MAGIC is a research and innovation programme and non-profit initiative within the health sector, working to improve the creation, dissemination and dynamic updating of clinical practice guidelines, evidence summaries and decision aids.
MAGIC has been realised using the GRADE methodology and through international collaboration, combined with the latest web technology, intuitive design and emphasis on open and linked digitally structured data.
Frameworks, methodologies and technological
solutions for GRADE guidelines
Among several initiatives and platforms used to create and disseminate guidelines to users point of care is the MAGIC Authoring and Publication Platform (MAGICapp). MAGICapp represents a web-based platform that allows digital and structured authoring, dissemination and dynamic updating of evidence summaries, recommendations and decision aids.
The PICO linked data model applied in MAGICapp breaks down the concept of a guideline document into discrete elements of content. This way of digitally structuring data allows content to be published in multilayered and flexible formats, usable on all devices and facilitates adaptation and dynamic updating of individual recommendations in a living guideline model. The linked data structure - combined with a coding module for annotating PICO questions and recommendations with terms from various structured terminologies and making the data available through an API – allows for connections (EHR, other platforms), re-use and sharing of data across the Ecosystem.
Despite globally recognized advances in research methods and systems for evidence-based health care, society faces challenges in delivering high quality and evidence-based health care to patients. Contributing to these challenges are an exponential growth of published research of limited value for society, combined with an epidemic of overdiagnosis and overtreatment - as well as underuse of effective interventions. Such insights have resulted in international calls and initiatives to increase value and reduce waste in research and health care.
Clinical practice guidelines, aiming to provide guidance based on best current evidence about patient management, represent key information resources for health care professionals. Some however, call for "a post-guidelines era" in health care, given well recognized problems and limitations, including how guidelines fail to provide timely information at the point of care. In an era where digitally structured data and the internet have revolutionized access to information "anywhere, anytime, on any device", the health care sector seems to lag behind.
This case study demonstrates feasibility of more efficient evidence synthesis and dissemination while adhering to the highest standards of trustworthiness, within the Evidence Ecosystem. In this case study we looked at innovations concerning increased patient involvement, stringent conflict of interest management, new medical publishing processes and new formats.
The case study also highlights limitations in making the Ecosystem work fully, with the critical steps of successful implementation and improvement of care remaining unanswered. The facilitation of rapid change in practice is itself a daunting challenge. Potential obstacles for practice-change in this case include cardiologists reluctant to change practice before the local protocols or the international guidelines on which they usually rely upon change, heart surgeons’ reluctance to lose a group of patients on whom they are used to operate, and a paucity of leadership in applying best current evidence in hospital programs.
Dept. of Medicine, Gjøvik , Innlandet Hospital Trust- Norway
Dept. of Medicine, Lovisenberg Diaconal Hospital, Norway
Ass.professor, Faculty of Medicine, University of Oslo, Norway
Researcher, Norwegian Institute of Public Health, Norway
Dept. of Medicine, Gjøvik , Innlandet Hospital Trust- Norway
Dept. of Medicine, Diakonhjemmet Oslo, Norway
PhD student, HELSAM, University of Oslo, Norway
Dept. of Medicine, Gjøvik , Innlandet Hospital Trust- Norway
Dept. of Medicine, Diakonhjemmet Oslo, Norway
PhD student, HELSAM, University of Oslo, Norway
Dept. of Clinical Epidemiology and Biostatistics, McMaster University, Canada
Dept. of Medicine, Gjøvik , Innlandet Hospital Trust- Norway
Dept. of Medicine, Lovisenberg Diaconal Hospital, Norway
PhD student, HELSAM, University of Oslo, Norway
Division of General Internal Medicine, University Hospitals of Geneva, Switzerland
Dept. of Medicine, Gjøvik , Innlandet Hospital Trust- Norway
Dept. of Medicine, Lovisenberg Diaconal Hospital, Norway
PhD student, HELSAM, University of Oslo, Norway
Dept. of Clinical Epidemiology and Biostatistics, McMaster University, Canada
Dept. of Clinical Epidemiology and Biostatistics, McMaster University, Canada
Dept. of Medicine, University of Toronto, Canada
Dept of Hematology and Oncology
Mayo Clinic, Rochester, Minnesota, USA
Medical Researcher, Oslo University Hospital, Norway
Systematic Overviews through advancing Research Technology, Canada
Researcher, Norwegian Institute of Public Health, Norway
Hospital St. Pau, Barcelona, Spain
Deputy Director, German Cochrane Centre, Germany
Senior lecturer, University of Dundee, Scotland
American University, Beirut, Lebanon
Fullstack Systems
San Francisco, USA
Fullstack Systems
San Francisco, USA
New Window
Nesodden, Norway
The GRADE working group is a collection of organizations working together since 2001 to develop a common framework to improve quality of guideline development.
We use the GRADE methodology as the basis of all our work, and all MAGIC researchers are active members of the GRADE working group.
MAGICapp is built to facilitate development of guidelines developed with GRADE.
Epistemonikos is a searchable database of Evidence and studies, built on relations between studies and overviews based on the primary studies they include.
We work with them on the topic of data-flow, import of studies, and continuous updating.
The people behind Epistemonikos are also responsible for the technical development of the Interactive Summary of Findings (iSoF) framework and the Evidence to Recommendation/Decision (EtR) framework developed within DECIDE.
Covidence is a web-based software designed specifically to perform the first stages of a systematic review.
It can be used by guideline panels that needs to make their own meta-analysis, but possibly also for reference inclusion and exclusion in the primary search for studies to use for effect estimates for the PICO questions you have in your guideline. We can currently import studies from Covidence and references, but are planning a closer integration in the future.
The organizations above do not necessarily endorse MAGIC and our description of them are purely to help you navigate and get an idea of the landscape out there. We refer to the entities own web pages for official descriptions and endorsements.