Human Factors Analysis

What is this project

The essential contribution of human factors is that it recognises the importance of the interaction between many components of a system, including those arising from the inherent variability of humans and the “real-world” of healthcare.

It is often helpful to start a discussion around this by asking some simple questions when presented with a diagnostic innovation. These questions include: “who will this benefit?”  “how and when will the benefits be realised?”  “how will we know?”

As the conversation develops, we usually find that other important issues are raised regarding who the diagnostics tests have been designed for (including all potential users), how the innovation will operate with and alongside other technologies,  when it should/should not be used and what happens when it fails (note: all technology fails sometimes.)

Our experience shows us that, in the field of healthcare, a human factors led approach to design is imperative if an innovation is to realise its full potential and be trusted by patients and health care professionals. 

All these factors impact on the real value of an innovation, over and above its technical specification (e.g. its sensitivity and specificity relative to existing benchmarks of diagnostic accuracy.) 

For a system to perform effectively, the role of the human in designing, interacting with or completing an engineered system must be recognised. All systems involve human contributions.

Even so-called ‘autonomous’ or ‘automatic’ systems will have been designed and maintained by humans. Therefore, recognising the capabilities, needs and limitations of humans within complex systems is essential.

The discipline of human factors has played a role in supporting the design of many types of socio-technical system, including where the “technical” component of such systems involves diagnostic technologies.

Because tools and technologies form part of a healthcare work system, the introduction of new devices will change the system. Such changes may be positive, negative, or both e.g. they might simultaneously have a positive impact of some parts of the system and a negative impact on other parts.  This points to the need for a systems approach to integrate diagnostic technologies into healthcare, as well as a need for design approaches that minimise negative effects for people and optimises the performance of tasks.

The key stages in any human factors led study of diagnostic innovation include:

Mapping the work system:  This includes identifying and describing  the clinical pathways, identifying how and where the diagnostic testing may be done, how the information arising from the tests will be used and by whom, what the impact will be on other equipment, other staff and on the wider organisation.

Task and process analysis: The key to understanding what actually happens in a system is to document processes and tasks. Sampling variability of these across organisations and within staff groups is essential.

Analysis of potential errors/failures: Poor design contributes to the likelihood of errors that may compromise patient safety, the efficacy and efficiency of the intervention, and the risk to end users.

Design recommendations:

Evaluation of impact and value proposition generation: Most human factors studies are performance driven. They consider productivity, efficiency, effectiveness, quality, innovativeness, flexibility, (systems) safety and security, reliability and sustainability. They also consider the well-being of those delivering the system (e.g. health and safety, satisfaction, pleasure, learning, personal development). Performance and well-being are likely to interact with performance influencing well-being and vice versa. Bringing these aspects to bear in value proposition statements and using them in health economic evaluations provides an important systematic approach to the challenge of evaluation of new diagnostics.