Conducting Observational Studies in Contemporary Practice: Modern Technologies and Biostatistical Methods
Dates: 7-16 July 2026
Format: Intensive internship programme with guided follow-up assignment
Workload: 48 contact hours + 12 follow-up hours
Credits: 2 ECTS equivalent

Observational studies play an increasingly important role in modern clinical research, especially in settings where real-world data, digital tools, and structured analytics are essential for generating relevant evidence. This intensive training programme is designed for clinicians, academic faculty, and healthcare researchers who want to strengthen their practical understanding of contemporary observational study design, digital data collection, data quality management, and modern biostatistical analysis.

The programme reflects Midaia’s broader approach to clinical research: combining digital infrastructure, real-world clinical data, and robust analytics to support high-quality observational research in contemporary healthcare.

Programme Goal

To familiarise participants with current principles for conducting observational studies and analysing data using digital tools, real-world clinical data, and modern biostatistical methods.

Who Should Attend

Clinicians, academic staff, and researchers working in healthcare and clinical research.

What Participants Will Gain

1. A practical understanding of contemporary observational study designs, protocol development, endpoint selection, and data quality requirements.
2. Insight into the use of modern digital technologies for data collection, monitoring, validation, and structuring of clinical information.
3. Experience in preparing analytical datasets and selecting appropriate biostatistical methods for real-world clinical data.
4. A stronger understanding of confounding, bias, missing data, and current approaches to their control and interpretation.
5. Opportunities for future scientific and academic collaboration in the field of observational research and data analysis.

Programme Structure

7 July 2026
Introduction to the programme structure and expected learning outcomes. The role of observational studies in modern clinical medicine and real-world evidence generation, with a focus on major real-world data sources, data fitness for purpose, and development of clinically relevant research questions grounded in available data.

8 July 2026
The place of observational studies in modern clinical medicine and real-world research, including major study types, data sources, and common design pitfalls.

9 July 2026
Protocol planning, endpoint definition, inclusion and exclusion criteria, and key ethical, regulatory, and organisational considerations.

10 July 2026
Modern digital technologies for data collection, including electronic questionnaires, mobile applications, ePROs, remote monitoring, data structuring, and quality control.

13 July 2026
Modern biostatistical methods for observational studies, with a focus on confounding, bias, missing data, and correct interpretation of findings.

14 July 2026
Practical case-based review of data analysis using modern technologies and biostatistical methods, including data visualisation, conclusion building, and preparation of results for presentation.

15 July 2026
Applied aspects of using real-world clinical data and the integration of research and clinical approaches in contemporary healthcare.

16 July 2026
Final discussion of programme outcomes, future collaboration opportunities, and certificate awarding.

Guided Follow-up Assignment

To consolidate learning outcomes and support the full 2 ECTS workload, participants will complete a guided follow-up assignment after the live programme. This component is designed to extend the training beyond contact hours and translate concepts into practical application. The follow-up task may include:

1. Drafting a concise concept note for an observational study or real-world data project.
2. Defining a preliminary study question, target population, endpoints, and key variables.
3. Identifying likely sources of bias, confounding, and missing data.
4. Preparing a short analytical reflection on appropriate digital tools and biostatistical methods for the proposed project.

Estimated follow-up workload: 12 hours.

Workload and Credits

Contact hours: 48
Guided follow-up work: 12 hours
Total workload: 60 hours
Credits: 2 ECTS equivalent