Quality assurance and safety

What are clinical safety, risk management and quality management methods?

Clinical safety, risk management, and quality management are three interconnected concepts essential to ensuring that decision support tools contribute to safe and effective delivery of healthcare.

Clinical safety is  freedom from the harm that can result from healthcare interventions. It encompasses a wide range of factors including patient safety, medication safety, and device safety.

Risk management is the process of identifying, assessing, and controlling risks. In healthcare, risk management is used to identify and reduce the likelihood and severity of adverse events.

Quality management comprises three elements:

• Planning for quality - for example, defining your decision support project goals, standards, practices, resources, specifications, and processes.
• Quality control - for example, editorial review processes, user testing, peer review, sampling content to ensure that it meets the required standards.
• Quality improvement - for example, continually gathering feedback and data on usage and impact so that you can keep improving your decision support tools and your approach to implementing them. 

How do I provide evidence of competency in this area? 

Can you...

• Explain the principles of clinical safety, risk assessment and quality management and give examples of how they apply to delivery of decision support systems?

What are the Medical Device Regulations and how are they relevant to decision support systems?

The definition of "medical device" covers a wide range of products, including some types of decision support software and apps. In the UK, the Medicines and Healthcare products Regulatory Agency (MHRA) is responsible for regulating the UK medical devices market.  Decision support systems that are classified as medical devices are legally required to conform to the standards and criteria set out in the Medical Devices Directive 93/42/EEC .

The Right Decision Service Standard Operating Procedure on compliance with Medical Device Regulations provides more detail on when decision support software is classified as a medical device and the evidence required to demonstrate conformity with the Medical Devices Directive. It also sets out anticipated changes in the Medical Device Regulations. 

How do I provide evidence of competency in this area? 

Can you...

• Signpost to information on the key principles and elements of Medical Device Regulations relevant to decision support systems?
• Appreciate why it is important that decision support systems classified as medical devices comply with  Medical Device Regulations?

What is clinical governance and how does it relate to decision support systems?

‘Clinical governance is the system through which organisations are accountable for continuously improving the quality of their services and safeguarding high standards of care by creating an environment in which clinical excellence can flourish. Effective clinical governance contributes to the safety and quality of patient care. Good clinical governance must support the early identification of risks and concerns that lead to individual, team and wider organisational learning.’ (General Medical Council, 2023, p. 05)

GENERAL MEDICAL COUNCIL, 2023-last update, Effective clinical governance for the medical profession. Available: https://www.gmc-uk.org/registration-and-licensing/employers-medical-schools-and-colleges/effective-clinical-governance-for-the-medical-profession (Accessed: 27^th September 2023).

Clinical governance is essential to ensure that decision support systems are safe to use in clinical practice, and to optimise their impact on quality of care. Key elements of clinical governance for decision support systems in healthcare organisations may include, for example:

1) A multi-stakeholder governance group that vets new requests and reviews existing content;

2) Confirmation that proposed new decision support systems meet service needs and address service problems;

3) Coordination with other governance bodies;

4) Putting mechanisms in place for clinical risk assessment and quality management;

5) Use of data analytics to identify high value and low value decision support, monitor progress and address gaps in usage.

6) Proactive elicitation of user feedback and suggestions for improvement.

7) Evaluation to guide decision-making regarding effectiveness of decision support systems.

How do I provide evidence of competency in this area? 

Can you...

• Articulate to others the key clinical governance principles, structures and processes which need to be applied to ensure safety and effectiveness of decision support tools?

What is information governance and why is it important to decision support systems?

Information governance is a framework for handling personal information in a confidential and secure manner to appropriate ethical and quality standards.  It provides a consistent way  to deal with the many different information handling requirements including:

• Assuring clinical information for safe patient care
• Confidentiality and data protection
• Corporate information assurance
• Information security assurance and
• Secondary use assurance - i.e. processing of health data for purposes other than the initial purposes for which the data were collected. This could involve, for example, collecting and analysing patient record data for research or audit purposes.

‘Information governance is about putting in place information management programmes to ensure that information is controlled to ensure it is “appropriately” available but that its security is not compromised.’ (Lomas, 2010)

LOMAS, E., 2010. Information governance: information security and access within a UK context. Records Management Journal, 20(2), pp. 182-198. https://doi.org/10.1108/09565691011064322.

Information governance is important to decision support because decision support systems may store or process person-identifiable data. They may also rely on secondary use of data to inform algorithms.

How do I provide evidence of competency in this area? 

Can you...

• Explain the key principles of information governance that are relevant to decision support systems?
• Identify potential information governance risks associated with decision support systems, including systems based on machine learning applied to large population datasets?
• Recognise how these risks can be mitigated? 
• Identify the key information governance contacts and processes in your organisation which will help to manage these risks and mitigations?