Remote Patient Monitoring & The Impact Of Data Analytics
6 min read

Remote Patient Monitoring & the Impact of Data Analytics

Telemonitoring has come a long way from the first pilot remote patient monitoring program. As data analytics rises to prominence, its potential to impact the future of remote patient monitoring is unmistakable. What exactly should the healthcare industry expect, and what limitations should they keep in mind? 

Currently, the United States, with $20.8 trillion in GDP, spends close to $4.01 trillion on health services. A substantial portion of this has been traced to hospital care. One of the keys to reducing costs and the pressure on health care providers, especially during this pandemic, is the effective use of remote patient care and data analytics.  
In this article, we will discuss the role of data analytics and how it ties to today’s remote patient monitoring requirements.

Remote patient monitoring today

Telemonitoring, otherwise known as remote patient monitoring, involves the transmissions of symptom scores and vitals directly to healthcare providers via automated electronic systems or web-based and phone-based data entry. It enables effective monitoring of patients outside of conventional clinical settings, increasing access to care while decreasing healthcare delivery costs. 

The process minimizes manual recording of patient details such as heart rate, blood pressure, oxygen saturation, weight, electrocardiogram (ECG), body temperature, respiratory rate, and blood glucose levels, among many others. It relies on interactive television-based systems, mobile phones, PDA devices, and even connected gadgets like smartwatches to send patient data directly to doctors for review.

Types of monitoring systems

Telemonitoring systems can be divided into three categories:

  • Non- reactive telemonitoring systems – these are solely meant for data collection purposes, e.g., event recorders.

  • Partial reactive telemonitoring systems – they work together and transmit data under a delayed analytic and decision-making structure, e.g., only within office hours.

  • Reactive telemonitoring systems – these systems operate on continuous analytic and decision-making infrastructure, integrating both invasive and non-invasive data.

Data analytics in healthcare

Data analysis involves the inspection, cleansing, transforming, and modeling of data to drive the discovery of useful information. Health data analytics, sometimes referred to as clinical data analytics, involves extrapolating actionable patient data insights. Today, it enables real-time decision-making in remote patient monitoring and care.

Which data is used?

Typically, patient data is sourced from electronic health records (EHRs). Heterogeneous sensors and physical activity sensors in remote monitoring medical devices and other smart devices record blood pressure, weight, blood glucose, and more. Around 42% of US consumers use digital tools to measure fitness and track health-improvement goals; hence third-party data is also used in the analysis.

The AppWell.Health Accelerator Platform

Data analytics models in healthcare

Health informatics is a fusion of medical knowledge and mathematical/computational models. Configurations are made to monitor daily living activities for patients with conditions like heart failure, dementia, diabetes, Chronic Obstructive Pulmonary Disease (COPD), and more. Important models include the readmission prediction model for reducing medical costs for re-admission and nursing.

Benefits of real-time data monitoring

Preventative patient care

Predictive analytics allows doctors to predict which patients are likely to develop complications by comparing real-time patient data from monitoring devices to medical baselines. Preventing avoidable harm in discharged patients can help safeguard their health. The same can be said for those with chronic conditions.

Cost reduction

In its findings on telemonitoring, a Goldman Sachs report estimated over $305 billion in healthcare costs could be realized from telemonitoring data analytics. Below are examples or practical applications to reduce healthcare costs through telemonitoring data analytics:

  • Treatment of critical conditions

    Data analytics allows for more cost-effective monitoring for conditions like heart disease, asthma, and diabetes.
  • Investment in bed capacity

    The strain on hospital resources could be eased if post-surgery hospitalization could be safely cut short through remote monitoring.
  • Prenatal care

    High-risk pregnancies can be effectively monitored from home settings, reducing hospitalization periods, and costly referrals.

Designing a healthcare data strategy

A data strategy determines how healthcare data is to be consolidated and utilized. This covers both technical and ethical standards on the usage of sensitive data, including:

  • Scale
  • Type of data
  • Business objectives
  • Security
  • Compliance

Telemonitoring Use Cases 

  • Personal mobile devices for remote monitoring

    Professor David Bates of Harvard Medical School and chief of the Division of General Medicine at Brigham and Women’s Hospital in Boston developed an idea for physicians to use accelerometers in smartphones to track patient movements post-surgery. Data analytics would play a significant role in flagging patients with decreased activity flagging deteriorating conditions.
  • Customized monitoring systems

    The “Care Beyond Walls and Wires” program in the Northern Arizona Healthcare system enables remote monitoring via a mobile application and customized medical devices appropriate to the patient’s condition. According to program administrators, savings per patient were estimated to have reached $92,000 within six months for the first 50 patients, and hospitalization rates were also lowered. 


With data analytics seeping into the healthcare industry, there is an enormous collection of patient information. This comes with a plethora of benefits. According to recent research, each patient can save up to $8000 in healthcare costs annually, and the US healthcare industry can save hundreds of billions of dollars. Clearly, there is still a lot of untapped potential in the application of data analytics in healthcare. We are just getting started.

At AppWell Health, our team is excited to be a part of technology advancement within the healthcare industry. We are in business to help people live better lives through better healthcare and are honored to help, even if in a small way, to contribute to the improvement of people’s lives. 
For companies looking to implement remote patient monitoring, AppWell Health provides an Application Accelerator Platform that can help save months of time and money implementing such solutions. Contact us now.

About us: AppWell Health is a trusted software development partner. Combining industry expertise, software development, cybersecurity, and design to craft unique healthcare product solutions. We help our clients build competitive healthcare software products. If you have any questions, please drop us a line at any time. 

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About AppWell.Health

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AppWell Health creates well-focused healthcare technology. Combining over 20 years of healthcare industry expertise, software product development, cybersecurity, user-centered design experiences, and modern data strategy.

We help healthcare product development companies execute their vision, navigate product design decisions, increase speed to market, create beautiful user experiences, and maintain highly secure environments.

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