Intensive Short Courses an der BSPH

Die Teilnehmerinnen und Teilnehmer der Intensive Short Courses erwerben kompaktes Wissen in Public Health und Epidemiologie. Die Vermittlung von Methodenkenntnissen ist ein wichtiger Schwerpunkt.

Die Kurse richten sich an Doktoranden, Studierende aus Public Health Masterstudiengängen im In- und Ausland und an Beruftstätige.

Eine Übersicht der Kurse der vergangenen Jahre finden Sie unter "Archiv".

Sie befinden sich hier:

Intensive Short Courses sind:

  • sind Bestandteil des Postgraduiertenprogramms des Instituts für Public Health der Charité - Universitätsmedizin Berlin
  • werden von Dozierenden renommierter Hochschulen und Forschungseinrichtungen geleitet
  • werden in der Regel in englischer Sprache angeboten
  • haben grundsätzlich Lehrcharakter
  • sind mit ECTS ausgewiesen
  • erfordern eine Prüfungsleistung
  • die Belegung der Plätze erfolgt nach Eingangsdatum der Anmeldung

Intensive Short courses 2020

Miguel Hernán / Katalin Gémes: Causal inference - Learning what works, February 19 - 20, 2020


Causal inference: Learning what works

Lecturers: Miguel Hernán (Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health), Katalin Gémes (Karolinska Institutet, Sweden)

Biography: Miguel Hernán conducts research to learn what works to improve human health. Together with his collaborators, he designs analyses of healthcare databases, epidemiologic studies, and randomized trials. Miguel teaches clinical data science at the Harvard Medical School, clinical epidemiology at the Harvard-MIT Division of Health Sciences and Technology, and causal inference methodology at the Harvard T.H. Chan School of Public Health, where he is the Kolokotrones Professor of Biostatistics and Epidemiology. His edX course Causal Diagrams and his book Causal Inference, co-authored with James Robins, are freely available online and widely used for the training of researchers. Miguel is an elected Fellow of the American Association for the Advancement of Science and of the American Statistical Association, an Editor of Epidemiology, and past Associate Editor of Biometrics, American Journal of Epidemiology, and the Journal of the American Statistical Association.

Katalin Gémes is a postdoctoral researcher at the Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden. She defended her PhD work in the field of Public Health Epidemiology. She currently works with combining data from observational studies and routinely collected administrative information to compare the effectiveness of different hypothetical interventions on diet and alcohol consumption on the risk of cardiovascular diseases.

Course objectives: To learn how to determine “what works” using data from observational and randomized studies 

Description: The course introduces students to a general framework for the assessment of comparative effectiveness and safety, with an emphasis of the use of routinely collected data in healthcare settings. The framework relies on the specification and emulation of a hypothetical randomized trial: the target trial. The course explores key challenges for causal inference and critically reviews methods proposed to overcome those challenges. The methods are presented in the context of several case studies for cancer, cardiovascular, and renal diseases.

Learning Objectives: After successful completion of this course, students will be able to:

  • Formulate sufficiently well-defined causal questions for comparative effectiveness research
  • Specify the protocol of the target trial
  • Design analyses of observational data that emulate the protocol of the target trial
  • Identify key assumptions for a correct emulation of the target trial

Pre-course reading: Chapters 1-3 of the book Hernán MA, Robins JM (2020). Causal Inference: What If. Boca Raton: Chapman & Hall/CRC, forthcoming. The book can be downloaded (for free) from


1.25 ECTS 


  • 312,50 €
  • 212,50 € for enrolled students (proof required)

CANCELLED Julie Buring / Pamela Rist / Bill Miller: From methods to manuscript, March 23 - 27, 2020


A modern researcher's toolbox: from methods to manuscript

40 Seats

Date: March 23 - 27, 2020

Pre-requisites: Introductory level epidemiology and statistics. This is a masters level / postgraduate course.

Part 1: March 23rd and 24th - Julie Buring and Pamela Rist

Course Description: During this two day course, participants will develop a solid foundation of applied principles and methods of epidemiology, use these to evaluate relevant clinical and public health questions, and turn their research into publishable work. The format will include lectures, group exercises and seminars.

  • Critical Thinking in Epidemiology: Examples from the Literature
  • Types of Epidemiologic Studies in the Literature (Descriptive, Analytic)
  • Measures of Disease Frequency, Measures of Association and their Scales
  • Interpretation of the Findings: Association versus Causation
  • Critical Evaluation of the Medical Literature
  • Principles of Randomized Trials; Strengths and Weaknesses
  • Sample size and power, P-values and confidence intervals
  • Screening

Please click here for a detailed schedule.

Part 2: March 25th to 27th - Bill Miller

Course Description: This three-day course is designed to improve the participants’ scientific writing. The focus will be on manuscripts for publication, but the principles apply to all forms of scientific writing. The objectives of this course are to:

  • Understand the components of typical scientific publications and maximize the potential for communicating a study’s results effectively.
  • Improve the writing style to enhance communication, focusing on writing clearly and concisely.
  • Identify ways to improve the participant’s writing effectiveness.
  • Understand the editorial and review process of journals, including responding to reviews and giving strong reviews as a reviewer.

Please click here for a detailed schedule.

Pre-course Preparations for Part 2:

Identify 2-4 papers of interest to you in the scientific literature with the following characteristics:

  • A well-written paper that is easy to read
  • A poorly written paper that is difficult to read
  • A paper in a general journal (e.g. JAMA, Lancet, etc.)
  • A paper in a specialty journal

Bring your own manuscripts that you are working on – just starting, drafts completed, or nearly finished. Any status is acceptable. If you don’t have papers, consider bringing a grant or an abstract.


  • Julie E. Buring, ScD, Professor of Medicine, Harvard Medical School and Professor of Epidemiology, Harvard T.H. Chan School of Public Health
  • Pamela M. Rist, ScD, Assistant Professor of Medicine, Harvard Medical School and Assistant Professor of Epidemiology, Harvard T.H. Chan School of Public Health
  • William (Bill) Miller, MD, PhD, MPH, Senior Associate Dean for Research and Professor, Division of Epidemiology in the College of Public Health at The Ohio State University


Students can take Parts 1&2 for 3 ECTS, only Part 1 for 1.25 ECTS or only Part 2 for 1.75 ECTS


  • 750 € for Part 1&2
  • 312,50 € for Part 1 only | 437,50 € for Part 2 only

Enrolled students (proof required):

  • 510 € for Part 1&2
  • 212,50 € for Part 1 only | 297,50 € for Part 2 only


Charité Campus Mitte
Philippstraße 11
10115 Berlin


Please use the registration form or send an e-mail to Tanja Te Gude
Tel. +49 30 450 570 812

ONLINE Malcolm Barrett: Mastering R for Epidemiologic Research, August 31 - Sept 12, 2020

Advanced Epidemiologic Methods: Mastering R for Epidemiologic Research

ONLINE COURSE, 50 (virtual) seats

The course is for researchers, public health professionals, epidemiologists, and clinicians who want to improve their R coding skills, who want to learn modern tools in the R ecosystem, like the tidyverse and Shiny, or who want to get started writing software in R.

Date: August 31 - Sept. 12, 2020

Lecturer: Malcolm Barrett, MPH

Malcolm Barrett is a PhD candidate in epidemiology at the University of Southern California. He studies vision loss and eye diseases that affect vision, like diabetic retinopathy. Specifically, he works on methods to improve the study of how vision impacts quality of life, including tools from psychometrics and causal inference, to make vision-specific quality of life analyses more accurate and more interpretable. In addition to applied research, Malcolm also develops R packages for epidemiologic and biostatistical methods, teaches R, and organizes the Los Angeles R Users Group. He regularly contributes to open source software, including favorite community projects like ggplot2 and R Markdown.

Learning objectives:

At the end of the course, participants will have:

  • Mastered the tidyverse, a set of principled tools for data science. The tidyverse is a friendly, readable, and fast set of packages intended to work well together, to improve code readability, and to make analyses more reproducible.
  • Written dynamic documents using best practices for reproducible research, including using R Markdown. R Markdown intertwines code and text so that reports and articles are fully reproducible and exportable to PDF, HTML, Word, and more. R Markdown also has excellent support for citation management and formatting for journals.
  • Modeled simple statistical and causal problems using both classical regression (linear, logistic) and G-methods.
  • Written robust functions, programmed with functions, and created a basic R package.
  • Built ready-to-share web applications entirely in R using the Shiny framework.


Basic epidemiology and statistics. Some experience with R programming will be helpful, but those new to R can take a free introductory course on DataCamp:  


R for Data Science ( and Advanced R, ed. 2 (, both free online.

About the online format:

  • The course starts Monday August 31st and will run for 2 weeks with instructor/TA support
  • Course material will be linked from Blackboard
  • Students will need to complete and submit 4 assignments (online) for credit. We will allow submissions of the assignments up to 3 weeks from the course start date. Students can therefore work through the course at an even slower pace (also on the weekends, if desired), just being aware that the office hour support will only run the first two weeks. For those who still prefer the compact format, it is of course also possible to finish the course within 1 week.
  • To maximize flexibility all around, the course will be entirely asynchronous. That is, students can work entirely at their own pace. The content will be equivalent to the 1 week, full-time course (3 ECTS). Some content will be clearly marked as “optional” for those who want to take a “deeper dive”, seek additional examples and/or want to learn more advanced programming skills. Those who have less time could skip these sections.
  • During the 2-week period starting Aug 31st, on weekdays, Malcolm Barrett would hold regular office hours (via Zoom) in the early morning Los Angeles time, end of work day Berlin time (exact time TBD). Teaching assistants (Berlin-based) would offer office hours earlier in the day.

Course Information:

  • Course language: English
  • ECTS points: 3
  • Course Fee: 510€ for students, 750€ for other participants


Please use the registration form or send an e-mail to Tanja Te Gude

Tel. +49 30 450 570 812

CANCELLED Rolf H.H. Groenwold / Maarten van Smeden: Causal research and prediction modeling

Advanced Epidemiologic Methods: causal research and prediction modeling


40 Seats

Date:  (August 17 - 21, 2020) POSTPONED to 2021!


  • Rolf H.H. Groenwold, MD, PhD, Leiden University Medical Center (NL)
  • Maarten van Smeden, PhD, Leiden University Medical Center (NL)

Learning objectives:

By the end of this week, participants should be able to:

  • Critically assess the results of epidemiological studies on causal relationships or prediction models
  • Correctly define exposures and learn how to best represent them in models
  • Understand difference between various sources of bias (confounding, measurement error and missing data) and the way these biases may differentially affect studies on causal relationships and prediction models.
  • Describe key assumptions of methods used to control for (time-varying) confounding.
  • Describe key assumptions of methods used to handle missing observations.
  • Understand the reasons for and consequences of overfitting prediction models
  • Describe recent developments in the fields of causal research and prediction modelling


  • Basic knowledge of epidemiology
  • Familiarity with R statistical software (for a short introduction see


  • 750 €
  • 510 € for enrolled students (proof required)



Please use the registration form or send an e-mail to Tanja Te Gude
Tel. +49 30 450 570 812

Download Flyer here

Gesundheitspädagogik, 24.08. - 28.08. und 17.09. - 19.09.2020 (2 Blöcke)

25 Plätze

Datum: 24.08. - 28.08. und 17.09. - 19.09.2020

Block 1: Montag, 24.08.20 bis Freitag, 28.08.20 jeweils von 9-17 Uhr

Block 2: Donnerstag,17.09.20 und Freitag 18.09.20 von 9-17 Uhr, Samstag 19.09.20 von 9-12:30 Uhr.

Marcus Kuhn, Schulforschung / Bildungswissenschaften, Fakultät Erziehungswissenschaften und Psychologie, Freie Universität Berlin


  • Gegenstand, Problemstellungen und Grundlagen der Gesundheitspädagogik
  • Grundbegriffe und Grundfragen der Erziehungswissenschaften; Einblicke in die Erziehungs- bzw. Bildungswissenschaften als Wissenschaftsdisziplin in ihrer historischen Entwicklung, ihren wissenschaftstheoretischen Ansätzen sowie ihren zentralen Forschungsfeldern
  • Überblick über die pädagogischen Grundbegriffe Lernen, Entwicklung, Erziehung, Bildung und Sozialisation
  • Überblick über die Handlungsfelder und Adressatengruppen pädagogischen Handelns mit besonderem Fokus auf die Praxis der Gesundheitsprofessionen
  • Edukative Interventionsstrategien der Gesundheitswissenschaften (Information, Aufklärung, Beratung, Anleitung)
  • Konzeption, Implementierung und Evaluation gesundheitspädagogischer Maßnahmen in diversen Settings, mit verschiedenen Zielgruppen und unterschiedlicher Reichweite

Interessenten für den Masterstudiengang Health Professions Education

850 €

Referat mit schriftlicher Ausarbeitung


Bitte nutzen Sie das Anmeldeformular oder senden eine E-mail an Tanja Te Gude

Tel. +49 30 450 570 812

Flyer: Flyer mit detailliertem Programm

Tobias Kurth / Kristina Fišter: How to publish a research paper in a major biomedical journal, September 15 - 18, 2020 in Zagreb

University of Zagreb – School of Medicine, Andrija Štampar School of Public Health and CharitéUniversitätsmedizin Berlin, Institute of Public Health in affiliation with the Berlin School of Public Health are organising a postgraduate continuing medical education course: "How to publish a research paper in a major biomedical journal".

Date: September 15 - 18, 2020

Tobias Kurth (MD, ScD), Professor, Director of the Institute of Public Health, Charité - Universitätsmedizin Berlin
Kristina Fišter (MD, MSc, DSc), Assistant Professor, Andrija Štampar School of Public Health, University of Zagreb,
Editors of the British Medical Journal (BMJ) and Canadian Medical Association Journal (CMAJ)

About the Short Course

Publishing visibly is closely linked with success in obtaining grants, yet competition for space is fierce, particularly in major biomedical journals. As research methods evolve and the publishing landscape changes, continuing education in knowledge and skills needed to produce quality research articles is necessary. This is all the more relevant as capacity is strengthened for health data sciences and decisions are increasingly made based on solid evidence.

Participants will gain knowledge and develop multiple skills needed to produce a high-quality research paper. This includes posing an important and relevant research question, searching biomedical literature, choosing an appropriate study design, writing a research protocol, using electronic data capture solutions, conducting data analysis using the statistical program R and interface RStudio, critically interpreting the findings, and approptiate referencing of previous work. From methods to manuscript, participants will develop the necessary skills to successfully produce a manuscript suitable for submission to a top biomedical journal.

The course is designed for medical doctors, studants and graduates of biomedical and health disciplines.


Zagreb, Croatia




3 ECTS points

To Apply

For more information and to apply for the course please email or visit

Course Fees

400 €, 300 € for students.


E-mail: publish(at)


CANCELLED Merrick Zwarenstein / Lars Hemkens: Designing pragmatic trials for real world evidence, September 23 – 25, 2020

Designing pragmatic trials for real world evidence


40 Seats

Date: Sept. 23 - 25, 2020

Pre-requisits: Intention to conduct a randomized trial to inform medical decisions under real world conditions soon, or at some time in your future career.
Introductory level epidemiology and statistics. This is a masters level / postgraduate course.

Course description: There is an increasing interest in providing real world evidence for health care decision-making. Randomized trials often have characteristics that make them not useful to guide such decisions. There are two approaches to design of randomized trials that can help to solve such problems and provide more useful trials. They were first described by Joseph Schwartz and Daniel Lellouch, two French statisticians who wrote a seminal paper in 1967: Pragmatic trials are aimed at informing a health care decision, namely which of several treatment options to choose in a real world situation, while explanatory trials are more like laboratory experiments, testing whether or not a particular mechanism of action is responsible for a change in outcome.

While we take the perspective of those who design trials, the course will also be helpful for those who use randomized trials for example in systematic reviews, health technology assessment, regulatory or funding decisions. Exposure to basic theory or practice of randomized trial design is required, e.g. from an introductory epidemiology course or through participation as a coinvestigator in a completed, not necessarily pragmatic randomized trial.
With full engagement, those who bring a prepared research question to the course can expect to produce a well-considered 2 page outline proposal for a pragmatic randomized trial, which could become the basis for writing a full submission for funding. For participants who do not have a specific intervention in mind, you will join a group with others who do, and apply your learning to their proposed intervention, or work on example projects provided by the lecturers.

The course will last 3 full days (from 9 am to 5 pm). To get the most out of it, preparation before and during the 3 days will be beneficial. The format for each session contains a didactic lecture on pragmatic attitudes and real world evidence, with plenary questions and discussion, followed by small group meetings, in which each group writes that section of their own protocol, followed by plenary discussion of a couple of groups’ written protocol sections. Over the 3 days everyone attending will present sections of their groups protocol and take part in plenary discussions of theirs and others protocols.

Learning objectives:

This course introduces participants to design such trials, focusing on the pragmatic approach and trials aiming to support decision-making in the real world. It will consider emerging technologies and routinely collected data that are increasingly shaping the future of randomized trial evidence generation. The course is intensive, experiential, and intended for individuals or small teams who are interested in real world evidence. 
Do you have a conviction that a particular therapy or intervention would benefit patients, communities or healthcare delivery, and the open-mindedness to want to know if your conviction was valid under real world conditions? If yes, you can learn how to design a randomized trial that evaluates your conviction.
The randomized trial you have in mind may be of  a drug, a surgical or other clinical procedure, a digital health app, a medical technology, a change in how one or other health care service is delivered. Alternatively, you may not know what kind of intervention you will one day want to evaluate, but you urgently want to learn how to evaluate interventions under real world conditions in randomized trials.  

Pre-Course readings: Info to come

Course Information:

  • Course language: English
  • ECTS points: 2,5
    The completion of an assignment after the course is mandatory for the award of ECTS credits. The assignment will be the development of a draft outline proposal, either on an own project idea or based on an example case.
  • Course Fee: € 625, € 425 for students (proof required)

Please use the registration form or send an e-mail to Tanja te Gude


  • Merrick Zwarenstein, MBBCh, MSc, PhD is an internationally-recognised primary care and health services researcher, who received his PhD in Epidemiology at the Karolinska Institute (Sweden), an MSc in Community Health at the London School of Hygiene (UK), and an MScMed in Microbiology and a medical degree (MBBCh) from the Witwatersrand University Medical School (South Africa). He is a full Professor in the Centre for Studies in Family Medicine, at the University of Western Ontario in Canada and a senior scientist in IC/ES, the research organization using Ontario’s electronic administrative data sets on health and health care for policy and clinically relevant analyses. He holds honorary positions at the Universities of Cape Town and Stellenbosch in South Africa, and the Karolinksa Institute in Sweden. He has led international research consortia focussing on overcoming limitations with the use of randomised trials in support of policy decision making.
  • Lars G. Hemkens, MD, MPH is Senior Scientist and Deputy Director of the Basel Institute for Clinical Epidemiology and Biostatistics (ceb), Department of Clinical Research, University Hospital Basel. His key interest is to inform health care decision-making and includes answering health care questions with data that were not made for answering those questions. His work focuses on routinely collected data and big data, pragmatic trials and real world evidence, and meta-research. He co-designed various clinical studies in a wide range of medical fields. He is board member of the Network for Evidence Based Medicine, associate editor of Trials, sits in the editorial board of BMJ Evidence-Based Medicine and in the working committee of the RECORD reporting guideline group. He is QUEST visiting fellow at the Berlin Institute of Health and coordinator of the RCD for RCT initiative, which aims to explore the use of routinely collected data for clinical trials.

Anmeldung Intensive Short Courses

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