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The University of Southampton

HLTH6104 Healthcare Informatics

Module Overview

This is an overview of heath care informatics. It is a non-technical module (that is, there is no programming or mathematics) that introduces students to the central concepts and debates in the field of healthcare informatics. This module will be of interest to anyone interested in the roles that information and knowledge play in the provision of health care, how to implement new information and knowledge-management processes, or who is interested in such current issues as Big Data, privacy, or ethics.

Aims and Objectives

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Critically debate the key methods used in health informatics, and how to select among them
  • Critically analyse health informatics governance and how it is applied
  • Demonstrate application of relevant information theory to the design and evaluation of health care information systems
  • Critically debate the important challenges currently faced by individuals seeking to improve health in the five health domains, and describe how information resources, properly deployed, can help address these challenges
  • Assess and evaluate health care information systems
  • Refer to, use, and critically evaluate key theories that underpin health care informatics


The content of this module is informed by the theoretical and empirical research outlined on pages 3 through 9 of module profile. Taken together, we can divide this work into eight broad themes, each of which we will examine and discuss over the course of the module. • Theories of information, and methods from computing and information science. o Theories and concepts of information and its relationship to methods of computing and information systems design. • The Electronic Health Record & The Personal Health Record. o Canonical health records o National and international standards o Uses and limits of health records are (and can be) used o Privacy issues o Big Data (We will also discuss how disparate data gathered on day-to-day individual behaviour (such as shopping data, travel data, online search behaviour) create a virtual health record, and the ethical and policy implications of this.) • Data and information representation. o Coding practices o Error and verification o Data quality o Data transcription o Vocabularies/Ontologies/Semantics/Semantic web • Interoperability. o National and international standards for data o Strategies for integration o Crosswalks and mapping o Transitive relationships • Governance. o Security o Protection o Legal implications o Access o Ethics o Patient voice o Anonymization • Uses. o Telecare and Telehealth o Quantitative analytics o Policy development and analysis o Decision support o Auditing o Measurement o Research o Service, management, and organizational improvement • Human factors. o Cognition and human computer interaction o Theories of behavioural change o Barriers and enablers to usage/uptake o Normalization, Structuration, Embeddedness, and Actor-Network theories o Professional identity and workplace routines • Management o Strategy o Design and analysis o Vendor relationships o Training and development Finally, upon completing this module, you should have enough competency to be either a student or affiliate member of the UK Council on Health Informatics Professions or similar organizations.

Learning and Teaching

Teaching and learning methods

The conduct of this module on health informatics is informed by the following principles: • Learning should be relevant to practitioners and their work environments • Practitioners should be given experience and learn through errors • As much as is practical, practitioners should be involved in the planning and evaluation of their instruction • Instruction should be problem-centred • Instruction must be informed by current research and theory In practice, this means that we will keep lectures to an absolute minimum, and will instead adhere to these principles through practice-based and activity-driven classroom time that both delineate and make real various theories and approaches to analysing and evaluating systems. Because of the nature of the subject, some of which is fairly technical, there will be lecturing, but only to the extent that it helps you understand the details of the subject at hand. We assume that you have an interest in informatics, but no training or experience with it, information systems or computer science. And although we will discuss some of the more important social theories, this will not be a module focused on theory. Instead, we’ll look at theory to help explain some of the issues that we face in health informatics. Case studies and case analyses will have a central place in this module, and will be used to highlight and analyse the themes we have outlined above. In addition, you are encouraged to construct your own small, informal, case studies—probably derived from your own workplace—that we can use to discuss and evaluate. The idea is that we simply don’t learn techniques and theory, but we connect what we are learning to the real world because this is at the heart of the study of informatics. There will be guest lectures for each of the themes, drawn from senior researchers in the Faculty and University, as well as from local NHS Trusts. We will also involve both service users and community members who have an interest in, or who have been affected by, health informatics practice or policy. This will give us a chance to hear from people who are working in the field, and to whom we can ask searching questions.

Completion of assessment task50
Preparation for scheduled sessions150
Wider reading or practice14
Total study time250

Resources & Reading list

Brennan, P.F., Schneider, S.J., Tornquist, E., eds. (2012). Information Networks for Community Health. 

Berg, M. (1997). Formal tools and medical practices: Getting computer-based decision techniques to work, in Bowker, G.C., Star, S.L., Turner, W., Gasser, L., Social Science, Technical Systems and Cooperative Work. 

Avison, D., Fitzgerald. (2006). Information Systems Development: Methodologies, Techniques and Tools. 

The Scientific Conceptualization of Information: A Survey. ,7 , pp. 117-140.

Bears, B.J. (1986). The Cognitive Revolution in Psychology. 

Anderson, J.G., Goodman, K.W. (2002). Ethics and Information Technology: A Case-Based Approach to a Health Care System in Transition. 

Technology as an occasion for structuring: Evidence from observations of CT scanners and the social order of radiology departments. ,31 , pp. 78-108.

Berg, M. (1997). Rationalizing Medical Work: Decision-Support Techniques and Medical Practices. 

“Patient informatics”: Creating new partnerships in medical decision making. ,73 , pp. 408-411.

Bowker, G.C., Star, S.L. (1999). Sorting Things Out: Classification and its Consequences. 

Avison, D., Shah, H. (1997). The Information Systems Development Life Cycle. 

Information chaos in primary care: Implications for physician performance and patient safety. ,24 , pp. 745-761.

The effect of electronic prescribing on medication errors and adverse drug events: A Systematic review. ,15 , pp. 585-600.

A Qualitative study of the organizational consequences of telemedicine. ,7 , pp. 18-26.

Saba, V.K., McCormick, K.A. eds. (2011). Essentials of Nursing Informatics. 

Public health in an era of personalized health records: Opportunities for innovation and new partnerships,. ,12(3) .

ICT in health care: Sociotechnical approaches. ,42 , pp. 297-301.

Ball, M.J., Douglas, J.V., Walker, P.H., eds. (2011). Nursing Informatics: Where Caring and Technology Meet. 

Barbási, A-L. (2003). Linked: How Everything is Connected to Everything Else and What it Means for Business, Sciences, and Everyday Life. 

A Theory of fads, fashion, custom, and cultural change in informational cascades,. ,100 , pp. 992-1026.

Shortliffe, E.H., Cimino, J.J., eds. (2006). Biomedical informatics: Computer Applications in Health Care and Biomedicine. 

Axel, E. (1997). According tools with meaning within the organization of concrete work situations, Social Science, Technical Systems and Cooperative Work. 

Visions and strategies to improve evaluation of health information systems: reflections and lessons based on the HIS-EVAL workshop in Innsbruck. ,73 , pp. 479-491.

Bennett, C.H. (1990). How to define complexity. In Complexity, Entropy, and the Physics of Information. In Zureck, W.H. (ed). 

Bad health informatics can Kill: Is evaluation the answer?. ,44 , pp. 1 to 3.

Institutionalization and structuration: studying the links between action and institution.. ,18 , pp. 93-118.

Evaluation of patient satisfaction with tailored online patient education information. ,26 , pp. 258-264.

‘To take care of the patients’: Qualitative analysis of Veterans Health Administration personnel experiences with a clinical informatics systems. ,5 .

Factors and forces affecting HER system adoption: Report of a 2004 ACMI discussion. ,12 , pp. 8 to 12.

Clinical prediction: Does one sometimes know too much. ,13 , pp. 267-70.



One page problem statement


MethodPercentage contribution
Essay  (3500 words) 100%

Repeat Information

Repeat type: External

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