How Artificial Intelligence Can Take Connected Health to the Next Level

What we have learned over the past year is connected health is here to stay. While it may have been driven by necessity during the pandemic, patients and physicians alike are in favor now that they’ve experienced it. Largely, though, the connected health experience has been limited to virtual visits and remote patient monitoring. They are two key areas of connected health that can have a significant positive impact on the patient experience, but there is more to the connected health experience. Virtual visits are just the beginning of what can be accomplished with connected health technologies.

While physicians’ understanding of the benefits of many connected health services has grown, along with their use, there is clearly more to be gained by adding Artificial Intelligence into the connected health technology stack. Physicians also understand that and, in particular, point to four top areas where they believe Artificial Intelligence can have the greatest positive impact:

  • Saving time and resources
  • Staff and physician job satisfaction
  • Accuracy in diagnosis
  • Patient experience

Not surprisingly, just as they learned the value of virtual visits and remote patient monitoring solutions through use, physicians also expect to see demonstrated proof that Artificial Intelligence can deliver on expectations. As that happens, physicians are prepared to increase their support for and use of AI technologies in their practices. Not surprisingly, the top proof points are tied closely to the top perceived benefits:

  • Improved efficiency
  • Enhanced care quality
  • Ease of use and availability
  • Increased time spent with patients/better patient-physician connection

By now, most people have experienced Artificial Intelligence in some capacity – certainly through their use of Siri, Alexa, or other virtual assistants. Subscribers to Netflix, Amazon, and other digital services also are probably quite used to AI-based recommendation engines that suggest new movies or products based on their previous experiences.

Similar AI tools can be used in healthcare to support the growth of digital health and bring the industry even further towards a truly connected healthcare system. From diagnostics to treatment to patient communication to administrative tasks, AI can support healthcare providers in many ways and drive new efficiencies that can enable providers to spend more time actually treating patients – instead of digging through masses of data, reports, and charts – delivering a better overall experience.

Improved Diagnoses

AI tools can help increase the efficiency and accuracy of patient diagnoses. AI engines can collect information from multiple sources to deliver an assessment, including patient-provided health data, readings taken from devices by providers or through remote patient monitoring, medical images and scans, and physicians’ notes. AI-driven data analyses can deliver diagnoses faster, and can pinpoint specific problems or risks that physicians may have trouble identifying. Because AI-delivered diagnoses are data-driven, human error is reduced, while physicians can respond to patients more rapidly because they don’t have to spend as much time reviewing charts, images, and other data.

Predictive Healthcare

One way to reduce the burden on healthcare providers is to identify health issues early. AI can analyze patient data and compare it to other available data sets to understand potential risks based on patients’ current conditions, medical histories, family histories, socioeconomic and geographic influences, and other information that can be integrated into healthcare databases. It may then be possible to identify patients at risk of developing various chronic diseases and to take preventative action before conditions appear or worsen. Similarly, anonymized patient data can be used by AI engines to drive better and faster analytics for research, to help

Emergency Care

Emergency responders often have to make on-the-spot decisions about triaging patients. Telehealth services can help them to connect easily to physicians to help assess conditions, and access to EHRs can provide additional insight into patient health and conditions, including allergies to medication or previous conditions. AI can add additional support by combining new information with existing data for rapid diagnoses and treatment recommendations, saving critical time. When needed, speech recognition and video technology can help analyze both verbal and non-verbal signs needed to help diagnose conditions, such as a potential stroke.

Administrative Workload

One of the biggest factors contributing to the high rate of burnout is the administrative effort tied to data entry and other similar tasks. Connected health devices and solutions can help alleviate that burden by feeding patient data from healthcare devices – both in-clinic and in-home devices – directly into EHRs. Artificial intelligence can further simplify admin tasks when speech recognition is used to transcribe physicians’ notes into digital records. In addition, natural language processing can allow AI solutions to understand physicians’ notes and trigger additional actions, such as prescription or lab test orders, follow-up visit scheduling, or other necessary actions to treat patients. When medical coding is added to the AI-driven process, much of the manual data entry effort can be offloaded, while also increasing accuracy by eliminating human error.

Enhanced Data Analytics

At the same time, AI can further assist with data-related workloads by running analyses on collected data and driving automated actions as required. For instance, when Remote Patient Monitoring solutions identify that a patient’s health data suggest elevated risk, alerts can be sent to physicians allowing them to intervene. For patients whose activity levels are being monitored, AI can identify when activity is above or below prescribed levels and send reminders to patients to adjust their behavior to avoid conditions escalating to the point where intervention becomes necessary. Or, based on individual diagnoses, AI engines can identify appropriate communications to be sent to patients, such as follow-up appointment reminders, medication information, or other details that can help patients manage their health better, while also reducing the number of times they need to call with questions.

Resource Maximization

AI can help streamline resource utilization based on availability and demand, while setting achievable expectations for patients. This goes beyond the basic scheduling of appointments to additional patient needs, especially where specific equipment or specialists are required. When healthcare providers are part of a connected network, AI can support patient care by understanding resource utilization and directing patients, physicians, or emergency personnel to the best resources for care based on patient conditions, geography, and availability. Likewise, AI engines can help reallocate resources to accommodate patients with more critical needs to ensure all patients receive the best care possible.

Connected health finally got its chance to prove the benefits many have promoted for years are real. But, the virtual visits that dominated 2020 are only part of how a truly connected healthcare system can drive efficiency and better outcomes. By combining human-enabled elements of connected health, like virtual visits and RPM, with AI and machine learning tools, healthcare providers can allow physicians and staff to treat more patients while potentially reducing the part of their jobs the dislike most – administrative work. As a result, both patient and physician experiences can be elevated thanks to more efficient operational processes that can often take time from physician-patient relationships. Ultimately, the result can be better outcomes for patients and increased job satisfaction and lower burnout rates for physicians.

To learn more about how connected health can help drive efficiencies in healthcare delivery, connect with us here.