Healthcare organizations are facing a deluge of rich data from varied sources such as EMR, text, social media, mobile, images and videos. It is estimated that data is growing at a rate of 50% every year with 9X time growth in unstructured data as compared to a structured one.
At the same time, advances in analytical and computing techniques coupled with a deluge of rich data coming from above-mentioned sources are helping healthcare organizations with better clinical practices, reduce drug discovery time, offer personalized healthcare and develop better hospital engagement models that improve outcomes and add value to both the patients and healthcare organizations.
In short, AI and its related technologies such as Machine Learning, Deep Learning and Big data, etc. are enabling Healthcare organizations that include Hospitals, Biotechnology companies and Pharmaceutical companies to become more efficient, operate with greater insight and effectiveness, and deliver better service than ever before.
AI and its related technologies are touching all areas of the healthcare industry, but there are three areas where AI is making the biggest impact. 1. Value-based care 2. Personalized healthcare 3. Drug trials and discovery.
The key to success in the healthcare industry is to identify the highest opportunities for health improvements at the lowest cost while being safe and effective. AI can transform petascale data into intelligence in real-time that drives efficient and effective care using relevant, predictive, and actionable insights. Further, AI can uncover the opportunities that can lead to lower costs and healthier outcomes, thereby enabling healthcare organizations to realize the true potential of value-based care.
Personalized healthcare is all about segmenting the patients based on disease type and subtype, risk and treatment responses, and other related variables. The key idea behind personalized healthcare is that medical decisions should be based on the individual patient rather than on population averages. AI combined with other related technologies such as big data is now able to pair patient’s individual health data with treatment responses on a massive scale for better medical outcomes for each and every patient.
Drug trials and discovery
Drug discovery can be a long, arduous and costly process. AI and other related technologies can not only reduce costs but can also accelerate many stages of drug discovery and research process. AI and other related technologies have evolved to a stage where they can be applied at all stages of the drug discovery process, but they are primarily effective while applied during designing the drug’s chemical composition and in investigating the effect of a drug at both preclinical and clinical phase for better and effective outcomes.