Elective Course At least 5 courses, including course that you have taken
Common practices in health services, operation in the clinical setting, quality of health care organization, clinical process and judgment; terminologies commonly used in public health field, health practices, and medical diagnosis
Objectives of the subject are
Know the objectives of using the medical terminology
Decoding the medical terms by using root , prefix, suffix and conjugation
Develop skill to memorize and grouping words by many methods e.g. organ oriented groups, disease orientated groups, Eponyms.
Know the meanings and how to use the public health related words as well as the standard medical terminology abbreviations properly.
LO: Learning Outcome
LO1: Know the objectives of using the medical terminology.
LO2: Decode the medical terms by using root , prefix, suffix and conjugation.
LO3: Develop skill to memorize and grouping words by many methods e.g organ oriented groups, disease orientated groups, Eponyms.
LO4: Know the meanings and how to use the public health related words as well as the standard medical terminology abbreviations.
Overview of computer architecture, data organization, structure of programming languages, networking and data communication
LO: Learning Outcome
LO1: Explain tools and terminologies related to the public health informatics
LO2: Apply public health informatics principles, tools, methodologies to improve public health practices
LO3: Discuss the role of information system in public health practices
LO4: Identify key characteristics of decision support system
LO5: Discuss the impact of developments in Electronic Medical Records, e-health, and m-health technologies for improving population health
LO6: Analyze challenges in the development of public health information system, and their solutions
Principles of good data management, case record form design, data management process, data management tool; data validation techniques
1. Describe principles of good data management practices
2. Design appropriate case record form for effective data collection
3. Discuss data management processes in clinical research
4. Apply appropriate data management tools to assist clinical data management
5. Use data validation and data handling techniques to appropriately prepare data for analysis
Disease mapping of tropical diseases by Geographical Information System (GIS), Remote Sensing (RS), and Global Positioning System (GPS).
LO1: Describe concepts of Geographical Information system (GIS) and its application to Public health
LO2: Identify tools in GIS that can be used to study disease distribution
LO3: Create maps showing disease distribution using appropriate GIS program
LO4: Select appropriate functions in GIS programs to explore factors related to spatial distribution of disease
LO5: Interpret and present results of disease mapping in lay language
Concepts of data presentation and data visualization, human perception to graphics and color; appropriate graphic designs for data presentation; business intelligence techniques to transform health data into meaningful presentation, information dashboard to assist decision making
Describe key concepts in data visualization, including graphical perception, color and visual interaction
Identify important tools used for development of business intelligence platform
Prepare data for business intelligence platform
Develop a business intelligence platform (dashboard) for decision making
Spatial epidemiology, sampling and analysis; Cluster analysis; Surface analysis; Spatial autocorrelation and regression
LO1: Describe concepts of spatial epidemiology
LO2: Select appropriate statistical methods for spatial analysis
LO3: Demonstrate analytical techniques for spatial analysis
LO4: Interpret results and outcomes from spatial analysis
Modern methods used to analyze data into useful decision making information; various techniques for data exploration and data manipulation; data characteristics in terms of their patterns, correlation, and constraints; predictive models, association rules, decision tree analysis and cluster analysis; examples of applying data mining to improve operations and decisions in healthcare services
LO1: Describe the overall data mining process
LO2: Discuss major theories, practices, and techniques associated with the data mining process
LO3: Apply appropriate data mining techniques
LO4: Interpret results obtained from data mining techniques applied
LO5: Evaluate models using data mining techniques
Relevant mathematical modeling concept and its application in epidemiological studies; differential equations; R Programming; mathematical model to answer research questions; recent published modeling articles; economics modeling and cost-effectiveness analysis to link any conclusion on modeling interventions to health policy program
Interesting topics in Biomedical and Health Informatics, literature review, principles of critical appraisal of published literature; examples of health information systems in different settings