Biostatistics, Information and Decision in Health II

Code:

MI329

Acronym:

BIOINFDS_II

Keywords
Classification	Keyword
OFICIAL	Medicine

Instance: 2018/2019 - 2S (of 11-02-2019 to 12-07-2019)

Active?	Yes
Responsible unit:	Department of Community Medicine, Information and Health Decision Sciences
Course/CS Responsible:	Integrated Master in Medicine

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIMED	288	Mestrado Integrado em Medicina- Plano oficial 2013 (Reforma Curricular)	3	-	3	30	81

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%). Only the theoretical exam component is allowed to be resat.

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
Participação presencial	10,00
Teste	10,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	51,00
Frequência das aulas	30,00
Total:	81,00

Eligibility for exams

Presence in 75% of the classes

Calculation formula of final grade

Evaluation will result from a theoretical test (80%) and practical evaluation (20%). The practical evaluation consists of tests at the end of each session (10%) and a global evaluation based on the student's participation during classes (10%).

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)