Applied Health Informatics (HBI108)

Module Objective

Clinical Bioinformatics is performed in the complex informatics and social structure of the NHS. Therefore, in order to support the design and evaluate information technology tools and processes, or design new ways of using information to address specific needs, there is a need to understand the interplay between technology, people and social systems. Qualitative research methodologies used within social science can be used to gain insights into these issues.

Health Informatics is a key component of the patient care pathways and so it is important for patient safety that any code that is developed or deployed can be shown to be safe and effective. For that reason the Clinical Scientist in HSST must have knowledge of the appropriate regulatory, governance and quality assurance frameworks that apply to Health Informatics and how they should be applied within the clinical environment.

By the end of this module the Clinical Scientist in HSST will be able to analyse, synthesise and apply their knowledge and understanding of ontology/terminology for describing a patient/family phenotype. They will be able to interact with organisations developing coding standards, appraise an interface for its appropriate use within a clinical environment and analyse the influence that an organisation structure will have on data quality. The Clinical Scientist in HSST will also be expected to consistently demonstrate the attitudes and behaviours necessary for the role of a CCS.

By the end of this module the HSST Clinical Scientist will be able to analyse, synthesise, evaluate and critically apply their expert knowledge to applied Health Informatics, including:

Knowledge representation

  • The theoretical foundations of knowledge representation.
  • Knowledge acquisition environments.
  • Reasoning across knowledge domains.
  • Relevant ontologies, classifications and terminologies applied to the appropriate clinical area, e.g. genetic, genomic and health data, and their strengths and weaknesses.
  • Methods used for interaction with electronic health systems.
  • Quality assurance and regulatory frameworks appropriate for electronic health systems.

Human–computer interaction

  • The main concepts in human computer interaction.
  • How to determine the needs of users.
  • User-centred design methodologies.
  • Strengths and weaknesses of interfaces and increasingly robust interoperability.
  • Techniques for basic user evaluation and usability testing
  • Quantitative evaluation, e.g. A/B testing.

System-wide human factors

  • For example, actor network theory; ethnographic methods.

Patient care pathways

  • Informed consent.
  • Communicating with patients, carers and families.
  • Informing, advising and communicating with vulnerable individuals and their advocates.
  • How health, public health and social care converge.
  • Risks of collating (extracted) data from multiple sources.
  • Governance, safeguarding and privacy of personal data.
  • The risks of data sharing.
  • The complexity and risks of protecting privacy.
  • Risk and mitigation of accidental disclosure of personal data, including ensuring that the ‘non- identifiable’ information that leaves the NHS can’t be cross-referenced with other databases to make it easier to identify individuals.
  • Potential for misinterpretation of data, e.g. in a legal or political setting.
  • Patient rights, including the opportunity to opt in or opt out of sharing of patient-specific data outside the NHS.
  • Importance of protecting privacy within and out with the NHS.
  • The non-clinical, negative effects of a genetic diagnosis. including:
    • psychological concerns;
    • financial considerations (e.g. insurance);
    • potentially as yet unrecognised issues.
  • Interoperability of operational healthcare delivery support systems.
  • Integrating genomics information:
    • with enabling technologies, e.g. telematics/telehealth/m-health/assistive-ambient technology;
    • across traditional care boundaries, e.g. primary care, secondary care, social care;
    • into patient records;
    • to support collaborative health.

By the end of this module the Clinical Scientists in HSST will have a critical understanding of current evidence and its application to the performance and mastery of a range of technical skills and will be able to:

  • Access and manipulate ontologies and classifications, cross-mapping between resources safely, taking account of contemporaneity and appropriateness and the risks implied by asymmetric synergy of sharing data over time.
  • Apply appropriate techniques for basic user evaluation and usability testing.