Health Data and System Integration

Details

Title

Health Data and System Integration

Type

Stage Two

Module code

HBI124

Requirement

Compulsory

Module objective

There is a mass of health and related data stored across multiple health and social systems and organisations, from the electronic health record to wellness data collected from wearable devices. However, it is often difficult to gain insights into this, evaluate population health projects, or translate knowledge into practice as the data is not integrated or linked across systems for a population. This module will focus on the integration of systems and key data sources, such as registries, electronic health records, epidemiological databases, bio-surveillance and other emerging data streams.

By the end of this module the Clinical Scientist in HSST will be able to manage and integrate health and related data sets from individual systems across a population with an in-depth understanding of the technological, sociological, ethical and methodological issues. They will be able to interact and communicate with stakeholders, including public health and patients, and ensure they can apply the latest developments in the fields. The Clinical Scientist in HSST will also be expected to consistently demonstrate the attitudes and behaviours necessary for the role of a CCS.

Knowledge and understanding

By the end of this module the Clinical Scientist in HSST will be able to analyse, synthesise, evaluate and critically apply their expert knowledge of current health (population and public health) data and system integration and interoperability, including:

• Population-level, public health and bio-surveillance data, and appropriate methods and metrics, and understand their use to improve population and public health.
• Data concepts, standards and architectures for sharing data/information for population and public health.
• Challenges and issues associated with the mapping/linking and integration of diverse data sets.
• Methods for interrogation of systems.
• Key systems design/architecture concepts to health informatics infrastructure that enables effective analysis.
• Policies and application of technologies that relate to the use of Health Informatics to improve population health.
• ‘Informatics’ solutions to support population health interventions and initiatives.

Technical and clinical skills

By the end of this module the Clinical Scientist in HSST will have a critical understanding of current evidence of Health Informatics and its application/interpretation to the integration of population data. They will perform and master a range of technical and clinical skills and will be able to:

• Assess processes and data-sharing requirements and provide workable models in line with current governance legislation.
• Apply key systems design concepts to population informatics infrastructure that enables effective monitoring and analysis.
• Identify and use data sets for linkage related to specific population health projects.
• Apply policies and use appropriate technologies to support health informatics analysis.
• Evaluate ‘informatics’ solutions and performance to support population health interventions and initiatives.
• Identify sub-optimal areas of practice and recommend improvements to allied professionals, clinicians, other healthcare scientists and managers.
• Impart scientific results to and discuss with patients, investigations, risks and outcomes that may be highly sensitive, emotive, or have serious implications, recognising that the responsibility for the overall care of the patient rests with the accountable medical consultant or general practitioner in appropriate circumstances and within the context of particular and defined clinical circumstances.

Professional practice

The Clinical Scientist in HSST will:

• Critically reflect and apply in practice a range of clinical and communication skills as they work in partnership with the public, patients, clinicians, academics and other healthcare professionals.
• Critically analyse the practice of Health Informatics, ensuring that regular review of research and evidence is undertaken so that adaptation to practice can be made in a timely and cost-effective manner.
• Protect research data on conclusion of the project in order to defend any relevant publication and/or challenge to the research findings.