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In this module, students will study the skills required by the professional health informatician including 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 at raising the awareness of students about scientific computing. It provides a brief overview of computation and focuses on the computational needs and workflows 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.
Health data scientists are expected to work with diverse data sources. However, due to the abstraction offered by modern database management systems, these data sources can be treated similarly through a set of standardised operations. The objective of this module is to raise the awareness of students about the process of data modelling and the key operations involved in the data processing of large and diverse datasets.
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 making use of computational and storage resources will eventually be called to present their findings to an audience. The objective of this module is to enable students to choose and produce appropriate static and dynamic visualisations of health 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 is taught at an intermediate to advanced level and assumes that students have completed PMIM302 Introductory Analysis of Linked Health Data or have equivalent knowledge. Advanced principles of health care epidemiology are combined with hands-on practical exercises in the implementation of computing solutions. The module provides students with a theoretical grounding on each topic, followed by a training session on the corresponding computing solutions. Students use de-identified data files in the hands-on exercises. The computing component of the module assumes a basic competence in the preparation of computing syntax for programs such as SPSS, SAS or STATA and familiarity with the statistical analysis of linked data files at an introductory to intermediate level.
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.