DECIDES I: Decision, Data and Statistics in Health

Code:

MI235

Acronym:

DECIDES1

Keywords
Classification	Keyword
OFICIAL	Medicine

Instance: 2022/2023 - 1S

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	259	Plano Oficial 2021	2	-	4	38	108

Teaching language

Portuguese

Objectives

Decision making in healthcare should be informed by high quality scientific evidence, based on data obtained, stored, analysed and interpreted according to the most appropriate methodological, statistical and computational practices. This curricular unit aims to present the continuous process that begins with the formulation of the research question and, using the most adequate methodological and computational practices, allows for the collection and storage of high-quality data, which after adequate analysis and interpretation result in properly informed decision-making. DECIDES curricular units aim to provide the knowledge and skills so that students can be able to participate in the:

• Analysis, synthesis and discussion of scientific evidence, applying it to the process of decision making in healthcare;
• Planning and development of a research project;
• Retrieval, management and analysis of health data.

Learning outcomes and competences

After completing this curricular unit, Students should be able to:

• Structure a research question, with emphasis in the clinical and health services research areas;
• Search and manage scientific literature;
• Collect, classify, manage and process data in a rectangular database for statistical analysis;
• Know the fundamental principles underlying statistical inference and statistical modelling;
• Statistically analyse health data (namely by estimating confidence intervals, applying hypothesis tests, and building simple linear regression models) and interpret the respective results;
• Use adequate software to apply and interpret different statistical methodologies;
• Understand the advantages and limitations of using secondary data for health research;
• Draft a research protocol.

 

Working method

Presencial

Program

At the end of this curricular unit, students are expected to: (i)know and apply basic principles and methods in biostatistics, including descriptive and inferential statistics, and develop basic skills to support the statistical analysis of health data; (ii) know and discuss the main topics underlying the planning and development of a research project; (iii) participate in the planning of a research project, namely in what concerns the formulation of the research question, the definition of the study design, and the selection of the most appropriate methods for data management and analysis; and (iv) critically assess health scientific literature, namely regarding the underlying research question, study design, and statistical methods.

In particular, the following content will be covered in this curricular unit:

• Structuring a research question, with emphasis in the clinical and health services research areas;
• Planning and executing a bibliographic search;
• Introduction to biostatistics;
• Definition of variables;
• Methods and tools for data collection. Database creation;
• Use of secondary data in health research;
• Descriptive statistics;
• Probability distributions;
• Sampling and methods for participants’ selection;
• Inferential statistics: Confidence intervals and hypothesis tests;
• Methods for analysing categorical and continuous variables;
• Sample size calculation;
• Correlation;
• Simple linear regression;
• Draft of a research protocol.

Mandatory literature

Petrie A, Sabin C. ; Medical Statistics at a Glance, 3rd edition , Blackwell Science Inc
Bland JM. ; An Introduction to Medical Statistics 4th Revised ed. Edition , Oxford Medical Publications
Shortliffe EH, Cimino JJ; Biomedical Informatics: Computer Applications in Health Care and Biomedicine 4th ed, Edition Springer
Michelle A. Green, Mary Jo Bowie. ; Essentials of Health Information Management: Principles and Practices 3rd Edition, Cengage Learning
Cruz-Correia RJ et al; 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), Hristidis V (ed.); , 2009

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. 

This curricular unit will encompass lectures and discussion sessions. The latter will involve individual and group exercises concerning practical problems in healthcare scenarios.

The evaluation will have the following components:

• Continuous assessment, involving students’ participation in the classroom and practical exercises, which may include preparation and presentation of research protocols and/or scientific papers
• Final examination 

To pass this subject, students must at least be classified with 10 marks both in the continuous assessment and in the final examination.

Software

IBM SPSS statistics

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	65,00
Participação presencial	5,00
Trabalho prático ou de projeto	30,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	60,00
Frequência das aulas	38,00
Trabalho escrito	10,00
Total:	108,00

Eligibility for exams

In accordance with the rules approved by FMUP: 75% of the classes.

Calculation formula of final grade

The evaluation will have the following components:

• Continuous assessment (AD) – 35% –, involving:
• Students’ participation in the classroom – 5%
• Practical exercises, as well as the preparation and presentation of research protocols and/or scientific papers – 30%
• Final examination (E) – 65%

To pass this subject, students must at least be classified with 10 marks both in the continuous assessment and in the final examination.

Final grade = (AD * 35 + E * 65) / 100

Examinations or Special Assignments

There is no special assignments.

Internship work/project

Not applicable

 

 

 

Special assessment (TE, DA, ...)

Working students can, if they will, be evaluated at once for their distributed assignments (AD), on a date to be scheduled by the end of the semester, with the weight of student's participation to be redistributed by the remaining evaluation pieces of the distributed evaluation. If this is the case, they have to communicate it to the Curricular Unit's regency, by e-mail, up to the end of October.

Classification improvement

Only the final exam might be subject to a reassessment towards mark improvement.

Observations

The teaching and assessment methods may have to be altered if there are significant changes in the epidemiological status.