How can an AI-based health monitoring system revolutionize the healthcare industry?

More and more industries across the globe and in India are adopting Artificial Intelligence (AI) and Machine Learning (ML) to enhance their operations and functioning. The healthcare industry in India is also turning to AI for improved efficiency and better disease management.

In fact, by 2021, AI application in the healthcare sector is estimated to reach a size of Rs. 431.97 billion, according to a recent report by a leading international body.

AI is a part of what is digital health with its scope and reach, a more comprehensive technological approach to address the rising disparity between the numbers of patients and doctors in India.

According to the same report mentioned above, proper leveraging of AI in the healthcare sector can increase the doctor-patient ratio in India to 6.9:1000 by 2023.

With more and more individuals in India resorting to telehealth services in view of the current health crisis, AI-based health monitoring system holds the potential to reshape the country’s healthcare sector for good.

How does AI benefit the healthcare system?

The deep learning algorithm, a characteristic feature of AI, has proven to be a revolutionizing technological advancement in many fields. It allows systems to amass and decipher complex and substantial volumes of data easily, which may otherwise cost significant resources.

The healthcare industry is one such sector that deals with massive amounts of data concerning patients, diseases, and treatments. Hence, AI fits aptly in this data-driven industry to deliver crucial benefits to everyone involved.
Primarily, AI encompasses five aspects of this industry –

● Diagnostics
● Pharmaceuticals
● Hospitals
● Telemedicine
● Medical equipment and supplies

However, its effect is the most emphatic in diagnosis, analysis of tests, and cost-effectiveness. When considering the impact of what digital health brings, its functioning and services are the most influenced by AI.
Here’s a list of ways how AI-based health monitoring system can benefit individuals at large –

  1. Extensive availability

    One of the most critical issues in the Indian healthcare industry is the lack of proper healthcare in lesser developed, suburban and rural regions. According to a research, 70% of healthcare facilities in India are concentrated in urban areas, which comprise only 30% of the population.

    It puts a large section of the population at a disadvantage when it comes to seeking medical assistance. However, with AI-based telehealth and a surge of internet users in rural areas, more and more individuals are gaining access to quality healthcare services. It dilutes the disproportionate spread of services significantly.
  2. Training of inexperienced professionals

    New medical professionals lack the experience required to provide quality services. It can often lead to inaccurate conclusions. However, with what digital health brings to the fore, individuals can easily gain a comprehensive understanding of different health problems that come with experience.

    With the AI-based health monitoring system, individuals can access a vast reserve of data concerning different medical accounts and conclude thereby. Moreover, experienced doctors can share 3D imagery on the cloud and gain a second opinion on various cases, which provides for better hands-on training of younger professionals.
  3. Early identification of health problems

    Perhaps the most significant benefit of an AI-based health monitoring system relates to its enhanced prognosis ability. Machine Learning (ML) studies the health data available on a patient to provide more accurate insights and predictions regarding at-the-moment and future health issues an individual can face.

    Wearable sensor-based devices play a crucial role in this regard. It monitors every muscle in an individual’s body to detect the possible onset of any disease. That way, it can suggest preventive measures more effectively.
  4. Patient-centric approach

    Integration of Artificial Intelligence in what is digital health will focus the treatments to be more patient-centric. The various chunks of data available on a patient’s health record facilitate curating treatments and drug combinations that are more suited to an individual’s needs.
  5. Reduction of costs

    Treatments will eventually become more cost-efficient when the full capacity of AI is leveraged. Two primary reasons that will lower the costs of treatment considerably are the increased patient-centric approach and a faster diagnosis.

    However, initially, the integration of AI is more expensive for both medical practitioners and patients. Individuals can attend to such expenses efficiently with the help of the Bajaj Finserv Digital Health EMI Network Card. It allows individuals to avail telehealth and in-person medical services without incurring the total cost of it at once.

    Here are some of the features of this financing option –

    ● Individuals can receive best-in-class services at 5,500+ medical facilities in India, spanning across more than 1,000 cities with the digital health card.

    ● Cardholders can pay for any of more than 800 medical treatments with the health EMI network card, which includes both elective and non-elective consultations and procedures.

    ● It extends a pre-approved limit of up to Rs.4 lakh, which cardholders may use to cover the medical expenses of their family members as well.

    ● Individuals can repay the amount over an extended tenure of up to 24 months.

    ● The health card comes with complimentary personal accident insurance cover, and also discounts and deals across different network partners.

    Existing Bajaj Finserv customers do not need to provide any documents during the online health card application. What’s more, the insta-card only involves a minimal one-time joining fee of Rs.707.

    That way, individuals can avail the most advanced services of what digital health comprises and tap the full benefits of AI without incurring any substantial financial burden.

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