Leveraging AI/ML for Pro-active Patient Participation

In 1955, the computer scientist John McCarthy created the term ‘Artificial Intelligence’. From 1955 to 2005, most scientists primarily used it for research purposes. Moreover, they checked whether AI could be implemented across different industries. In 2011, Apple introduced ‘Siri’ into the market and in no time, the whole world started thinking about different ways of using AI to tackle day-to-day issues. A recent example of this is ‘Google Duplex’ which can help you book an appointment using AI/ML technologies.

Akin to other industries, numerous companies in the healthcare market are heavily investing in AI/ML and cognitive engineering to enhance the quality of care, operations, and engagement. Also, several healthcare IT companies are investing considerably in the tech space to get more data insights, enhance virtual care, and move patients’ risk zone from ‘At Risk’ to ‘Healthy’. Enhancing patient engagement has become the topmost priority for the healthcare community. Artificial intelligence can undoubtedly play a vital role in achieving these outcomes.

Why AI matters in Patient Engagement?

As the healthcare industry is transitioning from FFS (Fee for Service) to a value-based system, it has become imperative for the patient to be aligned with the central position to accomplish top-notch quality of service at minimum healthcare cost. To achieve this alignment, a patient engagement tool which helps patients, providers, and payers, is vital. In the last decade, remarkable progress in patient engagement technology has been observed. This has been helpful to resolve multiple challenges like access to patients about their information, web/mobile based scheduling, communication with caregivers, and so on. On the other hand, patient engagement still entails several challenges that need to be addressed. Some of these are as follows:

• A lot of patient information to capture (habits, behavioural trends, emotional quotient, etc.)
• Capturing patient information before appointment though HRA (Health Risk Assessment)
• Lack of personalized healthcare education
• Lack of customized care plans and tracking of the care plans

The present patient engagement processes allow patients to participate in care delivery. However, this participation is only restricted to when a system or an app informs them to participate (feed the questionnaire, upload reports etc.). Moreover, patients should participate more ‘Pro-Actively’ in care delivery process. Ideally, patients should take part in the care delivery process via suggestions, the sharing of their thoughts/emotions/symptoms, feedback about physicians, etc.

Patient Engagement: Access-> Participation-> Pro-Active participation

The patient data generated by web and mobile patient portals is colossal and is not being utilized for ‘Pro-Active Patient Participation’.

Let’s explore how patient engagement has evolved over a period, and how it may continue to evolve in the near future.

Patient Engagement on the Horizon

During the implementation of ‘Pro-Active patient Participation’, technologies like AI and ML will be used for data aggregation, data analysis and extracting deeper insights. Most providers have started online appointment scheduling for their patients. In the upcoming months, AI and ML can be used to automate the scheduling part, which could help to reduce the admin cost of providers. At the time of scheduling, detailed patient information can be extracted through personalized health risk assessment by using AI technologies. Currently, nearly 74% patients forget their care plans post their appointments with doctors. To reduce this percentage, personalized care plans based on aggregated data from various data sources should be suggested to physicians by health systems.

Technology functions as a bridge between caregivers and patients to connect patients at a personal level and improve their health. ‘Pro-active patient engagement’ is the way forward to achieve this goal. Advanced technologies are clearly beneficial in the creation of robust 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 will add value to the ‘Patient-Physician’ relationship.

Now that it is established that AI/ML will be a huge value addition for every healthcare entity, are you planning to implement AI/ML techniques to enhance your quality of care? If you would like to find out more about Nitor Infotech’s services, feel free to write to us.