While telemedicine, digital health, and other novel patient engagement technologies were available prior to the COVID-19 pandemic, patient and provider adoption may have been limited. These technologies have been shown to help regulate health and are here to stay.

Patient engagement technology has become crucial and an essential requirement in the aftermath of the pandemic, as healthcare providers research on how to best keep patients healthy remotely, including care coordination and chronic illness management.

Digital patient engagement tools are becoming more prominent as clients demand user-friendly, customer-first digital solutions to monitor their condition in the same way they do the rest of their lives. The numerous types of patient engagement technologies on the market appeal to a wide range of consumer preferences, and digital platforms are highly adaptable. They can improve the patient experience by delivering consistent care, maintaining lines of open communication with clinicians, and providing access to resources.

Remote Monitoring Devices and Wearables

Remote monitoring capabilities gained new prominence during the pandemic, but they have also been proven to benefit patients who aren’t in quarantine. Patients can use remote monitoring technologies to connect with their physicians as needed and take a more active role in their care.

Remote monitoring devices send data to the electronic health record (EHR) and the care team. Remote monitoring devices transmit data to the electronic health record (EHR) and the care team in the healthcare sector.  They use digital patient engagement tools like mobile apps and SMS text messaging to create a point of communication for patients and providers outside of the work environment.

Fitness trackers and smartwatches have grown very popular because they are the most frequent wearables offered to patients. Wearables empower patients to be more involved in and in charge of their health.

Personalized Health and Predictive Medicine

Personalized treatment strategies based on predictive medicine are already improving care delivery, notably in chronic illness management. To personalize treatment to each patient’s needs, this technology utilizes branching logic or artificial intelligence (Al). Healthcare organizations must expand EHR integration a priority in order to provide individualized patient education, such as communications and targeted messaging.

Al and Machine Learning in Healthcare

Artificial intelligence (Al) and machine learning can be incorporated into EHR systems to automate routine tasks like recognizing unusual health signs or patterns and alerting clinicians to potential health problems. Wearables and remote monitoring enable Al to assist with these notifications from a distance. Deploying AI into an EHR workflow requires an initial commitment of extra time, money, and resources into an EHR workflow. Still, this technology makes up for the initial investment by facilitating a preventative, early diagnosis, and early intervention strategy.