The Role of AI in Significantly Reducing Healthcare Costs

According to recent estimations, 20% of healthcare costs are wasted, globally. The fact that this waste includes preventable and rectifiable system inefficiencies, such as care delivery failures, over-treatment, and improper care delivery, is even more concerning. Such inefficiencies can be minimized by technologies like Artificial Intelligence (AI) very competently, ensuring significantly more cost-effective and stream-lined health ecosystems.

This technology has been in debate for a long time now. The potential applications of AI based systems are vast and spread over a plethora of industries, healthcare is no exception. Although the technology has not attained its full potential yet, there are strong evidences directing to a number of ways in which AI can help domesticate healthcare costs.

Healthcare solution providers are moving towards a standard setup to record, analyze, and store healthcare information securely and systematically. This will enable large sets of data to become available for analysis by AI-enabled systems. These systems will allow us to tract patterns following the treatment and also find optimum treatments centered on the patients’ profile. In doing so, AI ensures the right interventions and treatments while empowering clinical decision-making, and creating a personalized line of attack to care. Repetitive, simple tasks such as the analysis of CT scans and certain tests can be done more precisely by AI-enabled systems, decreasing physician error and aiding early diagnosis.

Faster development of life-saving drugs and quicker analysis of patient data in clinical trials are other potential applications of AI, saving billions in money. AI opens up the prospective to truly empower individuals to make improved decisions concerning one’s health. Massive numbers of people across the globe use wearable technology to gather daily data, from their heart rate to their sleep patterns. This data integrated with machine learning can notify people of threat of certain diseases, long before it develops into a critical ailment.

These instances characterize a very small part of what possibilities AI will allow us to unravel. The possibilities can neither be underestimated nor overemphasized. Assistance amongst the public and private areas of the industry stakeholders is required if AI’s potential has to be leveraged to the fullest. ‘Perhaps it’s time to call in the machines!’

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