Biostatistics, Information and Decision in Health II
Keywords |
Classification |
Keyword |
OFICIAL |
Medicine |
Instance: 2017/2018 - 2S
Cycles of Study/Courses
Teaching language
Suitable for English-speaking students
Objectives
To develop knowledge on biostatistics, information and critical appraisal of medical evidence and to develop skills to integrate the best evidence in the health care decision making process.
Learning outcomes and competences
The learner should:
1) conceptualize the knowledge search process guided by a clear research question in health care
2) learn the need to qualify available biomedical research in terms of adequacy and validity
3) enclose the concept of integration in clinical practice according to patient's values and clinician's experience
4) be familiar with evidence formalization processes, used during their own decision process in everyday clinical practice
5) understand the existence of other perspectives in decision in health care
Working method
Presencial
Program
• Decision in health: in technology evaluation, health service research and clinical research;
• Stepwise approach to decision in health – evidence based medicine:
• Critical analysis of studies for specific clinical questions:
• Synthesis of evidence – systematic reviews and meta-analysis studies;
• Results valuing methodologies – preferences, utilities and QALY's;
• Economic evaluation and measurement of costs in health;
• Basics of decision analysis:
◦ structuring and analysis of the decision process;
◦ construction and interpretation of decision trees;
◦ uncertainty management, threshold analysis, sensitivity analysis and modeling;
• Decisionsupportsystems:
◦ formalization of decision algorithms after clinical guidelines;
◦ decision trees and probabilistic graphical models;
◦ knowledge discovery from health data;
◦ decision support systems based on clinical guidelines and meta-analysis;
◦ evaluation of clinical decision support systems
Mandatory literature
M. G. Myriam Hunink, Paul P. Glasziou, Joanna E. Siegel, Jane C. Weeks, Joseph S. Pliskin, Arthur S. Elstein, Milton C. Weinstein; Decision Making in Health and Medicine: Integrating Evidence and Values, Cambridge University Press, 2001
Michael F. Drummond, Bernard J. O'Brien, Greg L. Stoddart, George W. Torrance; Methods for the Economic Evaluation of Health Care Programs, Oxford University Press, 1997
Marthe R. Gold, Joanna E. Siegel, Louise B. Russell, Milton C. Weinstein; Cost-Effectiveness in Health and Medicine, Oxford University Press, 1996
Dinis-Ribeiro M; Relatório Pedagógico relativo ao ensino de uma unidade curricular de “Evidência na Decisão”. Provas de Agregação, Faculdade de Medicina da Universidade do Porto, 2009
Sackett DL et al; Evidence-Based Medicine: how to practice and teach EBM, Churchill Livingstone, 2000
Berner E.; Clinical decision support systems: theory and practice, Springer Verlag, 2006
Teaching methods and learning activities
Overall, after theoretical exposition of each topic, groups will be formed to perform practical exercises, along with individual exercises, using an e-learning platform. Furthermore, software for decision analysis and decision support will be made available in practical lessons.
Theoretical (12 hours) and theoretical-practical (18 hours) lessons with presentation and discussion of different topics, group and individual exercises with manuscripts critical appraisal and software outputs adequate interpretation.
Evaluation will result from a theoretical exam (80%) and distributed practical evaluation (20%).
The exam consists of multiple choice questions with simple answers, short answer questions and short development questions. The use of a calculator or any other electronic device is not permitted. The exam will last for a maximum of 90 minutes.
keywords
Physical sciences > Mathematics > Statistics
Evaluation Type
Distributed evaluation with final exam
Assessment Components
Designation |
Weight (%) |
Exame |
80,00 |
Teste |
20,00 |
Total: |
100,00 |
Calculation formula of final grade
Evaluation will result from a theoretical test (80%) and practical evaluation (20%).
Observations
Aproval is restricted to students who manage to get a positive mark (greater or equal to 9.5 out of 20) in each of the evaluation components (exam and distributed scoring)