Biostatistics, Information and Decision in Health I

Code:

MI112

Acronym:

BIDS

Keywords
Classification	Keyword
OFICIAL	Medicine

Instance: 2013/2014 - 1S

Active?	Yes
Responsible unit:	Department of Health Information and Decision Sciences Department
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	258	Mestrado Integrado em Medicina- Plano oficial 2013 (Reforma Curricular)	1	-	6	54	162

Modules

Code	Name
MI112_B
MI112_A

Teaching language

Suitable for English-speaking students

Objectives

Information and decision sciences are, traditionally, supported by two great scientific areas, Biostatistics and Medical Informatics, and so it is expected that the students:

• Acquire notions and training on probability and distributions, descriptive statistics Statistical inference and modelling, sample size;

 

• Learn the concepts and applications of information systems (IS) in healthcare, Data coding and classification systems, Electronic clinical records, decision support systems, processing of biological signal and image, telemedicine and eHealth;

 

• Acquire skills on data preparation, construction of probability plots, Bibliographic and modeling search and reference management, creation of databases  and queries to databases;

 

• Understand the organization of health information as applied to statistical analysis and health research.

 

Learning outcomes and competences

This unit aim to empower the students with the following skills:

• classify, store and process data for statistical analysis;
• apply descriptive and inferential statistical technics;
• interpret statistical modeling and inferential results;
• search and manage of scientific literature;
• model and integrate data and information;
• use information systems in a safe and efficient way;
• structure and implement algorithms and medical guidelines;

 

After this course unit the students should also develop the adequate skills in order to apply and correctly interpret the studied statistical and informatics methodologies using the appropriate software.

Working method

Presencial

Program

Introduction to biostatistics; introduction to probability and distributions.

Descriptive statistics; data preparation; probability graphical models.

Statistical inference and modelling: confidence intervals; hypothesis testing – parametric and non-parametric; categorical data analysis; correlation; linear regression.

Power analysis and sample size.

Introduction to advanced methods for data analysis and modeling.

Application of statistical analysis to biomedical research.

Bibliographic search and reference management.

Information systems (IS) in healthcare.

Data coding and classification systems.

Electronic clinical records.

Data modeling, creation of databases  and queries to databases.

Standardization of data communication, processing of biological signal and image; eHealth and telemedicine.

Basic principles of decision support systems

Organization of information in health: guidelines and algorithms in healthcare.

Mandatory literature

Petrie A, Sabin C.; Statistics at a Glance, Blackwell Science Inc, 2005
Bland JM; An Introduction to Medical Statistics, Oxford Medical Publications, 2000
Shortliffe EH, Cimino JJ.; Biomedical Informatics: Computer Applications in Health Care and Biomedicine, Springer, 2006
Michelle A. Green, Mary Jo Bowie; Essentials of Health Information Management: Principles and Practices Michelle , Cengage Learning, 2010
Hristidis V (ed.); Information Discovery on Electronic Health Records, Chapman and Hall, 2009 (Cruz-Correia RJ et al. Data Quality and Integration Issues in Electronic Health Records. p.55-95)

Teaching methods and learning activities

Theoretical lectures, seminars and practical lessons, with topic discussion (including examples in health), individual and group exercises, and hands-on training on medical scenarios, with proper software. 

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	70,00
Participação presencial	10,00
Teste	20,00
Total:	100,00

Calculation formula of final grade

Evaluation will be based on individual and group assignments (20%), teacher assessment (10%), and a final exam (70%).

Internship work/project

Not applicable