Chronic conditions are a major concern across the globe.
And here is the proof!
- US healthcare spends almost $1.65 trillion on chronic care
- Approximately 14% of Canadian people are suffering from at least 2+ chronic disease
- Chronic conditions are the leading cause of death in the Philippines
Decoding chronic illness is not a straightforward process, especially when the entire healthcare system has a broken leg.
But, AI emerged as a shining light in the dark tunnel!
So, in this blog, we are going to cover how AI is breaking the barrier in chronic care.
The need for AI in chronic care
Let’s understand this with a quick difference between traditional and AI-backed chronic care approaches.
Traditional chronic care management is time-consuming and a headache for healthcare professionals. The old-age healthcare ecosystem is one of the prior reasons for that.
Furthermore, medical staff are not able to fulfill the exact care needs of the patients due to a lack of transparency in the care approach. As a result, it poorly impacts patients’ care experience and satisfaction while at the same time rising medical costs.
On the other hand, AI enables healthcare professionals to provide a data-driven care approach that is faster, efficient and effective.
What’s more important is that it saves valuable time and operational costs for the healthcare organization.
So, let’s explore it in more detail.
5 ways AI helps in chronic care management
AI makes lives better for both patients and their care providers with solutions such as,
1. Symptom detection:
Telemedicine and remote patient monitoring (RPM) plays a major role in helping AI to detect the early signs of chronic conditions.
RPM devices continuously monitor patients’ vital body signs such as pulse rate, blood pressure, glucose level, oxygen level and much more.
The real-time data is directly stored in the EHR/EMR system.
This is when AI comes into the picture. It analyzes the patterns in a faster and more accurate manner. If the real-time data is unusual, AI-driven systems directly notify the healthcare professional about the symptoms along with an ideal care solution.
2. Preventing disease at an early stage:
This is far away one of the best use cases of AI in chronic care.
AI algorithms analyze the vast amount of data stored in EMR/EHR.
It identifies the potential risk of chronic conditions such as heart disease, diabetes, asthma attack and hypertension.
As per the data, healthcare professionals create an outcome-driven strategy to prevent or stop the chronic disease in the early stage.
The most interesting part here is that AI also supports the medical staff in providing sufficient care solutions based on large-scale clinical and real-time health data.
3. Finding the best treatment:
Data is everything in chronic care management.
In traditional methods, healthcare professionals have to go through large-scale data in order to identify the care needs of the patients. The process is tedious and complex for them along with a high possibility of human errors.
But, AI-driven tech solutions have the answer to it.
It only shows the meaningful data to the care providers which eventually speeds up the care delivery process without any hassle.
4. Personalized care solutions:
Healthcare is transforming.
Personalized care delivery is a major example of that.
Gone are the days when healthcare professionals used to deliver the same care approach to every patient.
Healthcare entities are now focusing more on personalized care solutions as it is improving the care outcomes and care experience under the same roof.
AI, ML (Machine Learning) and DL (Deep Learning) are becoming a helping hand to medical staff. The algorithm understands the symptoms and care reaction patterns easily and supports the care providers in providing personalized care solutions.
5. Uncovering new insights:
Finding the best solutions for patients’ chronic care needs has always been a challenging task for the healthcare industry.
But, AI opens a new door for them in order to thrive with ease.
AI contains large-scale clinical, research, and health data.
It helps the healthcare organization or drug development sector to analyze the various patterns of symptoms, drug reactions, treatment and many other things.
The data assist them in improving the care approach and medication strategies to help the patients in overcoming chronic conditions without adding any complexities to their well-being.
So, these are some of the use cases of AI in chronic care.
AI in chronic care: Future scope
AI is still in the development stage.
But the future is promising for AI in chronic care management.
Healthcare organizations are implementing AI in their care approach in order to save clinical hours and stay on top of patient care experience, outcomes and safety.
It will also help in reducing the medical costs for the treatment.
USA, Canada, the UK and the Philippines top the list when it comes to poor access to care and high cost.
The Philippines is also showing more interest in AI-powered care solutions as it is the only underdeveloped country in the above-mentioned list.
AI holds the potential to elevate the care efforts in chronic care management.
Healthcare entities are now providing AI-backed chronic care management in order to make lives better for the patients.
Custom healthcare solutions are now on the rise as more and more healthcare organizations want to implement health tech systems in order to break the costlier and time-consuming barriers.