This new complementary volume to Developing and Utilising Digital Technology in Healthcare for Assessment and Monitoring extends well beyond what has been already covered, including AI, Machine Learning and Big Data in health care, data-informed care, tackling health inequalities in cancer care through technological solutions and the policy considerations of digital innovation. 

This book reflects the increasing influx of technological solutions in varying fields within the context of healthcare, which extend from prevention to early detection, treatment and survivorship. With an increasing number of supportive care needs being unmet, such technological solutions can bridge the gaps in how current care is being delivered. An aspect that previously has not received considerable attention is the cultural competence in healthcare AI and robotics, and a chapter dedicated to this topic offers ideas for developing technologies that are culturally competent. The book offers unique insights into the areas and ways in which these interventions (e.g. taking into consideration cultural aspects) can be incorporated in the care continuum empowering the end-user (healthcare professional and patient). The book draws on the experts’ current (and at times ongoing) research on these topics.

The structure of the book provides multiple perspectives on the topic and makes it appealing to a multidisciplinary and multi-professional audience, with nurses as a primary target but also including clinicians, researchers, patients, technology experts and students. This approach fills a gap in this field not only by familiarizing the reader with a wide range of technological interventions in relation to their application in clinical practice, but also by emphasizing what the data-driven and need-orientated development of future interventions needs to take into consideration. 

This new complementary volume to Developing and Utilising Digital Technology in Healthcare for Assessment and Monitoring extends well beyond what has been already covered, including AI, Machine Learning and Big Data in health care, data-informed care, tackling health inequalities in cancer care through technological solutions and the policy considerations of digital innovation. 

This book reflects the increasing influx of technological solutions in varying fields within the context of healthcare, which extend from prevention to early detection, treatment and survivorship. With an increasing number of supportive care needs being unmet, such technological solutions can bridge the gaps in how current care is being delivered. An aspect that previously has not received considerable attention is the cultural competence in healthcare AI and robotics, and a chapter dedicated to this topic offers ideas for developing technologies that are culturally competent. The book offers unique insights into the areas and ways in which these interventions (e.g. taking into consideration cultural aspects) can be incorporated in the care continuum empowering the end-user (healthcare professional and patient). The book draws on the experts’ current (and at times ongoing) research on these topics.

The structure of the book provides multiple perspectives on the topic and makes it appealing to a multidisciplinary and multi-professional audience, with nurses as a primary target but also including clinicians, researchers, patients, technology experts and students. This approach fills a gap in this field not only by familiarizing the reader with a wide range of technological interventions in relation to their application in clinical practice, but also by emphasizing what the data-driven and need-orientated development of future interventions needs to take into consideration.