The transformative impact of wearables & AI on healthcare workflows & patient care

This paper explores the transformative impact of wearables and AI on healthcare workflows and patient care, focusing on enhanced efficiency, personalisation, and cost-effectiveness.

1️⃣ IoMT (Internet of Medical Things) market is rapidly growing, projected to increase from $50.3 billion in 2020 to $135.87 billion by 2025, highlighting a significant shift toward digital health adoption. I’d like to contrast sources to evidence this is true and link websites & graphs & charts from reputable credible sources & for deeper comparative analysis and historical review…

2️⃣ Wearables have diverse applications, monitoring both biological factors (e.g., saliva, sweat) and utility-based measurements (e.g., smart fabrics, implants) to enhance patient data collection. I’d like to link a few examples of innovations doing these things because it’s helpful to know what’s out there…

3️⃣ Real-time monitoring through wearables and AI supports early disease detection and continuous tracking, facilitating better treatment adherence and fewer hospital visits. There are several innovations in the space which I would like to link and many websites have written about these types of technologies with a few books written on the topic and innovations in the space for example with eyesight and scanning irises prior to prescription glasses and things like that… I have a few connections who are in the space and there are some researches as well across universities and organisations that primarily focus on research who I can liaise with to obtain the Updates! 😊

4️⃣ Patient interest in remote monitoring is strong, with 79% willing to use mobile ECG tools, and 74% feeling safer with constant monitoring, demonstrating growing acceptance of self-managed care. I have worked and remote monitoring for a long time across financial services or healthcare facilities and with regards to patient information management a lot of this is involving monitoring and the handling of data associated, I think there might be a problem with self managed care and some circumstances - it may even be overwhelming for some people to self manage their own care. It would be important to look at the effect of this across different use cases which I could source.

5️⃣ AI-assisted monitoring with wearable sensors achieves high accuracy, including 97% accuracy in detecting atrial fibrillation, outperforming traditional methods. What With the Nhs always complaining about having financial problems? It is no wonder that they are turning to AI for cost saving benefits. I do, however, think there are ethical issues around this … I am somebody who has worked for the NHS across 6 to 8 years And I moved around different departments during this time Both corporate and clinical divisions. I actually have a Fitbit, which is a device on my wrist similar to an Apple Watch and I do find it useful. I can see why medical professionals would find these devices useful. I think the difference is when a device becomes not only useful but controlling. I think the ethical management of devices would need to look at how it’s built what it records why it records it and the purposes associated how the data is processed where it is stored And inform reports, but also much more!! 😓 People will want to know what is Ai ? doing with their data and they need a transparent answer. There have been studies of hospitals being hacked and sadly a lot of care staff are not technically savvy historically, There would need to be a review into Healthcare review required to assess how this cyber Security teams outsourced or in-house or managing to secure the environments. NHS-Trusts everywhere across the UK and I think they have Overseas bases as well. I can find the evidence for this. In terms of the hierarchy and reaching the right people, it all sits under the Department for Health and social care, (I think) And the funds and governance can fill down three senior management at c level Across the HQs In places like Kent, The magnitude etc (Where i used to work) And filter down through middle management and through various operational divisional departmental heads down to team management and project managers, & continue to cascade across teams and business units and clinical divisions. The patient care is obviously impacted by the quality of the care Being received. If it is all digitalised, Some metrics would be difficult to measure Due to the nuance nature of human experience And personalised care being non-generic and in Many cases unique so complete digitalisation would be unethical.

6️⃣ AI models like deep learning and neural networks enable predictive diagnostics and personalised treatments, demonstrating 80% accuracy for heart disease, 80% for blood infections, and 94% for cancer detection. Obviously we will need to see the consistency and accuracy over many years to have a strong enough case for the utilisation of these models and these models should only be used in certain conditions or circumstances which they are trained for specifically And with the lower levels of nuance. For example, common & non-critical conditions that are ‎non threatening, If they do make mistakes in this area, they’ll end up having to shell out *compensation claims For clinical negligence * With responsibility needing to be squarely deciphered - All of which will negate And undermine the value that AI Originally Sort to bring financially to the Nhs, & Creating more work through investigation, Which then has costs associated on top of compensation claims.

7️⃣ Integration challenges include data management, EHR integration, privacy, bias, and transparency, all of which must be addressed to foster trust among healthcare providers and patients. Data is very important in healthcare because sometimes if they have high turnover or they have a higher reliance on contemporary staffing, it’s all you have to go by in delivering the Care quality standards required. Many of these systems are silo and don’t talk to each other and sometimes says benefits to that from a security angle. It’s definitely a huge area that cyber security is Required. I can understand I’m having integration issues and often they are so confused about these integrations that they just buy knee systems which become part of them being B2B contracts - Many of them don’t really understand fully the systems that they Attempt to integrate. Every time they endorse the new system, it creates training requirements which is a time burden on staff and it means that more materials and workshops need to be delivered. And this also means paid time off work to train for these things, Occasionally reimbursing travel for staff to get up to speed just because they’ve had an upgrade or have changed the system again. There may be security benefits to these changes and these are high-level considerations.

8️⃣ Automation potential is significant, with AI transforming tasks like medical billing, coding, and lab workflows, reducing errors and freeing up resources for patient care. In some cases it is for reducing errors but not in all cases and these cases should not be brushed under the carpet because they are learning opportunities. It’s important to find use cases. I’m sure that medical professionals suffering and blogs about these things so I will try to see if I can find any to link them to this to Assess the benefits of AI in society, Particularly Healthcare.

9️⃣ Future healthcare will increasingly depend on AI and wearables, reshaping patient management, especially for aging populations, and enabling personalised, real-time care delivery. If anything it’s a way to Augment care…I don’t think it should be replacing Care itself!

🔟 AI and wearables promise a comprehensive transformation of healthcare, enhancing efficiency, personalising treatments, and reducing costs while overcoming obstacles to data integration and physician-patient trust. I think some of these promises are extreme. Transformations are never technically always comprehensive because there’s always more that requires transformation. It’s an evolving continue improvement landscape. The personalisation also fluctuates with life stages and phases. It came to reduce costs, but as explored it can also increase them. Patients will trust Professionals when it is in their best interests and not just In the interest of cost savings and efficiency for business objectives!

✍🏻 Perry LaBoone, PE, CPA, PMP, Oge Marques.

This is an overview of the future impact of wearables and artificial intelligence in healthcare workflows and technology. This overview can be expanded overtime with discoveries that I can update and incorporate.