Data – Driven Healthcare – Chris May

AI-powered virtual health assistants These AI-driven tools support patients through digital communication, offering personalised health information, medication reminders and appointment scheduling. They can also answer patients’ questions and provide tailored health tips, improving patient engagement and adherence to treatment plans. These virtual assistants can be integrated into mobile apps and other digital platforms, making healthcare more accessible. For example, a virtual assistant could remind a patient to take their medication and provide information about potential side effects. In the next few years, there will no doubt be another book to write just on the use of AI in healthcare settings.

Advances are being made all the time, potential risks are being identified at an equally exponential rate and it is almost impossible to predict where we will end up in the short term. Long term, however, and assuming there isn’t the AI apocalypse feared by many, I am sure AI will become an omniscient and ubiquitous presence in healthcare that we will simply take for granted, permeating everything and making data- driven healthcare second nature. In the short term, however, what AI can offer will only be as good as the data available to it.

And as we will see, there is still much work to do on preparing the foundations before AI can be safely and productively unleashed to solve our healthcare problems. OceanofPDF.com The rise of data in healthcare aving examined the key technological and engineering advances driving healthcare in the preceding chapters, I will now review those developments that are purely or primarily related to data technologies. Separating the new healthcare technological landscape into data and non-data categories is a somewhat arbitrary process as a superficial review of the technologies just summarised will immediately reveal a huge dependence on data at their foundations.

Ultimately, everything digital can be reduced down to 1s and 0s. For example, personalised medicine and genetic science essentially deal with vast libraries of data that will be created and used to develop treatments. Similarly, telehealth at its core represents the transmission of data; 3D printing relies on patterns constructed of data; smart devices, wearables and biosensors capture data; and virtual worlds are made solely out of data.

What distinguishes the aforementioned technologies, however, is that they are more than data; there’s a lot more science and engineering going on. In the journey toward data-driven healthcare and the next generation of the patient care record, the data I refer to from now on includes all the information that is captured and stored as the patient navigates the healthcare system. This can include simple demographic information such as age and gender, but also complex data such as vital signs and genomic information.

The important thing to note here is that this data too is being captured in a shifting environment of general data technologies that are becoming increasingly powerful, clever and ubiquitous.

There are few voices in the industry I take as seriously as Chris May’s. In this clear and informed book, he gives us an overview of the current tech landscape as well as highlighting the key themes that are central to shaping its future. His approach is grounded in public expectation, informed by what’s technologically possible, and acutely aware of the unique challenges facing healthcare services. – Dr Ben Allen, GP partner & medical director A refreshing and humane approach to artificial intelligence, one that appreciates the vital collaboration between patient, doctor and software.

Standardising and personalisation might seem like polar opposites, but May makes it crystal clear why we do better with both. – Margaret Heffernan, CEO & author This book offers fascinating insight at a time when harnessing the power of data in healthcare has never been more important – or more possible. – Rachel Heggart, senior project manager, NHS England A welcome provocation on how we can harness data and digital innovations to better personalise care.

This book is useful for all in the healthcare community, as it shows how we can become more patient-centric by using insights gleaned from data to predict needs and prevent harm. – Tara Donnelly, former chief digital officer, NHS England & founder, www.Digital.Care Data-Driven Healthcare paints a compelling picture of the vastly untapped potential for using the data already available within the healthcare system to dramatically influence and improve patient outcomes.

Blissfully jargon free and wide ranging in its scope, it is a comprehensive primer for anyone interested in delving into the world of health data. – Lucy Ellis-Brookes, deputy director in data & analytics, NHS England Chris May sets out the path for a data-driven and patient-centric healthcare ecosystem that makes the most out of the latest advances in technology. A valuable read for clinicians, managers and investors alike. – Yasemin Arik, healthcare investor & partner, G Square Capital Chris May articulates the vision many of us in digital health share but often struggle to express: patient-centred, outcome-driven care built on interoperable, intelligent systems.

He makes a clear, compelling case for moving from data collection to data use, and issues a timely call to action for everyone involved in healthcare. We owe it to our clinicians, patients and the NHS to get the full value from the available data to drive better outcomes for all.

This is a short excerpt from the opening of “” by Unknown, quoted for review and introduction purposes. All rights belong to the copyright holders.

Book Information

• Unique ID: d6a72778a0f4fca9
• File Extension: .pdf
• File Size: 2,018,098 bytes (1.925 MB)
• Title: –
• Author: Unknown
• ISBN: 9781917490085, 9781917490092
• Pages: 194
• Language: English (en)

Reading & Word Statistics

• Estimated Reading Time: 212.16 minutes
• Total Words: 42,432
• Total Characters: 284,117
• Average Words per Page: 218.72
• Average Characters per Page: 1464.52

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