DECIDES III: Decision, Data and Digital Health

Code:

MI444

Acronym:

DECIDES3

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	124	Plano Oficial 2021	4	-	4	38	108

Teaching language

Portuguese

Objectives

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

• Model data relations;
• Know the most adequate methods to integrate different data sources;
• Understand the main diagnosis and procedures classification systems;
• Efficiently use health information systems;
• Respect the safety and privacy practices of health information systems;
• Operate the most frequently used health information systems;
• Know the main paradigms of digital health;
• Know the organization of the Portuguese healthcare system;
• Understand how scientific evidence can be integrated in the process of decision making;
• Represent in formal and adequate ways the process of decision making in health care;
• Manage and integrate the fundamental components of any decision-making process in healthcare:  (i) the best scientific evidence, (ii) patients’ characteristics, perspectives and values, (iii) clinical experience and (iv) the costs and economic impact of the alternatives;
• Explore uncertainties in the process of health decision making.

Learning outcomes and competences

At the end of this curricular unit the students are expected to: (i) know and discuss the main topics underlying health information systems, and integration of scientific evidence in health decision making; (ii) efficiently and safely use health information systems; (iii) critically assess health scientific literature, namely regarding health information systems, health technology assessment, and health decision analysis; and (iv) plan and interpret health economic evaluation studies and decision analyses.

Working method

Presencial

Program

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.

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

• Conceptual representation of information systems;
• Coding and classification stystems;
• Electronic health records;
• Data storage in health;
• Security, privacy and quality of information in health;
• Digital health and mobile devices;
• Artificial intelligence in health;
• Organization of the Portuguese healthcare system;
• Elements of decision making in healthcare, particularly in the context of evidence based practice;
• Representation of the decision process using models;
• Searching for and critically appraise scientific evidence regarding the effectiveness and safety of healthcare technologies;
• Searching for and critically appraise scientific evidence regarding diagnostic and prognostic technologies in healthcare;
• Integration of patients’ perspectives in health decision making;
• Integration of economic information in health decision making;
• Management and assessment of uncertainties in decision making;
• The role for clinical decision-making of health data science and clinical decision support systems

The syllabus includes all necessary and sufficient basic skills needed to (i) efficiently and safely use health information systems, (ii) understand and critically assess a health research project, namely on health information systems, health technology assessment, and health decision analysis, and (ii) participate in the planning of research projects, namely of health economic evaluation studies and decision analyses.

Mandatory literature

Shortliffe EH, Cimino JJ; Biomedical Informatics: Computer Applications in Health Care and Biomedicine
Michelle A. Green, Mary Jo Bowie; Essentials of Health Information Management: Principles and Practices
Hristidis V; Information Discovery on Electronic Health Records
Cruz-Correia RJ et al.; Data Quality and Integration Issues in Electronic Health Records
Niels Peek & Pedro Pereira Rodrigues; Three controversies in health data science
Straus SE, Glasziou P, Richardson WS, & Haynes RB; Evidence-Based Medicine: How to Practice and Teach It
Hunink MGM, Glasziou, P, Siegel, J, Weeks, J, Pliskin. J, Elstein, A & Weinstein, M; Decision making in health and medicine: integrating evidence and values
Welton NJ, Sutton AJ, Cooper NJ, Abrams KR, Ades AE; Evidence Synthesis for Decision Making in Healthcare
Athanasiou T, Darzi A. ; Evidence Synthesis in Healthcare: A Practical Handbook for Clinicians
Drummond, M.F., Sculpher, M.J., Claxton, K., Stoddart, G.L., & Torrance, G.W. ; Methods for the economic evaluation of health care programmes

Teaching methods and learning activities

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 – 35% –, involving:
  • Students’ participation in the classroom – 5%;
  • Practical exercises, which may include preparation and presentation of research protocols and/or scientific papers – 30%.
• Final examination – 65%

The teaching methodologies include theoretical and practical sessions. These will allow us to manage a logical progression of the student from the concepts to the methods and their implementation and from the more basic to the more complex concepts and methods. This will allow us to maximize the probability of success regarding the learning aims and expected outcomes.

Software

Moodle
SClinico
Microsoft Office
Google Drive (Docs & Drawing)
SPSS
Microsoft Teams
Diagrams.net
ObsCare - Registo Clínicos de Obstetricia
Servidor de BDs MariaDB e ambiente administração

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Participação presencial	5,00
Apresentação/discussão de um trabalho científico	30,00
Exame	65,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Apresentação/discussão de um trabalho científico	10,00
Estudo autónomo	30,00
Frequência das aulas	38,00
Trabalho de campo	10,00
Trabalho de investigação	20,00
Total:	108,00

Eligibility for exams

Participation in at least 3/4 of practical lessons.

Calculation formula of final grade

Final grade = exam * 0.65 + student's participation * 0.05 + practical exercises * 0.30

To pass this subject, students must at least be classified with 10 marks both in the continuous assessment (student's participation + practical exercises) and in the final examination.

Special assessment (TE, DA, ...)

Working students can, if they will, be evaluated at once for their distributed assignments, 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.

Classification improvement

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