A5071868716- Health Systems, Economic Evaluations, Quality of Life
- Clinical practice guidelines implementation
- Meta-analysis and systematic reviews
- Venous Thromboembolism Diagnosis and Management
- Health Policy Implementation Science
- Asthma and respiratory diseases
- Healthcare cost, quality, practices
- Delphi Technique in Research
- Allergic Rhinitis and Sensitization
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Atrial Fibrillation Management and Outcomes
- Health Sciences Research and Education
- Central Venous Catheters and Hemodialysis
- Primary Care and Health Outcomes
- Patient-Provider Communication in Healthcare
- Food Allergy and Anaphylaxis Research
- Healthcare Policy and Management
- Pharmaceutical industry and healthcare
- Statistical Methods in Clinical Trials
- Respiratory Support and Mechanisms
- Climate Change and Health Impacts
- Respiratory and Cough-Related Research
- Cardiac, Anesthesia and Surgical Outcomes
- Health and Medical Studies
- Ethics in Clinical Research
McMaster University
2016-2025
Cochrane
2016-2025
Impact
2017-2025
Fraunhofer Institute for Translational Medicine and Pharmacology
2024-2025
IRCCS Humanitas Research Hospital
2024-2025
Humanitas University
2021-2025
University of Freiburg
2012-2024
Health Sciences Centre
2015-2024
Department of Health Research
2017-2024
Government of Western Australia Department of Health
2024
Guidelines are inconsistent in how they rate the quality of evidence and strength recommendations. This article explores advantages GRADE system, which is increasingly being adopted by organisations worldwide
Non-randomised studies of the effects interventions are critical to many areas healthcare evaluation, but their results may be biased. It is therefore important understand and appraise strengths weaknesses. We developed ROBINS-I ("Risk Of Bias In Studies - Interventions"), a new tool for evaluating risk bias in estimates comparative effectiveness (harm or benefit) from that did not use randomisation allocate units (individuals clusters individuals) comparison groups. The will particularly...
GRADE Working Group (oxman{at}online.no)Informed Choice Research Department, Norwegian Health Services Centre, PO Box 7004, St Olavs Plass, 0130 Oslo, NorwayCorrespondence to: Andrew D Oxman,Accepted 5 March 2004
Section:ChooseTop of pageAbstract <<CONTENTSOBJECTIVEMETHODSSIGNIFICANCE OF EVIDENCE-...SUMMARY CONCLUSIONS AND T...DEFINITION EPIDEMIOLO...DEFINITION UIP PATTERNDIAGNOSISNATURAL HISTORY IPFSTAGING PROGNOSISTREATMENTTREATMENT SELECTED COM...PALLIATIVE CAREMONITORING THE CLINICAL C...FUTURE DIRECTIONSReferencesCITING ARTICLES
Section:ChooseTop of pageAbstract <<Executive SummaryContentsOverviewIntroductionMethodsRecommendations for Speci...ConclusionsFuture DirectionsReferencesCITING ARTICLES
The GRADE system classifies recommendations made in guidelines as either strong or weak. This article explores the meaning of these descriptions and their implications for patients, clinicians, policy makers
Network meta-analysis (NMA), combining direct and indirect comparisons, is increasingly being used to examine the comparative effectiveness of medical interventions. Minimal guidance exists on how rate quality evidence supporting treatment effect estimates obtained from NMA. We present a four-step approach in each direct, indirect, NMA based methods developed by GRADE working group. Using an example published NMA, we show that varies high very low across ratings given whole network are...
The GRADE system can be used to grade the quality of evidence and strength recommendations for diagnostic tests or strategies. This article explains how patient-important outcomes are taken into account in this process