ECTS - Decision Support in Health Informatics

Decision Support in Health Informatics (SE546) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Decision Support in Health Informatics SE546 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Natural & Applied Sciences Master's Degree
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives The objective of this course is to familiarize students with different types of healthcare data, assure the quality of the data and how to understand and communicate the information provided in support to effective decision making by various stakeholders of the healthcare system.
Course Learning Outcomes The students who succeeded in this course;
Course Content Choosing the correct information for different decisions and communicate its meanings to users; evaluation of statistical and other methods and tools; the difference between research databases and operational databases; techniques to effectively communicate quantitative healthcare data using tables and graphs; methods for choosing the right medium.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to Information Systems Overview of Decision Support System Reading will be provided
2 Decision Theory and Decision Making Reading will be provided
3 Decision Support in Medical Informatics Course-Book. Chapter 1
4 Decision Analysis Course-Book. Chapter 2
5 Medical Decision Support Requirements and Areas Course-Book. Chapters 4-5
6 Medical Decision Support Requirements and Areas Course-Book. Chapter 6
7 Bioinformatics Problems Reading will be provided
8 Bioinformatics Problems Reading will be provided
9 Analysis Approaches for Bioinformatics Problems Reading will be provided
10 Analysis Approaches for Bioinformatics Problems Reading will be provided
11 Visualization Reading will be provided
12 Visualization Reading will be provided
13 Case Study-1 Course-Book. Chapters 8
14 Case Study-2 Reading will be provided
15 General Exams
16 General Exams

Sources

Course Book 1. Berner, E.E. (ed.) (2007). Clinical decision support systems: Theory and practice, New York, Springer, Heath Informatics Series.
Other Sources 2. Osteroff, J.A., Pifer, E.A., Teich, J.M., Sitting, D.F., & Jenders, R.A. (2005). Improving outcomes with clinical decision support: an implementer’s guide: Chicago, IL: HIMSS.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury - -
Final Exam/Final Jury - -
Toplam 0 0
Percentage of Semester Work
Percentage of Final Work 100
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Ability to apply knowledge on Mathematics, Science and Engineering to advanced systems.
2 Implementing long-term research and development studies in the major fields of Electrical and Electronics Engineering.
3 Ability to use modern engineering tools, techniques and facilities in design and other engineering applications. X
4 Graduating researchers active on innovation and entrepreneurship.
5 Ability to report and present research results effectively.
6 Increasing the performance on accessing information resources and on following recent developments in science and technology.
7 An understanding of professional and ethical responsibility.
8 Increasing the performance on effective communications in both Turkish and English.
9 Increasing the performance on project management.
10 Ability to work successfully at project teams in interdisciplinary fields. X

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 1 16
Presentation/Seminar Prepration
Project 1 6 6
Report
Homework Assignments 3 5 15
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 30 30
Total Workload 125