The year was 1955. The computer scientist John McCarthy coined the term ‘Artificial Intelligence’. From 1955 to 2005, computer scientists mostly used this term for research purposes.
What was more, they checked if artificial intelligence could be implemented across different industries.
In 2011, Apple introduced ‘Siri’ into the market. Quickly the whole world started thinking about AI to deal with day-to-day activities.
Enter artificial intelligence in healthcare!
A recent example of this is ‘Google Duplex’. It can help you to book an appointment by using AI and ML technologies.
Like other industries, many companies in the healthcare market are investing in AI and ML. This is to enhance the quality of care, operations, and engagement.
Many healthcare IT companies are investing in the tech space. This is to:
Fig 1: Reasons why healthcare IT companies are investing in the tech space
For the healthcare community, enhancing patient engagement has become the topmost priority. AI in healthcare can certainly play an important role in achieving those outcomes!
In this blog, let’s explore why it is important…
Why AI technology is required in patient engagement
As healthcare industry is moving from FFS (Fee For Service) to a value-based system, the patient should be aligned to the central position. This is to get a better quality of service at minimum healthcare cost.
To achieve this alignment, patient engagement tools are vital. They help patients, providers, and payers.
In the last few years, we have observed remarkable progress in patient engagement technology. It has been helpful to solve multiple challenges like access to patients about their patient info, web/mobile based scheduling, and communication with caregivers.
On the other hand, patient engagement still faces many challenges that need to be addressed. Here are some challenges:
- More patient information to capture (habits, behavior trend, and emotional quotient)
- Capturing patient information before appointments though HRA (Health Risk Assessment)
- Not having personalized healthcare education
- Not having personalized care plans and tracking of the care plans
Current patient engagement processes allow patients to participate in care delivery. But this participation is only restricted when the system or app informs them to participate (feed the questionnaire and upload reports, for example).
Moreover, the patient should participate more ‘pro-Actively’ in the care delivery process.
In an ideal scenario, the patient should participate in the care delivery process in the form of suggestions. This can mean sharing their thoughts/emotions/ feelings/symptoms, and feedback about physicians.
You can imagine it like this:
Fig 2: Patient engagement
For the last 5-6 years, the penetration of web and mobile patient portals has increased moderately.
However, the patient data these systems are generating is humongous. What’s more, we are not utilizing it for ‘pro-active patient participation’.
Let us look at how patient engagement has evolved over a period. We’ll also look at how it is going to look soon.
Tomorrow’s patient engagement
While implementing ‘Pro-Active patient Participation’, technologies like AI and ML will be used for data aggregation, data analysis, and extracting deeper insights.
Most of the providers have started online appointment scheduling for their patients. Now, we can use AI and ML to automate the scheduling part, which could be helpful to reduce the admin cost of providers. At the time of scheduling, one can extract detailed patient information through personalized health risk assessment. This is via the use of AI technologies.
In the current patient world, nearly 74% of patients forget their care plan after the doctor’s appointment! To reduce this percentage, health systems should suggest personalized care plans to physicians. These are based on aggregated data from multiple data sources.
Technology acts as a bridge between caregivers and patients to connect patients at the personal level and improve their health. ‘Pro-active patient engagement’ is the way forward to achieve this. It is quite evident how advanced technologies help us to build powerful patient engagement solutions!
In the future, during care plan tracking, personalized AI based patient education will be the key to boost ‘pro-active patient participation’. These advanced patient engagement activities forge a better ‘patient – physician’ relationship.
Explore how we categorized patients and built personalized care plans with GenAI.
Well, it is established that AI and ML is a win-win for every healthcare entity! When are you planning to implement AI-ML techniques to enhance your quality of care? If you would like to find out more, feel free to write to us.
Also visit us at Nitor Infotech to learn more about what we do in the healthcare world.
