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This module is designed to provide the foundational knowledge necessary to develop a deeper understanding of the historical context and antecedents for population health. It will address the structure, stakeholders, and processes of local, national and international health systems. An examination of the historical events and social, political, economic and demographic forces will help to contextualise the challenges faced by health systems stakeholders. Topics will cover both organisational and individual perspectives of population health and will serve as a foundation for further modules.
In this module, students will study the skills required by the professional health informatician with an introduction to information governance, including privacy and the maintenance of confidentiality, data security, legislation, ethical considerations, and current UK and global eHealth strategies. Students will also begin to develop their academic skills in literature searching, the critical evaluation of research literature and reflective practice.
The module aims to raise the awareness of students about scientific computing in the field of health data science. It focuses on basic software development workflows, tools, and skills that health data scientists most often employ. Students will also learn about the professional context within which health data scientists operate.
In this module, students will learn about communication and communication systems. This will include a study of electronic health records and clinical coding systems. Academic skills are developed and enhanced by an introduction to qualitative research methods.
Students will study data quality and management, secondary uses of clinical data, service improvement and clinical audit. Academic skills are developed and enhanced by an introduction to quantitative research methodologies. Students will be introduced to statistical software such as SPSS.
In this module, students will study the information systems & technologies used in health informatics projects and their implementation. These include: networks; the Internet; integrated communications; mobile communications; health information systems. Academic skills are further developed by studying how systematic reviews of literature are undertaken.
Data scientists working in healthcare are called to deal with problems involving classification and pattern recognition. The objective of this module is to provide the essential theory and practical aspects of widely used machine learning software.
In this module, students will study knowledge management in health care environments. The themes covered will include: clinical decision-making; decision support systems; workflow management; web site design. Students will study experimental research designs.
Health data scientists often have to present their findings to a non-academic/expert audience. The objective of this module is to enable students to choose and produce appropriate visualisations of health related data using a range of media.
In this module, students will develop their research skills by learning how to write a research proposal and prepare for the research dissertation.
This module builds on the knowledge and skills developed in part one of the course. Students will work independently in order to critically explore and add to the evidence base for a topic of relevance to health informatics.
This module builds on the knowledge and skills of modules PMIM302 and PMIM602 and are pre-requisites. Students will work independently with a large scale linked data set, developing and answering a specific research question.
In this module students use work based learning and experience in the construction of a work based portfolio, which will reflect on the leadership of a health informatics project.