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Clinical Data Management and Analysis

Curs d'expert universitari impartit en anglès

Clinical Data Management and Analysis


Poor training in statistics and data analysis are frequent and lasting deficiencies among health professionals. Both their nature, which is markedly different from that of the fundamental subjects of medicine, and their scarce and early presence in the medicine curriculum, are determining factors of these deficiencies. However, it is enough to read an original article published in a scientific journal to be convinced of their importance. In addition, in the era of "Big Data", the ability to manipulate and analyze data to extract information ("data science"), will become a fundamental competitive advantage, if not an absolute necessity in any professional environment, and medicine will not be an exception.

This program aims to remedy the lack of training in data analysis of health professionals. Its approach is eminently practical, presenting analysis techniques from the point of view of their application in the specific field of clinical research, rather than from their theoretical foundations.

Other differences with respect to traditional biostatistics courses are the attention to data acquisition, manipulation and preparation tasks, the exploration of data through graphics, the use of modern analysis methods such as the bootstrap, or literate programming as a means to ensure reproducible research results, all based on the R language, one of the most used languages in data science.


The course has three modules that can also be taken independently:

  • Data analysis (9 ECTS)
  • Data management (3 ECTS)
  • Statistical modeling (3 ECTS)

Check the dates of each module in the Program tab/section in case you want to take them separately. If you are interested in this modality, contact IFMiL through the email to opt for it.

Acreditació: Crèdits Universitaris ECTS (European Credit Transfer System)

Dirigit a

Physicians and other professionals in the health sector (university graduates and diploma holders) interested in acquiring the knowledge and developing the skills that will allow them to tackle the analysis of data from clinical research projects.

Career opportunities:

  • Clinical research teams in health centers, biomedical research institutes, pharmaceutical or healthcare device companies, and contract research organizations (CROs).
  • Healthcare management support.
  • Healthcare technology assessment bodies.


  • To develop skills for the acquisition of data stored in different electronic formats in common use.
  • To know the basic techniques of descriptive statistical analysis and exploratory analysis using graphics.
  • To understand the fundamental concepts of statistical inference involved in significance tests (p-value) and parameter estimation (confidence intervals).
  • To know the most used inferential techniques in clinical research and be able to apply them and interpret their results.
  • Develop literate programming skills to ensure the traceability and reproducibility of the processes of reading, preparing and analysing data, and interpreting and communicating results.
  • To know different ways of organizing the data of a clinical study and how to modify this organization when needed.
  • To know the different data types (numeric, dates and character strings), and how to work with them.
  • To know how to define and implement a data validation plan.
  • To understand the multivariate nature of complex problems, and to promote multivariate thinking.



  • Introduction to R and RStudio
  • R data structures
  • Data acquisition
  • Data preparation
  • Exploratory data analysis
  • Statistical inference
  • Analysis of categorical data
  • Analysis of quantitative data
  • Assessing relationships
  • Reproducible research

M1 - Data analysis dates: 26/10/2022 - 1/03/2023 

Webinars M1:  8/11/2022, 18:00h     1/3/2023, 18:00h.

Module 1 price if taken independently: 1.150€ (977€ collegiate)

Contact us if you want to study this modality.



  • Working with dataframes
  • Working with variables
  • Data validation

M2 - Data management dates: 01/03/2023 - 3/05/2023

Webinar M2: 3/5/2023, 18:00h.

Module 2 price if taken independently: 413€ (351€ collegiate)

Contact us if you want to study this modality.



  • General linear model
  • Logistic regression model
  • Cox proportional hazards model
  • Poisson regression model

M3 - Statistical modeling dates: 01/05/2023 - 30/06/2023 

Webinar M3: 30/06/2023, 18:00h.

Module 3 price if taken independently: 413€ (351€ collegiate)

Contact us if you want to study this modality.


Albert Cobos

PhD in Medicine. MSc in Applied Statistics. Lecturer at the Bioestatistics Unit, Departament de Fonaments Clínics, Facultat de Medicina, Universitat de Barcelona.

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