Will AI and Wearables Facilitate Telemedicine?

Data is the new currency for a successful digital transformation. The healthcare industry is poised to benefit greatly by being able to optimize healthcare data that is being constantly generated in the current digital age. A patient’s medical records and electronic health records (EHRs) are no longer the only sources of healthcare data. The rise in healthcare-based mobile apps and a growing prevalence of health and fitness wearables are fueling the rise in healthcare data generation. The Internet of Medical Things (IoMT) comprises of a network of interconnected devices within the health IT infrastructure. 

The healthcare data collected through leveraging the power of IoMT implementation has the potential to streamline healthcare delivery, give way for personalization of patient care, introduce efficiency in treatment planning, enhance health outcomes and increase the overall quality of patient care. 

wearable healthcare technology

Wearables and Artificial Intelligence

Artificial intelligence and wearable technology make perfect sense together. The healthcare data generated by wearable devices can be processed via AI algorithms to yield timely inferences allowing healthcare practitioners to take data-backed decisions. 

Wearable devices also facilitate remote delivery of care through timely intervention by healthcare professionals via telemedicine. Expansion of reach and accessibility of high-speed internet and growing demand for better treatment options at lower costs is propelling innovations that couple wearable devices powered by artificial intelligence.

With an aging population and a rise in chronic diseases, the need for newer models for healthcare delivery is being felt more than ever. Telemedicine in combination with technologies like wearables and AI can help bridge the gap, make healthcare more accessible, provide timely interventions and help keep patients out of the hospital while ensuring the quality of healthcare delivery. 

The transformation is currently happening

The use of AI-powered wearable devices to provide telemedicine facility is not a futuristic vision. One such device is already in the market and has also received FDA approval in April this year. NHS hospitals at Dartford and Gravesham have partnered with Current (formerly known as Snap40) for a pilot program aimed at remotely monitoring the patient’s vitals and analyzing the same through Artificial Intelligence. 

At the time of discharge, the patients are fitted with wi-fi enabled armband that records the patient’s vitals. They also receive a chatbot equipped tablet that provides medication reminders, health-related information and can be used to remotely communicate with the doctors on a real-time basis both via video and text.

With real-time health data being constantly analyzed by artificial intelligence algorithms, these devices can pick up the warning signs and send out alerts to the patients as well as the doctors. 

Benefits of AI-powered IoMT devices 

The advancement of wearable devices that are powered by AI algorithms is supported by concurrent technological progress in both hardware as well as software. Bulky devices are a thing of the past. Wearable devices come in all shapes and sizes now and can be conveniently carried around and worn by patients resulting in increased compliance. The strides that artificial intelligence has been making in recent times is also fueling the adoption of these healthcare devices. 

Here are the ways the combination of AI and IoMT are benefiting healthcare delivery via telemedicine

1. Personalization of care 

The patient data collected via the wearable devices allows healthcare practitioners to make a data-driven approach. Doctors can take data-backed decisions and formulate a health plan that is customized for the patients at an individual level. 

While healthcare devices let the patients get access to their own healthcare data, in order for it to result in enhanced patient engagement, intervention by healthcare professionals becomes a necessity. Patient data needs to  be interpreted and explained by the care providers and this is where telemedicine factors in. 

Leveraging the data collected by the IoMT devices, the AI algorithms can formulate tailored and personalized action plans. The treating physician can then remotely ensure the adherence to the plans, monitor the progress and prescribe changes whenever necessary resulting in improved health outcomes. 

2. Early diagnosis and timely intervention

Artificial intelligence and machine learning algorithms can be employed to identify patients at elevated risk of developing diseases. Radiological and histological analysis via AI has already shown promising results. Leveraging the AI-powered wearable devices to screen the patients and create a risk profile can result in timely interventions via telemedicine and improve the overall outcomes. 

Identification of “at-risk” patients also allows setting up of special touchpoints and timely interventions thus reducing the burden on the hospitals, lessening the hospital admission and readmission rates and reducing the overall healthcare delivery costs. 

The patient and his caregivers may not be the best judge when deciding when to contact the doctor but AI algorithms that are constantly analyzing the patient data collected by the wearable devices can result in timely interventions. 

3. Remote patient monitoring

Contrary to the traditional hospital setup where nurses and doctors check on the patient at regular intervals, the wearable devices monitor the vitals on a minute by minute basis. Any anomaly that occurs can be immediately identified resulting in quick alerting of the healthcare professionals and timely healthcare delivery.

AI-powered wearable technology has transformed the way we collect and analyze patient data. The widespread availability and adoption of these devices streamline the process of post-hospitalization monitoring. Healthcare professionals not only gain access to real-time patient data, having AI processed data gives them vital insights into trends and patterns which brings efficiency in the process of healthcare delivery. 

Using telemedicine for hosting follow-up appointments and treating patients remotely is a resource-efficient strategy. Healthcare practitioners can cater to a greater number of patients while bringing down the costs associated with healthcare delivery. 

Virtual delivery of healthcare also saves up on the patient’s time and resources by not having to schedule visits to-and-from the hospital premises just for the sake of follow-up appointments, reduces hospital readmissions and most importantly prevent avoidable deaths.

How can healthcare organizations successfully leverage technology?

Make use of AI in disease detection as well as treatment

Artificial intelligence can be a vital resource during the diagnostic as well as the treatment phase. Diagnostic reports, scans, graphs, and vitals can be analyzed using AI in order to identify high-risk patients, both in hospital setup as well as on a remote basis. This is particularly promising in the area of cancer detection, chronic pulmonary obstructive disease (COPD) and chronic cardiac conditions.

MIT’s computer science and artificial intelligence laboratory (CSAIL) has partnered with Massachusetts general hospital (MGH) to create a deep learning model that predicts the risk of the patient developing breast cancer in the future by analysis of patient’s mammographs. The hospital is making progress into early screening and prevention programs at an individual level, making AI aided early diagnosis a reality. 

Use of AI and wearables can streamline the treatment phase as well. Cancer treatment, in particular, requires episodic encounters of the patients and healthcare providers. Even when intensive chemotherapy is ongoing, the patients spend a significant amount of time away from the clinical setup during which the side effects are required to be monitored. 

AI with the help of wearable devices can help in complex decision making and adverse effects monitoring by recording the patient data. AI algorithms can also help in the decision-making process by determining when the situation calls for contacting the health care team. In case of emergencies, contacting the emergency personnel can also be automated which has to potential to save lives in adverse situations as a result of timely alerts being sent out. 

Leverage the power of IoMT through smartphones and other wearables

IoMT is a powerful asset when it comes to patient data collection. Huge devices that would disrupt the patient experience are already a thing of the past. Modern technological innovations in the hardware department have resulted in the development of microsensors which can be easily embedded in handy devices or even implanted in the form of biosensors. 

Smartphones and smartwatches have also become an important component of IoMT. A wide range of sensors come in-built in these devices. Healthcare organizations can have custom developed healthcare applications that collect patient data, provide real-time support to the patients or even act as telemedicine portals through video-conferencing. Healthcare providers can also analyze and compare the relevant patient data in order to result in optimum clinical decision making.

When it comes to mobile health applications, the possibilities are limitless. The health data collected can be further analyzed by AI algorithms to create personalized care plans. Mobile apps and other wearables can also be used by healthcare providers to ensure patient’s adherence to the care plans by sending out real-time reminders via push notifications or other alarms. 

Take into data security into consideration 

While the applications of patient data collection and its analysis are immense, healthcare data is inherently sensitive in nature. It is also subject to numerous regulations and legislations like HIPAA, HITECH, and GDPR to name a few. While adopting any technology that involves patient data collection, you need to ensure compliance with the norms and establish adequate measures for the security of the patient data collected and stored.

If you are hosting the health data on the cloud, you need to ensure that the cloud hosting provider complies to the data security norms. Special considerations and additional security measures like data encryption, two-factor authentication need to be established to make sure that the patient data collected and stored stays in compliance with the regulatory norms. 

Use other technologies in collaboration with AI

The aim of technology in healthcare is to streamline the collection of health data, ensure its optimum utilization to yield actionable insights, enable collaboration between various stakeholders by facilitating the sharing of data and ensuring data security from malicious attacks. Use of other technology in addition to artificial intelligence can help healthcare organizations in achieving the above-mentioned objectives. 

The pool of data collected can be analyzed via big data analytics to get vital insights into the trends and statistics. Cloud computing has the potential to significantly reduce data storage costs while facilitating remote collaboration at the same time. Use of blockchain in healthcare has the potential to add a much-needed layer of security in relation to storage and sharing of healthcare data. 

Closing words

A combination of AI with wearable technology promises long term ramifications for the healthcare industry. Successful implementation of the same needs to focus on the sensitivity of patient data and ensuring compliance with the security and regulatory norms. 

The technological advances taking place in the healthcare segment is just the beginning. The impact and possible applications that technology will have in the grand scale of things have immense potential.

Rahul Varshneya is the co-founder of Arkenea, a healthcare software company that builds custom mobile and web apps for founder-driven businesses and enterprises. Rahul has been featured as a business technology thought leader in numerous media channels such as Bloomberg TV, Forbes, HuffPost, Inc, among others.

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