AI and Remote Patient Monitoring: Working Together for Higher Quality Care
During office visits, providers spend valuable time with patients to assess their conditions, understand how they are progressing, and make amendments to treatment plans. While in-person visits are incredibly important, they capture a moment in time, and, often, don’t paint the whole picture. Although healthcare providers can use the information they gain during a visit to develop an effective treatment plan, what happens in the day-to-day lives of patients plays a disproportionately large role in what types of outcomes they can expect.
Artificial intelligence can understand the clinical and socioeconomic factors influencing and driving risks across individuals and the communities they live in, recognize patterns, predict trajectories, and organize data with great speed and accuracy. Remote patient monitoring uses devices to continuously collect vitals, other patient-specific data points, and information about how an individual’s condition may be progressing. Together, AI and remote patient monitoring, can be powerful tools to give providers insight into the day-to-day factors that may be impacting an individual’s health.
How AI Enables Better Remote Patient Monitoring
Clinical AI can be leveraged to yield more successful remote patient monitoring programs before they even begin. Advanced algorithms can analyze large data sets like clinical, socioeconomic, and experiential data for a more holistic view of an individual. Based on this analysis, stratification can occur to identify not only risk levels, but to gain a better understanding of which individuals would respond most optimally to remote patient monitoring.
Once the appropriate patients are identified they will need to be enrolled in the remote monitoring program. Again, AI can step in and make recommendations on what will work best to get patients activated and engaged. Once enrolled, providers will begin to continuously collect data from patient devices as well as patient reported information like symptoms and pain levels. Where AI and patient monitoring are used in harmony, these can act as additional data sources to further refine and personalize the patient experience. As remote monitoring data comes in, AI systems will continue to stratify patients on a more granular level, making data more actionable for timely interventions. This collaboration between AI and remote patient monitoring creates a self-sustaining cycle in which tools become more reliable and more accurate with increased usage (1).
AI and Remote Patient Monitoring in Action
Both clinical AI and remote patient monitoring offer value on a standalone basis but enabling remote patient monitoring with AI insights capitalizes on that value. Some of the benefits of this collaboration include:
Improved Patient Outcomes | When it comes to making important decisions, more data is definitely helpful. The continuous collection and analysis of patient data provided by AI-enabled remote patient monitoring solutions ensures that providers can make the best possible treatment decisions for their patients. In addition to more effective treatment decisions, providers can also keep a close eye on the trajectory of their patient’s conditions and make more timely interventions to avoid readmissions and ED utilization.
Personalized Care | The collaboration of AI and remote patient monitoring is providing our industry with, perhaps, the most holistic view of a patient than we have ever had. With so many patient data points we are able to create person-centered solutions. AI allows us to understand individuals not as patients, but as people, with unique clinical, socioeconomic, and experiential factors impacting their health. Taking all of this into consideration, technology can empower “sticky” experiences that fit the preferences and needs of the individual user without manual effort from the clinical staff. This level of personalization is a proven key to success for both the patient and their provider.
Increased Revenue and Reduced Healthcare Costs | Perhaps the most common application of AI-powered remote patient monitoring is amongst the chronic disease population. Chronic diseases are the leading cause of death and disability in the United States, and the leading driver of the nation’s $3.8 trillion in annual healthcare costs (2). Leveraging this technology to reduce avoidable admissions, lower ED utilization, increase staff efficiency, and optimize healthcare resources is a big step towards helping to cut that healthcare cost. Additionally, CMS continues to expand its codes to better support those implementing remote patient monitoring for more reimbursement opportunities.
Is your organization ready to embrace this level of innovation? Mozzaz can help you decide. Contact us today to set up a “readiness assessment” where we will engage in a conversation around the key clinical and organizational elements of a successful digital strategy. Contact us today!
(1) Socially distanced care: The need for AI-Powered patient monitoring. (2021). MedCity News. Retrieved from https://medcitynews.com/2021/03/socially-distanced-care-the-need-for-ai-powered-patient-monitoring/?rf=1
(2) About Chronic Diseases. (2021). CDC. Retrieved from About Chronic Diseases | CDC
