The Second-level short specialisation degree in Principles and Practice of Systematic Reviews and Meta-Analysis in the Biomedical Field prepares professionals who work (or want to work) in the biomedical field, in designing, conducting and analysing a systematic review for evidence-based healthcare questions in a view of methodological and processing reproducibility.
The course focuses on the applicative aspects of meta-analysis, from basic methods to multi-level, multivariate and Bayesian networks, and the automation of review and update processes. Basic and advanced methods are treated through the use of the R software.
It is a Level 2 Master issued online and on-demand, to allow attendees to follow the course when it’s most convenient for them.
The Second-level short specialisation degree in Principles and Practice of Systematic Reviews and Meta-Analysis in the Biomedical Field comprises 5 modules. Since evidence synthesis covers an increasingly important role in research, medical practice and health-related policy decision-making processes, an essential condition to implement the results deriving from a systematic and consequent meta-analysis is their reproducibility. Therefore, the course covers classic systematic review methodology topics, alongside innovative text mining and machine learning applications. Meta-analysis is treated by giving ample space to the applicative aspects, from basic methods to multilevel, multivariate and network meta-analysis models. The R software will be used.
Empirical evidence quality scaling is introduced by taking into account the ethical quantification principles and the peculiarities of the real world evidence. Reproducibility is covered by following its taxonomy, from technical to methodological and scientific reproducibility. The literate programming is treated in R Markdown with applicative examples.
The Second-level short specialisation degree in Principles and Practice of Systematic Reviews and Meta-Analysis in the Biomedical Field is mainly addressed to graduates in medical, biological, pharmacological, mathematical and statistical sciences. The Master identifies in those professionals who already work (or want to work) in the biomedical field, the ideal candidates to guide in the implementation of solid and reproducible systematic reviews.
The Master provides applicative knowledge of growing significance for all medical practice and research fields, and its purpose is training professionals with high systematic review planning, conduction and analysis skills. The competencies acquired during the Master are relevant for further specialization of already employed healthcare professionals, and to define technical-quantitative profiles to work in the healthcare, biomedical research and CRO field.
The Second-level short specialisation degree in Principles and Practice of Systematic Reviews and Meta-Analysis in the Biomedical Field provides a path divided into 5 online and on-demand modules, as follows:
- Module 1. SYSTEMATIC REVIEW METHODOLOGY
Purpose of this module is transferring the methods and tools to create systematic reviews, from protocol drafting and registration, to reporting and critical evaluation.
- Module 2. TEXT-MINING AND MACHINE LEARNING IN SYSTEMATIC REVIEWS
The use of text-mining tools and machine learning algorithms in conducting systematic reviews is becoming an increasingly popular approach to optimize human and economic resources and the time required to complete these reviews. This module describes the most promising approaches in literature related to de-novo screening and to a review upgrade and extension, with R application for open source tools.
- Module 3. META-ANALYSIS METHODOLOGY 1
This module provides an introduction to the terms and methodological concepts involved in this evidence synthesis approach. Some of the basics covered include the synthesis of the measures having an effect, an introduction to meta-analysis, and the heterogeneity component between studies. It includes practical examples and applications.
- Module 4. META-ANALYSIS METHODOLOGY 2
It covers advanced meta-analysis methodology aspects. The topics covered include multivariate/multilevel meta-analysis models, Bayesian meta-analysis, and frequentist and Bayesian network meta-analysis (NMA). It includes practical examples and applications.
- Module 5. RESEARCH REPRODUCIBILITY
This module covers many different topics related to reproducibility, from a quantitative and computing standpoint – such as selective inference and literate programming – and from an epidemiology and science philosophy one.
The general ranking of merit for the academic year 2023/24 will be published on the Italian page of this Master according to the timing provided in the Call.
Every module is divided into 4 weeks of asynchronous lessons and there will be one week off before the next module. There will be an easy and frequent interaction between students and professors, through Moodle’s Forum. R is the reference software, with a streamlined interface for those topics that will allow it. Video-lessons will be held between November and May with periodical homework to verify the competencies acquired. Homework too will be issued on demand. The project work to discuss the final exam will be completed between June and July, even on cases that specifically interest the students, in agreement with the tutor. The project work is discussed online, on the Zoom platform.
No, there will not be any stages or traineeships.
There will be a final project work that can be completed also on the student’s workplace analysis and data. The topic will be agreed with the course’s professors.
No, unfortunately there will not be any form of facilitation or prizes. However, healthcare professionals are exonerated from CME obligations.
Attendance is mandatory, even if the course is held online. However, since video-lessons are pre-recorded, they can be watched at any time, and it is therefore easy to catch up with the study plan. The course administrative office and the professors are available to help students in case of onerous engagements of periods of intense work.