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RPM’s role in the COVID-19 long haul and a fastly aging population

Lecturer: Flora Maurincomme

Track: Covid19

While researchers and scientists are continuing to understand COVID-19’s long-haul impact as the pandemic drags on, a growing number of studies have demonstrated that people who had coronavirus will have a long road of rehabilitation –– for instance, 76% of people hospitalized with COVID-19 had symptoms 6 month later. From mild symptoms such as fatigue, insomnia, shortness of breath and "brain fog", to long-term respiratory or cardiovascular damages that can cause more severe chronic illnesses, a significant number of COVID-19 patients will require long-term follow-up and monitoring. 

 

Prior to COVID-19, we were already battling a fastly aging population and the prevalence of chronic diseases. Now it’s further exacerbating the situation, with people’s lifestyle changes during the pandemic such as increased alcohol consumption and lack of exercises contributing to cardiovascular diseases, which is globally known as the most common form of chronic illness. Moreover, people have delayed routine monitoring of hypertension, cholesterol levels and other chronic conditions that can have a cardiovascular impact, further exacerbating the situation. 

 

All of these are undoubtedly placing a huge pressure on the already congested hospital resources and associated high cost with in-hospital chronic care. In this presentation, we’ll discuss how health telemonitoring technologies can solve these compounding challenges by enabling remote healthcare: 


 

  • Continuous monitoring of real-life health status 
    • RPM can not only serve as the virtual form of traditional in-person routine check-ups; it can also provide incredible insights into patients’ day-to-day activities and the real-life progression of their health status –– an advantage over conventional hospital-based monitoring. 
    • RPM allows patients with mild to moderate cases to safely recover at home so not to take up precious hospital units which should be reserved for patients with acute and urgent pathologies. 


 

  • COVID-specific rehabilitation 
    • By integrating a suite of targeted sensors for detecting vital signs such as ECG, temperature, respiration, and pulmonary impedance, RPM can effectively detect and monitor COVID-19 patients’ long-haul symptoms and complications. These measurements provide valuable insights for healthcare providers to prescribe personalized therapeutic plans throughout the rehabilitation process. 
    • This is especially important for monitoring COVID-19 patients discharged from hospitals, to eliminate unnecessary readmission. 


 

  • Predicting health deterioration 
    • When integrated with AI predictive analytics, RPM solutions can be very powerful in detecting clinically significant health status changes, so healthcare providers can intervene with treatment changes before acute deterioration events to avoid hospital admission. 

 

The presentation will also discuss important areas to address for RPM to deliver its intended benefits, primarily in patient adherence and data reliability. RPM wearables can take many formats to capture patient vitals, but the key is to make sure the wearables are easy to use and comfortable to apply, in order to encourage patient compliance and ensure quality data intake. 


Language

English

Topic

Vård på distans

Objective of lecture

Inspiration

Level of knowledge

Fördjupning

Target audience

Chef/Beslutsfattare, Omsorgspersonal, Vårdpersonal, Patientorganisationer/Brukarorganisationer

Keyword

Innovativ/forskning

Lecturers

Profile image for Flora Maurincomme

Flora Maurincomme Lecturer

Sales Manager
Chronolife

I work for Chronolife, a French Medtech & Service Provider, to develop partnerships, opportunities and access to markets in Denmark, Finland, Norway and Sweden.

Chronolife is an artificial intelligence company specialized in digital health. We develop remote monitoring and predictive solutions for patients health status, in the form of smart wearables that integrate various sensors and allow data fusion.