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 Table of Contents  
EDITORIAL
Year : 2022  |  Volume : 24  |  Issue : 3  |  Page : 1-2

Healthcare re-imagined – Is the future already here?


1 Director General Medical Services (Navy), New Delhi, India
2 Cdr (MS) - Research & Training, Integrated Headquarters of Ministry of Defence (Navy), New Delhi, India
3 Cdr (MS) - Health, Integrated Headquarters of Ministry of Defence (Navy), New Delhi, India

Date of Submission30-Apr-2022
Date of Decision01-May-2022
Date of Acceptance10-May-2022
Date of Web Publication01-Jul-2022

Correspondence Address:
Surg Commander (Dr) Sourabh Bhutani
Cdr (MS) - Research & Training, Integrated Headquarters of Ministry of Defence (Navy), New Delhi - 110011
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jmms.jmms_74_22

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How to cite this article:
Chawla N, Bhutani S, Roy K. Healthcare re-imagined – Is the future already here?. J Mar Med Soc 2022;24, Suppl S1:1-2

How to cite this URL:
Chawla N, Bhutani S, Roy K. Healthcare re-imagined – Is the future already here?. J Mar Med Soc [serial online] 2022 [cited 2022 Aug 18];24, Suppl S1:1-2. Available from: https://www.marinemedicalsociety.in/text.asp?2022/24/3/1/347872



Healthcare, as it is practised around the world today is undergoing a significant evolution. Rapid advances in technology are transforming all the aspects of the provision of health care. Two particularly relevant technologies include Artificial Intelligence (AI) and Internet of Things (IOTs) or more specifically, Internet of Medical Things (IOMTs).

John McCarthy established AI as an academic discipline way back in the year 1955.[1] He defined it as the science and engineering of making intelligent machines, especially intelligent computer programs.[2] From its humble academic beginnings, AI has come a long way making a change in the many aspects of our lives today. The applications of AI range from the extensive usage in cloud computing to big data analytics and from data mining for social media content, to the way weather predictions are made. Every industry, every organization worldover is being affected by AI in some way or the other.[3] The industry estimates project that AI industry will grow from 58.3 billion US dollars in 2021 to 309.6 billion US dollars by 2026, at an astonishing compounded annual growth rate of 39.7%.[4] Within this market, the AI-healthcare market itself is projected to reach $194.4 billion by 2030.[5]

It is quite evident that these technologies have the potential to improve the quality of health-care delivery and also save lives. As an example, the incorporation of AI- and IOT-based sensors into motorcycle helmets[6],[7] has the potential to save many lives.

The term IOTs was coined by Kevin Aston in the year 1999.[8] Simply put, it describes the network of interconnected devices, which are connected to themselves as well as the internet, thereby enabling the exchange of data and parameters without a human interface.[9] IOT too is an all-pervasive technology. The present applications include smart warehouses, smart cities, traffic management, and even optimization of energy use. When this technology is used in medical devices, it is known as IOMT. Like AI, IOMT too has wide-ranging applications in health care.[10]

A significant application of these technologies is the development of self-monitoring devices for individuals, more commonly known as wearables. These are devices that the patient can be used to self-monitor the parameters while in the comfort of one's home. A number of wearable biosensors are available which are portable electronic devices that integrate sensors in/or within the human body. These sensors can come in the form of smartwatches, sensors embedded in clothing, headbands, implants, or even tattoos. These devices enable real-time measurement of parameters and thereby enable instant feedback from the patient to the doctor.[11]

Together, IOMT and AI have a synergistic role in transforming health care. IOMT device collects, monitors, and transmits the data, whereas AI is responsible to carry out the analysis, draw inferences from the data and suggests actions on the basis of the data output.[12]

Another aspect of these novel technologies bringing health care to the patient's doorstep is the development of self-help apps. The development of apps has been particularly valuable in the mental health sector, where these apps are seen as very scalable tools to provide mental health care to every part of the world and every section of society.[13] Apps are also enabling geriatric patients in self-monitoring neurological illnesses such as Parkinsonism and stroke and helping improve their quality of life.[14]

As we move from a patient to the hospital setup, it is worthy to realize that the way these technologies are changing the way hospitals function, which is potentially revolutionary. Smart hospitals using AI, cloud storage, and big data analytics have made their way into hospital systems, all for the sole purpose of improving the quality and speed of patient care. Smart ambulances which are connected to the hospital could transmit patient data even before reaching the hospital.[15] This combined with real-time location could enable faster patient reception, automated reception and registration, advance information to diagnostics as well as intimation to the concerned specialists – all aimed toward improving the efficiency of the system and thereby saving lives. Other applications for hospitals include advanced diagnostics, hospital information systems, smart wheelchairs, inventory management, and several other aspects of hospital administration.[16],[17]

Hospitals and health-care establishments are using these novel technologies innovatively for improving public health as well. AI-based technology can screen for diabetic retinopathy in rural areas, thereby bringing advanced health care to under serve areas.[18],[19] The scope of using these technologies in public health includes telemedicine, community-based screening of diseases, assistance of elderly patients at their homes, control of outbreak, and in research. The development of a number of these technologies has been hastened in the COVID pandemic.[20] Contact tracing applications based on geo-position such as Arogya Setu were extensively used during the COVID pandemic in India.[21]

While the growth of AI and IOMT-based technologies in health care is unprecedented, a number of challenges remain. These range from issues such as data privacy and consent, security, encryption to installation and recurrent costs, standardization of technologies, and interoperability of applications and software.[22] On part of the medical personnel, there are issues with respect to the learning curve and acceptance of new technologies.

It is vital for us to understand that while the fields of AI and IOMT sound very promising for the future of health care, we must not rush unguarded. We must draw a balance between accepting new technologies, while at the same time not losing our clinical judgment, human touch, empathy, and the connection with the patient. The machine may be able to provide good solutions based on an algorithm, but it is the doctor who through his mere presence can provide a healing touch to the patient.

The future looks promising, and the medical community should therefore keep an open mind in adapting to newer developments. The doctor may seem irreplaceable in the near future, but these novel technologies can assist the doctors and be an adjunct in making better decisions, making health care safer and improve the efficiency of the entire system. Smart health care of the future may thus be closer than our imagination!



 
  References Top

1.
McCarthy J, Minsky ML, Rochester N, Shannon CE. Proposal for the Dartmouth summer research project on artificial intelligence, August 31, 1955. AI Mag 2006;27:12.  Back to cited text no. 1
    
2.
Mccarthy J. What is Artificial Intelligence?; 2007. Available from: http://www-formal.stanford.edu/jmc/. [Last assessed on 2022 Apr 12].  Back to cited text no. 2
    
3.
How Artificial Intelligence is Transforming the World. Available form: https://www.brookings.edu/research/how-artificial-intelligence-is-transforming-the-world/. [Last accessed on 2022 Apr 11].  Back to cited text no. 3
    
4.
Artificial Intelligence Market Size, Share and Global Market Forecast to 2026. Available form: https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-market-74851580.html. [Last accessed on 2022 Apr 11].  Back to cited text no. 4
    
5.
Artificial Intelligence in Healthcare Market – Global Report; 2030. Available from: https://www.alliedmarketresearch.com/artificial-intelligence-in-healthcare-market. [Last accessed on 2022 Apr 12].  Back to cited text no. 5
    
6.
Internet of Things Enabled Smart Helmet. Available from: https://www.ijert.org/internet-of-things-enabled-smart-helmet. [Last accessed on 2022 Apr 12].  Back to cited text no. 6
    
7.
da Silva K, Sabino M, da Silva E, Gallegos L. IoT Helmet: An Intelligent Helmet for Locating Accidented Bikers. ACM International Conference Proceeding Series; 2021. p. 169-72.  Back to cited text no. 7
    
8.
Kramp T, van Kranenburg R, Lange S. Introduction to the Internet of Things. Enabling Things to Talk: Designing IoT Solutions with the IoT Architectural Reference Model; 2013. p. 1-10. Available from: https://link.springer.com/chapter/10.1007/978-3-642-40403-0_1. [Last accessed on 2022 Apr 12].  Back to cited text no. 8
    
9.
What Is the Internet of Things (IoT)? Oracle India. Available from: https://www.oracle.com/in/internet-of-things/what-is-iot/. [Last accessed on 2022 Apr 12].  Back to cited text no. 9
    
10.
Arora S. IoMT (Internet of Medical Things): Reducing cost while improving patient care. IEEE Pulse 2020;11:24-7.  Back to cited text no. 10
    
11.
Sharma A, Badea M, Tiwari S, Marty JL. Wearable biosensors: An alternative and practical approach in healthcare and disease monitoring. Molecules 2021;26:748.  Back to cited text no. 11
    
12.
Shah R. IOT and AI in Healthcare: A Systematic Review. Issues in Information Systems; 2018.  Back to cited text no. 12
    
13.
Lagan S, Aquino P, Emerson MR, Fortuna K, Walker R, Torous J. Actionable health app evaluation: Translating expert frameworks into objective metrics. NPJ Digit Med 2020;3:100.  Back to cited text no. 13
    
14.
Winberg C, Kylberg M, Pettersson C, Harnett T, Hedvall PO, Mattsson T, et al. Feeling controlled or being in control? Apps for self-management among older people with neurological disability. Disabil Rehabil Assist Technol 2021;16:603-8.  Back to cited text no. 14
    
15.
Al-khafajiy M, Kolivand H, Baker T, Tully D, Waraich A. Smart hospital emergency system: Via mobile-based requesting services. Multimed Tools Appl 2019;78:20087-111.  Back to cited text no. 15
    
16.
Li G, Lian W, Qu H, Li Z, Zhou Q, Tian J. Improving patient care through the development of a 5G-powered smart hospital. Nat Med 2021;27:936-7.  Back to cited text no. 16
    
17.
Kwon H, An S, Lee HY, Cha WC, Kim S, Cho M, et al. Review of smart hospital services in real healthcare environments. Healthc Inform Res 2022;28:3-15.  Back to cited text no. 17
    
18.
Google Works with Aravind Eye Hospital to deploy AI that can Detect Eye Disease | VentureBeat. Available from: https://venturebeat.com/2019/02/25/google-works-with-aravind-eye-hospital-to-deploy-ai-that-can-detect-eye-disease/. [Last accessed on 2022 Apr 19].  Back to cited text no. 18
    
19.
Raman R, Dasgupta D, Ramasamy K, George R, Mohan V, Ting D. Using artificial intelligence for diabetic retinopathy screening: Policy implications. Indian J Ophthalmol 2021;69:2993-8.  Back to cited text no. 19
[PUBMED]  [Full text]  
20.
Gunasekeran DV, Tseng RM, Tham YC, Wong TY. Applications of digital health for public health responses to COVID-19: A systematic scoping review of artificial intelligence, telehealth and related technologies. NPJ Digit Med 2021;4:1-6.  Back to cited text no. 20
    
21.
Basu S. Effective contact tracing for COVID-19 using mobile phones: An ethical analysis of the mandatory use of the aarogya setu application in India. Camb Q Healthc Ethics 2021;30:262-71.  Back to cited text no. 21
    
22.
Richardson JP, Smith C, Curtis S, Watson S, Zhu X, Barry B, et al. Patient apprehensions about the use of artificial intelligence in healthcare. NPJ Digit Med 2021;4:1-6.  Back to cited text no. 22
    




 

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