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. [1] 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 clinical practice guidelines as well as other decision makers. [2]
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. [3] [4]
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. [5] 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:
GRADE rates quality of evidence as follows: [6] [7]
High | There is a lot of confidence that the true effect lies close to that of the estimated effect. |
Moderate | There is moderate confidence in the estimated effect: The true effect is likely to be close to the estimated effect, but there is a possibility that it is substantially different. |
Low | There is limited effect in the estimated effect: The true effect might be substantially different from the estimated effect. |
Very low | There is very little confidence in the estimated effect: The true effect is likely to be substantially different from the estimated effect. |
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. [8] The GRADE approach to assess the certainty in evidence is widely applicable, including to questions about diagnosis, [9] [10] prognosis, [11] [12] network meta-analysis [13] and public health. [14]
Factors and criteria that determine the direction and strength of a recommendation:
Factor and criteria* | How the factor influences the direction and strength of a recommendation |
---|---|
Problem This factor can be integrated with the balance of the benefits and harms and burden. | The problem is determined by the importance and frequency of the health care issue that is addressed (burden of disease, prevalence or baseline risk). If the problem is of great importance a strong recommendation is more likely. |
Values and preferences | This describes how important health outcomes are to those affected, how variable they are and if there is uncertainty about this. The less variability or uncertainty there is about values and preferences for the critical or important outcomes, the more likely is a strong recommendation. |
Quality of the evidence | The confidence in any estimate of the criteria determining the direction and strength of the recommendation will determine if a strong or conditional recommendation is offered. However, the overall quality that is assigned to the recommendation is that of the evidence about effects on population-important outcomes. The higher the quality of evidence the more likely is a strong recommendation. |
Benefits and harms and burden | This requires an evaluation of the absolute effects of both the benefits and harms and their importance. The greater the net benefit or net harm the more likely is a strong recommendation for or against the option. |
Resource implications | This describes how resource intense an option is, if it is cost-effective and if there is incremental benefit. The more advantageous or clearly disadvantageous these resource implications are the more likely is a strong recommendation. |
Equity This factor is often addressed under values preferences, and frequently also includes resource considerations | The greater the likelihood to reduce inequities or increase equity and the more accessible an option is, the more likely is a strong recommendation. |
Acceptability This factor can be integrated with the balance of the benefits and harms and burden. | The greater the acceptability of an option to all or most stakeholders, the more likely is a strong recommendation. |
Feasibility This factor includes considerations about values and preferences, and resource implications. | The greater the acceptability of an option to all or most stakeholders, the more likely is a strong recommendation. |
Over 100 organizations (including the World Health Organization, [15] 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,[ citation needed ] and the Saudi Arabian Ministry of Health [16] ) have endorsed and/or are using GRADE to evaluate the quality of evidence and strength of health care recommendations.[ citation needed ]
Evidence-based medicine (EBM) is "the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients". The aim of EBM is to integrate the experience of the clinician, the values of the patient, and the best available scientific information to guide decision-making about clinical management. The term was originally used to describe an approach to teaching the practice of medicine and improving decisions by individual physicians about individual patients.
A randomized controlled trial is a form of scientific experiment used to control factors not under direct experimental control. Examples of RCTs are clinical trials that compare the effects of drugs, surgical techniques, medical devices, diagnostic procedures or other medical treatments.
Cochrane is a British international charitable organisation formed to organise medical research findings to facilitate evidence-based choices about health interventions involving health professionals, patients and policy makers. It includes 53 review groups that are based at research institutions worldwide. Cochrane has approximately 30,000 volunteer experts from around the world.
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A medical guideline is a document with the aim of guiding decisions and criteria regarding diagnosis, management, and treatment in specific areas of healthcare. Such documents have been in use for thousands of years during the entire history of medicine. However, in contrast to previous approaches, which were often based on tradition or authority, modern medical guidelines are based on an examination of current evidence within the paradigm of evidence-based medicine. They usually include summarized consensus statements on best practice in healthcare. A healthcare provider is obliged to know the medical guidelines of his or her profession, and has to decide whether to follow the recommendations of a guideline for an individual treatment.
A systematic review is a scholarly synthesis of the evidence on a clearly presented topic using critical methods to identify, define and assess research on the topic. A systematic review extracts and interprets data from published studies on the topic, then analyzes, describes, and summarizes interpretations into a refined conclusion. For example, a systematic review of randomized controlled trials is a way of summarizing and implementing evidence-based medicine.
Gordon Henry Guyatt is a Canadian physician who is Distinguished University Professor in the Departments of Health Research Methods, Evidence and Impact and Medicine at McMaster University in Hamilton, Ontario. He is known for his leadership in evidence-based medicine, a term that first appeared in a single-author paper he published in 1991. Subsequently, a 1992 JAMA article that Guyatt led proved instrumental in bringing the concept of evidence-based medicine to the world's attention.[2] In 2007, The BMJ launched an international election for the most important contributions to healthcare. Evidence-based medicine came 7th, ahead of the computer and medical imaging. [3][4] Guyatt's concerns with the role of the medical system, social justice, and medical reform remain central issues that he promoted in tandem with his medical work. On October 9, 2015, he was named to the Canadian Medical Hall of Fame.
A hierarchy of evidence is a heuristic used to rank the relative strength of results obtained from scientific 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 and the endpoints measured 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). 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).
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David Lawrence Sackett was an American-Canadian physician and a pioneer in evidence-based medicine. He is known as one of the fathers of Evidence-Based Medicine. He founded the first department of clinical epidemiology in Canada at McMaster University, and the Oxford Centre for Evidence-Based Medicine. He is well known for his textbooks Clinical Epidemiology and Evidence-Based Medicine.
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