Data Management (HBI110)

Module Objective

A major challenge that current and future health analytic technologies will create is in data – both in terms of volume and complexity of the governance. Clinical informatics and genomics will create some of the largest data sets that have ever been used within the NHS. Managing and working with data of this scale safely and effectively creates data management challenges for the existing NHS IT infrastructure.

By the end of this module the Clinical Scientist in HSST will be able to analyse, synthesise and apply their knowledge and understanding of standard relational database structures and the challenges of database handling at scale, as very large data becomes inherent in the clinical process. They should be aware and able to communicate effectively with the data science community and be able to formulate strategic directions that could be taken within the service. They will also be able to formulate, argue the value and impact of, and implement a data sharing policy. They will also be able to incorporate unstructured data into a structured, manageable framework. 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 Clinical Scientist in HSST will be able to analyse, synthesise, evaluate and critically apply their expert knowledge to data management, including:

  • Relational database theory.
  • Large data (e.g. NoSQL).
  • Challenges of managing and working with large data sets and applicability of distributed systems and other big data solutions.
  • Concepts of provenance and reproducibility.
  • Data sharing, the role of the patient in informed consent.
  • Information security and governance.
  • Safeguarding personal data, confidentiality, privacy.
  • Risk of non-identifiable information being cross-referenced with other databases to make it possible to identify individuals.

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:

  • Implement development and rollout of relevant databases.
  • Evaluate the impact of new systems.
  • Manage procurement development and maintenance of shared, scalable data infrastructure and/or data management system.
  • Use data federation to support the integration of health data, e.g. rare diseases from different platforms.
  • Provide appropriate input into strategies for clinical record mining.
  • Link clinical data to support appropriate analysis of health data, e.g. genomic profiling; radiomics.
  • Manage large data resources within clinical governance and quality assurance frameworks.

By the end of this module the Clinical Scientists in HSST will be expected to critically reflect and apply in practice a range of clinical, problem-solving and communication skills with respect to data handling and management. They will communicate effectively with clinicians, academics and other healthcare professionals as well as the public and patients, as appropriate, and will be able to:

  • Drive discussion and strategy around patient access to and sharing of data across professional groups.
  • Effectively communicate data management issues to the patients, the public, and the scientific and clinical community.

In addition, Clinical Scientists in HSST will be aware of their own attitudes, values, professional capabilities and ethics, and critically reflect on: (i) their professional practice; and (ii) the challenges of applying research to practice in relation to these areas of practice, identifying opportunities to improve practice building on a critique of available evidence.