New Delhi: Telemedicine has existed for years, however, the onset of the pandemic has accelerated its adoption. Driven by the need to bridge gaps in healthcare delivery models, health tech companies are building digital technologies, including integrating telemedicine and AI to tackle the overburden of existing healthcare systems globally. The recent stats indicate this burgeoning need as the global AI in telemedicine market is expected to grow at a CAGR of 26% to reach USD 19.4 billion in 2024 to USD 156.7 billion by 2033. Prasanth Madavana, Co-founder, Fedo stressed the need for innovative ways to prevent healthcare catastrophe later.
Despite this, healthcare is convoluted and complex as chronic diseases continue to become a public challenge. As per the stats, chronic diseases like heart disease and cancer account for 63% of deaths in India. Additionally, these diseases estimate to cost approx. $3.55 trillion to the country, in lost economic output between 2012 and 2030. This requires the adoption of a critical approach to predict disease outbreaks and outcomes.
Transforming chronic disease management
Chronic diseases demand a holistic diagnosis approach and consistent care as delayed diagnoses and fragmented care can lead to unexpected outcomes and rising healthcare costs. Diseases like diabetes, hypertension, and cardiovascular diseases require frequent monitoring and timely interventions. Considering the complexity of such diseases, many patients experience lapses in treatment, while underserved regions struggle with accessibility issues.
However, the integration of telemedicine with AI empowers medical practitioners to overcome these obstacles, providing smarter, scalable solutions. Moreover, the augmented use of AI in telemedicine elevates this experience by automating processes, predicting risks, and offering tailored treatment plans, centered around individual patient needs. Hence, these technologies provide a comprehensive approach to improving patient outcomes.
Telemedicine & AI: Game Changer in Chronic Diseases Management
The predictive nature of AI has the potential for data collection and integration. By gathering patient data from diverse sources such as Electronic Health Records (EHRs), healthcare devices, and patient reports, it provides a holistic view of the patient’s overall condition. In addition, AI is augmented with Machine Learning (ML) capabilities. These models can analyse complex datasets to identify disease patterns in patients, which might not be very evident in traditional methods. Hence, AI and ML can enable early detection, catching a disease at a stage where it can be prevented or managed.
Apart from this, AI is designed to enhance user-centricity across industries. Similarly in healthcare, it focuses on the ease of use and accessibility for all stakeholders including caregivers and seekers. The use of telemedicine with AI focuses on a personalized approach to managing chronic diseases, making it more centric to the patient’s needs.
The integration of these technologies prioritizes patient experience, ensuring adherence to the treatment plan. Offering a personalised approach and experience encourages more active participation from patients by giving them control in their own hands to make the right healthcare choices and turning them into brand advocates.
In addition, telemedicine augmented with AI simplifies access to quality healthcare services by facilitating remote consultations and virtual follow-ups. This approach significantly reduces dependency on in-person visits and allows consistent monitoring from the comfort of patients’ homes. Moreover, telemedicine has a greater impact in rural and underserved areas, where specialized care is often inaccessible or out of the reach of patients. Subsequently, it offers a cost-effective and scalable solution to manage chronic diseases, ensuring timely interventions and better patient engagement.
Adoption of smarter care for a healthier future
In recent years, telemedicine has emerged as a game-changer for meeting healthcare needs, especially for underserved communities and patients who require consistent medical attention. By enabling patients to connect with healthcare providers remotely, the combination of telemedicine and AI elevates patient experience by automating mundane processes, predicting risks, and offering a personalised approach. Henceforth, it represents the future of chronic disease management by addressing the challenges of accessibility, early detection, and patient engagement.
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