The use of artificial intelligence (AI) and machine learning technologies has had a tremendous impact on the consumer experience over the past few years. Most people are unaware of the role of AI and machine learning in their streamlined experience, but now expect the convenience of these technologies in their shopping, banking, and other consumer interactions, including healthcare. As these technologies have improved and grown in adoption, the rate at which that change occurs is rapidly increasing and consumer expectations have followed.
Helping to drive that change is the fact that the modern consumer is now comfortable with having a powerful communication tool in the palm of their hand. According to Pew Research, 97% of Americans own a cellphone of some kind; 85% of Americans own a smartphone, a number that was only 35% just ten years ago.
The expectation of the patient experience and what it means to be engaged and communicated with has changed as well. Consider that, according to the recent Pega Systems 2021 Healthcare Engagement Survey, 63% of patients agree that they would switch doctors due to poor communication or engagement.
So, while patient engagement has long been at the core of the care journey, the days of traditional pamphlets and brochures is quickly fading as AI and machine learning models, driven by big data, allow for an improved experience.
How can you harness the power of artificial intelligence and smart technologies in your patient engagement strategy? Here are three areas where AI and machine learning can make a difference.
Truly Personalized Communication with Every Healthcare Encounter
It is no secret that the key to engaging patients is communication tailored to their specific needs. However, a significant portion of the “personalized” messaging used today is based on high-level assumptions with minimal differentiation across populations – it isn’t very personal at all.
The manual process of analyzing and evolving these campaigns for patient groups and individuals takes time, placing additional workload on the analytics and clinical teams. While this manual approach can yield results and be effective, the opportunity that machine learning presents is astounding.
For most organizations the starting point for any personalized patient communication strategy lies with a core set of messaging protocols or pathways, either previously created or developed as part of the project launch. But what if, with the power of machine learning, you could quickly scale and automatically deliver a wide array of data-driven message options right from the start?
AI and machine learning are empowering organizations to deliver healthcare that is on par with everyday consumer experiences by testing various messages to learn how, what, when, and where their patients engage with information. These technologies are facilitating engagement strategies that account for a range of alternative patient needs to successfully drive adherence with the medical plan of care and improve outcomes.
Understanding Patient Behavior
Automated patient engagement initiatives allow healthcare providers, payers, and life sciences organizations to efficiently consume a massive amount of information. With so much data at your disposal, traditional methods of analysis to then adapt and evolve your strategy could take months and significant internal resources.
A patient engagement strategy driven by machine learning can quickly take these thousands of data points, as well as historical data across millions of patient profiles, to maximize engagement and outcomes.
The value of machine learning applies to both broad and granular findings. For example, AI can know that a patient with hypertension in a particular demographic profile, in a particular geography, will respond more favorably to a casual text than a more proper salutation. And if a patient doesn’t engage with the first two text messages, a link to a video message has a higher likelihood of getting their attention than a chat prompt. Machine learning also enables the automatic selection of a video from an entire library based on previous patient engagement behavior.
At the end of the day, the goal of using technology in healthcare is to provide a more personalized, effective, and caring experience for patients. Our current health system faces numerous challenges such as inefficient hand-offs, gaps in care, endless phone tag, unclear patient expectations, and many more.
Forward thinking organizations are solving these inefficiencies by taking a more data-driven and effective approach to patient engagement with AI. Twistle by Health Catalyst harnesses data across millions of touch points and patient records to identify disruptions in workflow, engagement challenges, and areas of opportunity for performance improvement. Smart communication pathways with personalized messages are then used to drive patient activation and avoid potential barriers to care.
If you’d like to learn more about how Twistle by Health Catalyst is using Smart Pathways to better engage patient populations, contact us today.