Postgraduate taught 

Health Technology Assessment MSc/PgDip/PgCert: Online distance learning

Survival analysis for Health Technology Assessment (Online) MED5380

  • Academic Session: 2021-22
  • School: Health and Wellbeing
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: Yes
  • Available to Erasmus Students: Yes
  • Taught Wholly by Distance Learning: Yes

Short Description

This course will demonstrate how survival / time to event data is used to inform health economic analyses within health technology assessments

Timetable

5 week online course comprising 5 lectures and 5 accompanying practical exercises. The lectures will be 45 mins/1 hr in duration and the exercise associated with each lecture will take a notional 2 hours for the student to complete. Each week the academic lead will contribute to and answer questions on a discussion board.

Requirements of Entry

None

Excluded Courses

None

Co-requisites

None

Assessment

Written Assignment/Coursework - Students will be given data sets and a series of research questions, which they will need to answer by applying methods from the course and write up as a report (1000 words).

Course Aims

This course aims to equip students with the necessary statistical skills so they can analyse and interpret survival data that are commonly used in health economic analyses within health technology assessments.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ Create, interpret and critically assess the ouput from the Kaplan-Meier method (descriptive statistics and survival graphs).

■ Create, interpret and critically assess the ouput from Cox regression (survival graphs, hazard graphs, hazard ratios).

■ Create, interpret and critically assess the ouput from parametric survival models (survival graphs, hazard graphs, hazard ratios).

■ Critically discuss how parametric survival models can be used for extrapolating (and therefore obtain unrestricted life expectancy estimates) and partitioning survival curves.

■ Evaluate how outputs from survival models can be used as inputs in Markov models, discrete event simulations and cumulative incidence implementations.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.