We bring together expertise from human factors, participant engagement and recruitment, methodology, and experience-based co-design, to ensure that studies complement the strengths and abilities of your target users and minimise the effects of their limitations. This varied expertise also helps us take a scientific approach and adapt our thinking to a diverse range of client requirements and project challenges.
We help you to build or develop safe, effective and high-quality devices or systems in the British and Chinese healthcare markets.
From the start, our human factors specialists fully communicate and understand users' requirements and make them a cornerstone of our work. After that, we are involved in an iterative design and development process. Finally, we conduct verification and validation studies to provide strong evidence that will help you make devices or systems safer and more effective, as well as meet regulations.
We have many years' experience in human factors methods, such as risk analysis, usability testing, user-related errors/risks analysis, and evaluation.
We use these methodologies to ensure rigour in our data analysis and to bring you deep insights which can help understand better understand users, and build and develop devices or systems more reliably and safely.
We establish a recruitment strategy early in your design and R&D process. Depending on your requirements, we provide a focused and flexible plan to help you recruit patients, healthcare professionals, nurses, carers, hospital managers, and other participants for market research, user research, clinical trials, and human factors and usability studies.
We have always attached key importance to user experience and combine healthcare professionals, nurses, carers and training staff with patients to co-study and co-design medical devices or care pathways together in partnership.
We use this approach and human factors techniques to deliver comprehensive and elegant solutions that offer a positive user experience and also maximumly avoid potential use errors.