Purpose:

To equip the students with the knowledge and skills to appropriately use decision support systems in healthcare (both clinical and public health settings).


Course objectives

At the end of this course the student should be able to:

1. Describe types of clinical and public health decision support systems

2. Illustrate mathematical foundations of knowledge-based systems in decision support systems

3. Explain areas of logical application of decision support systems in health and health care

4. Evaluate decision support systems and workflow, and apply methodologies to re-design health care processes using health information technology

5. Integrate CDSS systems in health care settings


Expected learning outcomes

At the end of this course the graduate should be able to:

1. Demonstrate knowledge of the range of clinical and public health decision support systems

2. Apply mathematical foundations of knowledge-based systems in decision support systems

3. Implement and evaluate integrated decision support systems in healthcare

4. Design healthcare processes using health information technology.

5. Utilize CDSS systems in health care settings.


Content

Clinical and public health decision support systems: History of CDSS, CDSS features, alerts and reminders, infobuttons, Rule-based systems, CDSS and electronic health records, expert systems (e.g. CADUCEUS), Watson, the Electronic Surveillance System for the Early Notification of Community based Epidemics (ESSENCE), BIFuM, Syndromic Surveillance Systems Mathematical foundations of knowledge-based systems; Application into decision support systems: Selected applications of mathematical foundations of decision support (e.g. Arden syntax, signal detection, bayesian networks). 

Areas to apply decision support systems in health and health care: Driving forces for CDSS, patients/provider/population/system based CDSS, challenges of CDSS, Big Data, syndromic surveillance and disease detection.

Implement CDSS in a Health-Care setting: Integration of CDSS to a Health Information system; alert fatigue; challenges to CDSS; practical use-cases of CDSS systems in Health; health information exchange; workflow engineering processes.


Mode of delivery: 

Overviews; Lectures; Small & large group discussions; Distant learning courses; eLearning; Case studies; Mini-project; Practical


Core Texts

Greenes, R.A. (2014). Clinical Decision Support, 2nd Edition. The Road to Broad Adoption. Academic Press; 2 edition (April 29, 2014)


Other Resources & Reference Materials

Reference readings as part of core text.

Instructional materials/equipment: White board; LCD projector, EMR system, computers.

Student assessment: Continuous Assessment Tests (Individual assignments, Presentations); End of semester Examination

Monitoring and Evaluation: Student attendance list; Student evaluation of instructor and course; Assessment of student attitudes and skills

PURPOSE

This course will equip students with knowledge on foundational techniques and technologies to understand key issues in HI and their application in research and practice in healthcare.



OBJECTIVES

1. Explain the basic concepts and key definitions in HI

2. Discuss the importance of designing system with appropriate human interaction

3. Describe how information is stored and retrieved

4. Identify utility of mathematical modeling techniques in HI

5. Illustrate how informatics is applied in health



OUTCOMES

1. Utilize basic concepts and key definitions in HI

2. Demonstrate understanding of HI systems with appropriate human interaction

3. Store and retrieve information

4. Apply mathematical modeling techniques in Health Informatics and health care

5. Apply informatics in health



CONTENT

Basic concepts/key definitions in HI: Definitions of health informatics; Evidence-Based Practice (EBP); ontologies; messaging; standards; enterprise architecture; interoperability

Human Computer Interaction: Understanding and conceptualising interaction; Understanding users; Usability testing; Emerging trends in HCI


Data, information management and retrieval: Database approach; Types of database management systems; Basic file processing concepts; Physical data storage concepts; File organizations techniques

Basic Mathematical Foundations of HI: Bayesian networks; neural networks; machine learning; rule-based systems; statistical based systems; prediction models; knowledge representation; Genetic algorithms; Clustering

E-Health application concepts: Electronic Health Record (EHR); Tele-health/ Consumer Health/ Mobile Technology; Community and Population Health; Education/ Gaming; Data Exchange and

Interoperability; Computerization and Health devices



PURPOSE

This course is designed to familiarize learners with common terminologies and concepts in health, healthcare and health systems


OBJECTIVES

1. Describe common medical terminologies

2. Discuss Systems of Classification of diseases

3. Discuss the determinants of health

4. Describe the healthcare system, its structure and actors


OUTCOMES

1. Use common medical terminologies

2. Classify diseases appropriately

3. Demonstrate knowledge of the determinants of health

4. Demonstrate knowledge of the healthcare system, its structure and actors


CONTENT

Medical terminologies including: health; diseases; primary care; consultation (history physical examination, investigations, management, referral; outpatient; inpatient; preventive; promotive; curative; etiology, prognosis; pharmaceuticals; medical laboratory

Classification of disease: communicable (infections or microorganisms); non communicable; acute; chronic; disease classification systems (International Classification of Diseases System, Diagnostic and Statistical Manual of Mental Disorders system)

Health determinants: underlying, intermediate and immediate causes (physical or environmental, personal or individual characteristics (genetics) and behavior); social; economic

Healthcare system: levels of health care (primary, secondary, tertiary); system building blocks (service delivery, health workforce, information, medical products, vaccines and technologies, financing, leadership or governance); upward or downward referral, health policies or laws (national, local); overall goals of health systems (improved health, responsiveness, social and financial risk protection, improved efficiency); public, private or faith based facilities.