Summer School Pharmaco-epidemiology
What is the aim of the course?
Large longitudinal healthcare databases have become important tools for studying the clinical effectiveness of medical products and interventions in a wide variety of care settings and for evaluating the impact of clinical programs or policy changes. This course will prepare students to design, implement, execute and discuss studies on causal treatment effects using healthcare databases. Strengths and limitations of large longitudinal healthcare databases that are commonly used for comparative effectiveness research will be considered.
Who ist the course targeted at?
The course is targeting trainees/investigators who recently started analyzing longitudinal healthcare data or are planning to do so. We specifically focus on comparative effectiveness research and will not cover data visualization, descriptive analyses or prediction. The course centers around student projects of an analyses of some medical product outcome pair and we therefore expect working knowledge of epidemiology study designs for causal inference and the typical statistical analysis methods in non-randomized settings. The software package is in its logic, terminology, and workflows aligned with our didactics of teaching causal study design concepts and we assume that most students will use a variety of software products after completing the course.
Where and when does the course take place? How much does it cost?
The course is a five day intensive full time course and will take place in Munich (in presence) from June 26-30. The course fee is 250 EUR per participant.
Which preliminary skills are required?
The course does not require specific programing skills. It is focused on analytic principles and their application to database research rather than mathematical details. It requires an understanding of epidemiologic study designs and typical analysis strategies.
What will I learn and how?
The centerpiece of the course is a student project resulting in a pilot analysis and a study protocol. Each morning includes lectures with discussions. In the afternoons students will convene in the Evidence Lab with faculty and teaching assistants to work in small groups with a large longitudinal claims database of 31 million commercially insured patients in the US and with an easy-to-use statistical software to develop inclusion and exclusion criteria, compare population descriptives, implement follow-up models and risk-adjustment methodologies resulting in multivariate adjusted effect estimates. Practical issues in obtaining, linking, and analyzing large databases will be emphasized throughout the course, and key analytic issues will be addressed, including design considerations and multivariate risk-adjustment. Bring your laptop with the Chrome browser installed.
What will I get out of this?
Upon completion, students will receive a certificate and those enrolled in an LMU graduate degree program will receive 3 ECTs
How can I enrol?
If you are interested in taking part, please send an email to email@example.com. Please, note that the number of participants is limited to 30.
Zur Zeit keine Meldungen in diesem Bereich.