Innovation Training Centre
Preparing and training innovators to give them their best chance of securing funding and developing new digital health innovations.
We curated a host of resources that will not only smooth your journey through the SYDHH Innovation Pipeline, but also help you gain the skills and knowledge needed to become a successful, funded innovator.
To find out about and reserve your place on one of our training events, sign up to our .
Project design
Below are some free resources on the innovation process and project management.
Co-design and patient and public involvement and engagement
Patient co-design in health refers to a collaborative approach where healthcare professionals, researchers, and patients work together to design and improve healthcare services, technologies, and processes. This approach recognises the unique perspectives and insights that patients bring to the table, considering them as valuable contributors in shaping their own healthcare experiences.
As part of the EPSRC South Yorkshire Digital Health Hub, patient co-design plays a crucial role in fostering innovation and ensuring that digital health solutions meet the diverse needs of the people they aim to serve. By actively involving patients in the design process, the Digital Health Hub seeks to create technologies and services that are not only effective from a clinical standpoint but are also user-friendly, accessible, and responsive to the preferences and requirements of the individuals who will use them.
In essence, patient co-design empowers individuals to have a direct impact on the development of digital health innovations, contributing to a more inclusive, responsive, and effective healthcare system. This collaborative effort aligns with the broader goals of the EPSRC South Yorkshire Digital Health Hub in advancing research, technology, and practice in the field of digital health for the benefit of both patients and healthcare professionals.
Here are some resources you can access for free about Co-Design and PPIE:
Data science in digital health
In the dynamic landscape of healthcare, the integration of data science has emerged as a transformative force, revolutionising the way we understand, manage, and improve health outcomes. The EPSRC South Yorkshire Digital Health Hub stands at the forefront of this revolution, bringing together the realms of technology, research, and healthcare to create innovative solutions for the well-being of individuals and communities.
Data Science in Health is the art and science of deriving meaningful insights and knowledge from vast and diverse datasets within the healthcare domain. It involves the application of advanced analytics, machine learning, and artificial intelligence to extract valuable patterns, trends, and predictions from medical data. This, in turn, enables healthcare professionals, researchers, and policymakers to make informed decisions, enhance patient care, and drive advancements in the field.
Here are some resources you can access for free about Data Science:
- - create a free account to access this training course
- - create a free account to access this training course
- -This module contains several courses; Introduction to Python, Introduction to R, Machine Learning, Natural Language Processing, Prediction Modelling. You will need to create a free account to access these courses.
- - This module contains several courses including; Basic R, Statistics with R, Using Spreadsheets. You will need to create a free account to access these courses.
Wearables for data collection
The utilisation of wearable devices in data-driven health solutions, particularly within the context of the EPSRC South Yorkshire Digital Health Hub, represents a pioneering approach to enhancing healthcare outcomes. Wearable devices, ranging from smartwatches to fitness trackers, play a pivotal role in continuously monitoring and collecting relevant health data from individuals. This wealth of information contributes to a comprehensive understanding of an individual's health status and behaviour patterns, facilitating personalised and proactive healthcare interventions.
Wearable data could support the development of a more personalised and data-informed healthcare experience. Wearable devices can continuously monitor vital signs, physical activity, sleep patterns, and other relevant metrics, providing participants and healthcare professionals with valuable insights into an individual's health journey. The incorporation of NHS data can further enhance the accuracy and completeness of this information, fostering a collaborative and informed approach to healthcare decision-making.
The Digital Health Hub's emphasis on data-driven solutions not only aids in early detection and prevention of health issues but also facilitates targeted interventions and treatment plans. Participants can receive timely feedback, access personalised health recommendations, and actively engage in their well-being. This comprehensive approach not only empowers individuals to take control of their health but also contributes to more efficient and effective healthcare delivery.
Here are some resources you can access for free about the usefulness of using wearables for collecting health data:
NHS policies
Here are some websites and resources that give more information on NHS regulations and policies around digital health and innovation.
GDPR
Here are some resources that give more information about GDPR.
Data management, governance and security
Below are some resources that give more information about managing data safely.
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The Health Research Authority (HRA) outlines necessary approvals for UK health and social care research. Depending on whether a project is classified as research, specific approvals such as HRA Approval, Research Ethics Committee review, or Confidentiality Advisory Group recommendations may be required. The HRA also provides a decision tool to guide organisations in determining if their projects need formal approvals based on data use and study type. The research project should obtain their approval before starting their project. Find out more here.
Health Research Authority emphasises the importance of documenting your data management plan for research involving health and care data. This includes preparing a Data Protection Impact Assessment (DPIA), a Data Flow Diagram, and a Data Sharing Agreement to outline data handling, compliance, and security. Such documentation helps identify data risks and ensures adherence to UK GDPR requirements.
Managing research data ethically and effectively throughout its lifecycle is essential. From data planning and protection to secure storage and sharing, researchers should focus on maintaining high data quality, meeting ethical standards, and creating well-documented, reusable datasets. A clear understanding of anonymisation, intellectual property rights, and data security is critical to uphold best practices and ensure data integrity.
Artificial intelligence in digital health
AI systems can analyse vast amounts of health-related data, offering valuable insights into patient trends, treatment outcomes, and epidemiological patterns. The data-driven approach ensures that health solutions are grounded in evidence, promoting precision and efficiency. Co-design methodologies emphasise the active involvement of end-users in the creation of solutions.
By combining AI-generated insights with user feedback, solutions are tailored to address specific needs, preferences, and challenges faced by individuals and communities.
AI can facilitate the development of personalised health interventions by understanding individual variations in health data. Co-design principles ensure that these personalised solutions align with the diverse needs and expectations of the participants. The iterative nature of co-design, coupled with AI's ability to continuously analyse new data, can be the key innovation for ongoing improvements to health solutions. This dynamic feedback loop ensures that interventions remain relevant and effective over time.
By bringing together the strengths of AI and co-design, the Digital Health Hub endeavours to pioneer a new era of healthcare innovation that is both evidence-based and user-centred.
Here are some resources you can access for free about the basics of artificial intelligence:
- - You will need to create a free account to access this course.
- - This resource contains three courses: Demystifying AI, Intermediate Python and Software Engineering and Applied Artificial Intelligence. You will need to create a free account to access these courses.
Large language models
These courses are mainly for non-computer science specialists.
Good clinical practice - NIHR
Good clinical practice (GCP) is an international ethical and scientific quality standard for designing, recording and reporting trials that involve the participation of human subjects. Compliance with this standard provides public assurance that the rights, safety and wellbeing of trial subjects are protected and that clinical-trial data are credible. - European Medicines Agency