Policy Challenges and Opportunities in the Age of Precision Medicine
We live in an ecosystem where we desire a personalized experience, from music to web series, and the products and services we purchase are often recommended to us based on the data that is collected by these websites or applications.
This ability lets us understand our needs and wants for a better living experience.
Similarly, in the healthcare industry, we can monitor our health and get personalized treatment with the help of artificial intelligence (AI), Natural language processing (NLP), and machine learning (ML) models and algorithms, which tech and healthcare visionaries refer to as AI in healthcare.
AI in healthcare is a promising collaboration, as it challenges the traditional way patients are treated by doctors and healthcare specialists to bring a futuristic clinical and administrative solution. Using modern-age technology, doctors, researchers, and other healthcare providers improve healthcare delivery in areas like preventive care, disease diagnosis and prediction, treatment plans, as well as care delivery and administrative work.
Virtual Care
The shortage of medical professionals and personnel in critical healthcare areas has broadened the need to confront the challenge of delivering quality healthcare services. To curb this issue, AI can be a savior by providing telehealth solutions where physicians can make data-driven decisions by getting real-time patient's health insights and providing clinical decisions to support, thereby enhancing the quality of care.
To monitor the vitals of patient's in an ambulance, healthcare service providers implement Internet of Medical Things (IoMT) sensors to gain accurate data, which is further shared with physicians and other healthcare staff who can analyze and plan the treatment for the patients accordingly.
Patient Engagement and Empowerment
AI in healthcare has immense potential to improve the healthcare sector for efficiency, as this technology can be used in supply chain management, clinical procedures, and administrative processes. By using AI, healthcare sectors can increase patient retention rates and improve patients' relationships with healthcare service providers.
Healthcare service providers can develop ML and AI algorithms to forecast the demand for services during peak events, ensuring optimal allocations and management of beds, oxygen cylinders, and medicines based on availability and needs. By automating these processes and implementing communication mechanisms, healthcare providers can improve the quality of services and reduce unnecessary waiting times for patients.
Care Delivery
Care delivery usually focuses on making AI-driven clinical decisions for disease management for physicians and AI-based diagnostics to assist healthcare staff in making preventive, curative, and palliative care for ailing patients.
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