possible harm excludes treatments from this category. Category 5, innovative and novel treatment, includes interventions that are not thought to be harmful, but are not widely used or discussed in the literature. Category 6, concerning treatment, is the classification for treatments that have the possibility of doing harm, as well as having unknown or inappropriate theoretical foundations.

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=== Khan et al. ===
A protocol for evaluation of research quality was suggested by a report from the Centre for Reviews and Dissemination, prepared by Khan et al. and intended as a general method for assessing both medical and psychosocial interventions. While strongly encouraging the use of randomized designs, this protocol noted that such designs were useful only if they met demanding criteria, such as true randomization and concealment of the assigned treatment group from the client and from others, including the individuals assessing the outcome. The Khan et al. protocol emphasized the need to make comparisons on the basis of "intention to treat" in order to avoid problems related to greater attrition in one group. The Khan et al. protocol also presented demanding criteria for nonrandomized studies, including matching of groups on potential confounding variables and adequate descriptions of groups and treatments at every stage, and concealment of treatment choice from persons assessing the outcomes. This protocol did not provide a classification of levels of evidence, but included or excluded treatments from classification as evidence-based depending on whether the research met the stated standards.
=== U.S. National Registry of Evidence-Based Practices and Programs ===
An assessment protocol has been developed by the U.S. National Registry of Evidence-Based Practices and Programs (NREPP). Evaluation under this protocol occurs only if an intervention has already had one or more positive outcomes, with a probability of less than .05, reported, if these have been published in a peer-reviewed journal or an evaluation report, and if documentation such as training materials has been made available. The NREPP evaluation, which assigns quality ratings from 0 to 4 to certain criteria, examines reliability and validity of outcome measures used in the research, evidence for intervention fidelity (predictable use of the treatment in the same way every time), levels of missing data and attrition, potential confounding variables, and the appropriateness of statistical handling, including sample size.
== History ==
=== Canada ===
The term was first used in a 1979 report by the "Canadian Task Force on the Periodic Health Examination" (CTF) to "grade the effectiveness of an intervention according to the quality of evidence obtained".
The task force used three levels, subdividing level II:
Level I: Evidence from at least one randomized controlled trial,
Level II1: Evidence from at least one well designed cohort study or case control study, preferably from more than one center or research group.
Level II2: Comparisons between times and places with or without the intervention
Level III: Opinions of respected authorities, based on clinical experience, descriptive studies or reports of expert committees.
The CTF graded their recommendations into a 5-point A–E scale: A: Good level of evidence for the recommendation to consider a condition, B: Fair level of evidence for the recommendation to consider a condition, C: Poor level of evidence for the recommendation to consider a condition, D: Fair level evidence for the recommendation to exclude the condition, and E: Good level of evidence for the recommendation to exclude condition from consideration.
The CTF updated their report in 1984, in 1986 and 1987.
=== United States ===
In 1988, the United States Preventive Services Task Force (USPSTF) came out with its guidelines based on the CTF using the same three levels, further subdividing level II.
Level I: Evidence obtained from at least one properly designed randomized controlled trial.
Level II-1: Evidence obtained from well-designed controlled trials without randomization.
Level II-2: Evidence obtained from well-designed cohort or case-control analytic studies, preferably from more than one center or research group.
Level II-3: Evidence obtained from multiple time series designs with or without the intervention. Dramatic results in uncontrolled trials might also be regarded as this type of evidence.
Level III: Opinions of respected authorities, based on clinical experience, descriptive studies, or reports of expert committees.
Over the years many more grading systems have been described.
=== United Kingdom ===
In September 2000, the Oxford (UK) Centre for Evidence-Based Medicine (CEBM) Levels of Evidence published its guidelines for 'Levels' of evidence regarding claims about prognosis, diagnosis, treatment benefits, treatment harms, and screening. It not only addressed therapy and prevention, but also diagnostic tests, prognostic markers, or harm. The original CEBM Levels was first released for Evidence-Based On Call to make the process of finding evidence feasible and its results explicit. As published in 2009 they are:
1a: Systematic reviews (with homogeneity) of randomized controlled trials
1b: Individual randomized controlled trials (with narrow confidence interval)
1c: All or none (when all patients died before the treatment became available, but some now survive on it; or when some patients died before the treatment became available, but none now die on it.)
2a: Systematic reviews (with homogeneity) of cohort studies
2b: Individual cohort study or low quality randomized controlled trials (e.g. <80% follow-up)
2c: "Outcomes" Research; ecological studies
3a: Systematic review (with homogeneity) of case-control studies
3b: Individual case-control study
4: Case series (and poor quality cohort and case-control studies)
5: Expert opinion without explicit critical appraisal, or based on physiology, bench research or "first principles"
In 2011, an international team redesigned the Oxford CEBM Levels to make it more understandable and to take into account recent developments in evidence ranking schemes. The Levels have been used by patients, clinicians and also to develop clinical guidelines including recommendations for the optimal use of phototherapy and topical therapy in psoriasis and guidelines for the use of the BCLC staging system for diagnosing and monitoring hepatocellular carcinoma in Canada.
=== Global ===
In 2007, the World Cancer Research Fund grading system described 4 levels: Convincing, probable, possible and insufficient evidence. All Global Burden of Disease Studies have used it to evaluate epidemiologic evidence supporting causal relationships.
== Proponents ==
In 1995 Wilson et al., in 1996 Hadorn et al. and in 1996 Atkins et al. have described and defended various types of grading systems.

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== Criticism ==
In 2011, a systematic review of the critical literature found three kinds of criticism: procedural aspects of EBM (especially from Cartwright, Worrall and Howick), greater than expected fallibility of EBM (Ioaanidis and others), and EBM being incomplete as a philosophy of science (Ashcroft and others). Rawlins and Bluhm note, that EBM limits the ability of research results to inform the care of individual patients, and that to understand the causes of diseases both population-level and laboratory research are necessary. EBM hierarchy of evidence does not take into account research on the safety and efficacy of medical interventions. RCTs should be designed "to elucidate within-group variability, which can only be done if the hierarchy of evidence is replaced by a network that takes into account the relationship between epidemiological and laboratory research"
The hierarchy of evidence produced by a study design has been questioned, because guidelines have "failed to properly define key terms, weight the merits of certain non-randomized controlled trials, and employ a comprehensive list of study design limitations".
Stegenga has criticized specifically that meta-analyses are placed at the top of such hierarchies. The assumption that RCTs ought to be necessarily near the top of such hierarchies has been criticized by Worrall and Cartwright.
In 2005, Ross Upshur said that EBM claims to be a normative guide to being a better physician, but is not a philosophical doctrine.
Borgerson in 2009 wrote that the justifications for the hierarchy levels are not absolute and do not epistemically justify them, but that "medical researchers should pay closer attention to social mechanisms for managing pervasive biases". La Caze noted that basic science resides on the lower tiers of EBM though it "plays a role in specifying experiments, but also analysing and interpreting the data."
Concato said in 2004, that it allowed RCTs too much authority and that not all research questions could be answered through RCTs, either because of practical or because of ethical issues. Even when evidence is available from high-quality RCTs, evidence from other study types may still be relevant. Stegenga opined that evidence assessment schemes are unreasonably constraining and less informative than other schemes now available.
In his 2015 PhD Thesis dedicated to the study of the various hierarchies of evidence in medicine, Christopher J Blunt concludes that although modest interpretations such as those offered by La Caze's model, conditional hierarchies like GRADE, and heuristic approaches as defended by Howick et al. all survive previous philosophical criticism, he argues that modest interpretations are so weak they are unhelpful for clinical practice. For example, "GRADE and similar conditional models omit clinically relevant information, such as information about variation in treatments' effects and the causes of different responses to therapy; and that heuristic approaches lack the necessary empirical support". Blunt further concludes that "hierarchies are a poor basis for the application of evidence in clinical practice", since the core assumptions behind hierarchies of evidence, that "information about average treatment effects backed by high-quality evidence can justify strong recommendations", is untenable, and hence the evidence from individuals studies should be appraised in isolation.
== See also ==
Evidence-based practice
Evidence-based medicine
Jadad scale
Source credibility
== References ==
=== Works cited ===
== External links ==
Evidence levels with explanations – entry in the Centre for Evidence-Based Medicine
Evidence-based medicine resources page – with a diagram showing different levels of evidence forming a pyramid
Systematic database of 195 hierarchies of evidence in medicine up to 08/10/2020 by Christopher J Blunt for his PhD Thesis.
This article incorporates public domain material from Dictionary of Cancer Terms. U.S. National Cancer Institute.

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A knowledge broker is an intermediary (i.e., organization or a person), that aims to develop relationships and networks with, among, and between producers and users of knowledge. This development involves providing linkages, knowledge sources, and in some cases, knowledge itself, (e.g., technical know-how, market insights, or research evidence) to organizations in its network.
== Overview ==
While the exact role and function of knowledge brokers are conceptualized and operationalized differently in various sectors and settings, a key feature appears to be the facilitation of knowledge exchange or sharing between and among various stakeholders, including researchers, practitioners, and policy makers.
A knowledge broker may operate in multiple markets and technology domains.
The concept of knowledge brokers is closely related to the concept of knowledge spillovers.
In the fields of public health, applied health services research, and social sciences, knowledge brokers are often referred to as bridges or intermediaries that link producers of research evidence to users of research evidence as a means of facilitating collaboration to identify issues, solve problems, and promote evidence-informed decision making (EIDM), which is the process of critically appraising and incorporating the best available research evidence, along with evidence from multiple other sources into policy and practice decisions.
Using a knowledge broker to facilitate the exchange of knowledge and the adoption of insights is one strategy in the broader field of knowledge management.
== Function ==
Knowledge brokers facilitate the transfer and exchange of knowledge from where it is abundant to where it is needed, thereby supporting co-development and improving the innovative capability of organizations in their network. In the field of public health, knowledge brokers facilitate the appropriate use of the best available research evidence in decision making processes, enhancing individual and organizational capacity to participate effectively in evidence-informed decision making. In this setting, knowledge brokers promote research use.
Knowledge brokers are typically involved in the following activities below:
Assessing barriers and establishing access to knowledge (i.e. screening and recognizing valuable knowledge across organizations and industries)
Learning (e.g. internalizing experiences from a diverse range of perspectives including those of industry, technology or health disciplines)
Linking of separate knowledge pools (e.g. through joint research, consulting services, and developing a mutual understanding of goals and cultures
Supporting knowledge and skill development
Facilitating individual/organizational capacity development for knowledge use (e.g., assessing current knowledge use, absorptive and receptive capacity, and readiness for change)
Implementing knowledge in new settings (e.g. combining existing knowledge in new ways)
== Expertise ==
The role of knowledge brokers is to provide a link between the knowledge producers and knowledge users. In order to facilitate this knowledge exchange, knowledge brokers must build rapport with their target audiences and forge new connections across domains.
Research into effective knowledge brokers, conducted by University of Oxford researchers, found that committed knowledge leadership is key to mobilizing research across organisational boundaries and embedding it in practice. In the longitudinal research funded by the National Institute for Health and Care Research (NIHR), the study found three variations of knowledge leadership, of transposing, appropriating and contending academic research.
A successful knowledge broker will possess:
Expertise in synthesizing and adapting information for use in different local contexts
A non-judgmental, respectful manner
Excellent written and oral communication skills
Strong interpersonal and networking skills
An understanding of the context, processes, and key influencers of both the producers and users of knowledge
Critical thinking skills
Critical reflection abilities and practices
Strategic planning skills and experience
An understanding of (higher-)education principles and practices
Knowledge brokers possess a portfolio of intellectual capital or expertise typically spanning the "specialized jargon, knowledge, and form(s) of reasoning" of multiple disciplines. Assuming that expertise lends itself to interdisciplinary exchange, the adequacy of a knowledge broker's understanding of a field can also be understood in terms of their possession of varieties of intellectual autonomy concerning the field, as suggested by Nguyen (2018):
Direct autonomy is "where we seek to understand arguments and reasons for ourselves."
Delegational autonomy is "where we seek to find others to invest with our intellectual trust when we cannot understand."
Management autonomy, is "where we seek to encapsulate fields, in order to manage their overall structure and connectivity."
Nguyen (2018) responds to Elijah Millgram's The Great Endarkenment, where Millgram proposes between-field translation to reduce the internal and mutual incomprehensibility (i.e., for experts in a discipline, and between respective disciplines) of hyperspecialized disciplines. The goal of translation is intellectual transparency, or making clear the models, values, defeaters, and trade-offs of arguments in and between disciplines.
Intellectual transparency is currently scarce due to both the above cited incomprehensibility problems, and the inevitability of mistakes (out of anyone's purview, due to resource constraints in personal and group knowledge management) accruing in "modern scientific practical arguments," draped across many fields" that are already individually difficult to keep tabs on. Nguyen argues that "intellectual transparency will help us achieve direct autonomy, but many intellectual circumstances require that we exercise delegational and management autonomy. However, these latter forms of autonomy require us to give up on transparency" (pp. 1).
== Examples of knowledge brokers ==
Every individual or organization, which has access to knowledge from several, unconnected entities, can theoretically act as a knowledge broker. Certain types of organizations have been identified to be acting primarily as knowledge brokers:
Dedicated knowledge brokers
Venture capitalists
Consulting firms
Evidence-informed decision making support organizations (e.g., Health Evidence, which offers dedicated knowledge brokers to mentor or facilitate evidence-informed decision making in public health organizations, and the National Collaborating Centre for Methods and Tools, which has knowledge brokers facilitating a public health Community of Practice
=== Climate change knowledge broker initiative ===
A project funded by the Climate & Development Knowledge Network is aiming to integrate sources of climate change information and tailor data into relevant information products. Access to reliable information and data, and the ability to share lessons and experience, are considered key ingredients in tackling climate change, particularly within developing countries. However, although numerous websites, portals and online platforms have been set up to provide such information, the ‘knowledge infrastructure’ within the climate and development sector is still weak. The project aims to fill some of the gaps and provide bridges between isolated initiatives.
A study by IISD investigated the value of knowledge brokers within the climate change sphere. Interviews and surveys were conducted with more than 200 online climate change information users to understand their needs, preferences and behaviours. The findings were published in the paper "A user-oriented analysis of online knowledge brokering platforms for climate change and development". This publication identifies potential areas for innovation in online knowledge brokering and highlights the need for taking climate knowledge brokering beyond its online functions.
== References ==