• Start date:
  • 14 May 2018
  • Duration:
  • 5 days
  • Working as:
  • General practitioner, Medical specialist, Trainer, Student

Accreditations

  • ABAN:
  • 24

Diagnostic and prognostic models are increasingly published in the medical literature each year. But are the results relevant for decision making in practice? How can models be used for risk stratification in populations? What are the critical elements of a well-developed diagnostic or prognostic model? How can we assume that the model makes accurate predictions for our population, and not only for the sample that was used to develop the model (generalizability, or external validity)? Are big data and advanced statistical techniques the solution for the problem of poor generalizability?

In the course we will address these and other questions from an epidemiological, statistical and decision-making perspective, using examples from the clinical literature. The participants will be encouraged to participate in interactive discussions and in practical computer exercises, starting with basic approaches and extending to advanced modeling.

Objectives

  • Increasing the knowledge of the roles that diagnostic and prognostic models may play in medical decision-making and the critical factors that determine the validity of predictions from such a prediction model.

  • Gain insight in the pitfalls in model development with standard statistical techniques.

Acquire both theoretical and practical knowledge on advanced methods in model development and validation, specifically on regression modelling.

Target group

The partners of the LUMC-Campus The Hague offer the course PHM for

  • health care professionals,

  • staff members

  • PhD fellows in Health and Healthcare related science,

  • MD specialist trainees in primary, elderly and secondary care and Public Health and

  • master students

that:

  • Want to become change agents to support the development of a more integrated health care system.
  • Have an open attitude towards a new paradigm for health care.

Draft program

Dag 1: Screening & diagnosis (David)

Dag 2: Prognosis & prediction (David)

Dag 3: Dynamic prediction in survival (Marta)

Dag 4: Prognosis & Prediction (David)

Dag 5: Advanced statistical modelling, predictive analytics, big data (David/Ross/Henrik/Alex)

Cost-effectiveness already in week 2 for this year

,
Health care professional € 1.250,00  
PhD (candidate) € 625,00  
Student for free