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Thematic analysis of tools for health innovators and organisation leaders to develop digital health solutions fit for climate change
Summary
This article discusses the need for health innovators and organization leaders to develop digital health solutions that take into account climate change. It presents a qualitative thematic analysis of 34 tools related to two responsibility principles: environmental sustainability and organizational responsibility. The analysis showed that 11 tools focus on reducing energy and materials consumption, and 33 tools focus on executive roles for data risk management, data ethics and AI ethics. It concluded that significant work is needed to support the development of sustainable digital health solutions.
Q&As
What practice-oriented tools are available to develop environmentally sustainable digital health solutions?
Guidance to make environmentally sustainable digital solutions is found in 11 tools.
What roles should organisation leaders have in supporting the development of such solutions?
Organisation leaders should have roles for data risk management, data ethics and AI ethics.
How can environmental sustainability be translated into tangible organisational responsibilities?
Environmental sustainability can be translated into tangible organisational responsibilities by focusing on reducing energy and materials consumption as well as pollution and waste production.
What are the market considerations that shape key design and development decisions in the digital health industry?
Market considerations that shape key design and development decisions in the digital health industry include cost, efficiency, and user experience.
What work is needed for medical and organisation leaders to support the development of solutions fit for climate change?
Medical and organisation leaders need to support the development of solutions fit for climate change by providing guidance on environmental sustainability and organisational responsibility, and by translating environmental sustainability into tangible organisational responsibilities.
AI Comments
👍 This article provides an insightful analysis of the tools available to health innovators and organisation leaders to develop digital health solutions that are fit for climate change.
👎 The article fails to provide concrete solutions to help health innovators and organisation leaders develop digital health solutions that are fit for climate change.
AI Discussion
Me: It's about developing digital health solutions that are fit for climate change. It looks at the tools available for innovators and organisation leaders to do this and how they can support each other in this endeavour.
Friend: Interesting. What are the implications of the article?
Me: The article suggests that there is a need to balance the clinical safety and efficacy of digital health solutions with environmental sustainability. It also highlights the importance of organisational responsibility when it comes to data risk management, data ethics and AI ethics. This means that organisation leaders need to be aware of these issues and take proactive steps to ensure that digital health solutions are fit for climate change.
Action items
- Research existing tools for health innovators and organisation leaders to develop digital health solutions fit for climate change.
- Develop a plan to integrate environmental sustainability into organisational responsibility for data risk management, data ethics and AI ethics.
- Create a framework for medical and organisation leaders to support the development of digital health solutions fit for climate change.
Technical terms
- Thematic Analysis
- A method of analyzing qualitative data by identifying patterns and themes in the data.
- Digital Health Solutions
- Technology-enabled healthcare services and products that are used to improve patient care and health outcomes.
- Climate Change
- A long-term change in the Earth's climate, especially a change due to an increase in the average atmospheric temperature.
- Scoping Review
- A type of literature review that seeks to map the key concepts, sources, and stakeholders in a research area in order to identify the main issues and key gaps in the existing literature.
- Qualitative Analysis
- A type of research that uses non-numerical data to explore and understand a phenomenon.
- Data Risk Management
- The process of identifying, assessing, and managing risks associated with data.
- Data Ethics
- The ethical principles and standards that guide the collection, use, and storage of data.
- AI Ethics
- The ethical principles and standards that guide the development and use of artificial intelligence.