Remote patient monitoring
Technology and Telemedicine
Telemedicine  is a growing field implementing current technology to improve the reach of medical care. It is often used as a means to deliver specialty care to underserved or remote locations. This has been done through means such as remote stroke assessment  , remote dermatology assessment , and remote monitoring in an intensive care unit (ICU) . As the field of personal health monitoring technology expands, a subset of telemedicine has evolved called Remote Patient Monitoring where patients use technology that directly transmits health data to providers. The data gathered are often referred to as patient generated health data (PGHD) or as a digital phenotype . This means of remote data gathering is ideal for patients with difficulty getting to clinic either due to remote location or health issues. It is most frequently used to monitor chronic health conditions and in the setting of research. The field of remote patient monitoring can be divided into four areas: data generation and collection, sharing or communication data, interpretation, and utilization(1).
Data Generation and Collection
Glucose monitors have improved dramatically in the last few years. Many finger-stick self-monitoring devices can automatically transfer data to a remote storage area such as a phone or online database. Additionally, many people wear a device to monitor their blood sugar around the clock to create for passive data collection, an ideal for remote patient health monitoring. There are several devices for continuous glucose monitoring , , or flash glucose monitoring  which allow for the collection of a robust digital phenotype. While the flash glucose monitors differ from the continuous glucose monitors in that they are not set up to automatically transmit data, the continuous glucose monitors actively push data from the device to designated locations. This can be to the user’s cell phone, a friend or family member, or a physician or other clinician. The allows for real time remote patient monitoring which can alert other people when the users blood sugar is at an extreme high or low.
Digital sphygmomanometers such as the Omron 10 series , LotFancy  Easy@Home , and many others. Digital sphygmomanometers work by measuring a physical oscillation rather than an auscultation with a manual blood pressure cuff. This digital measurement is less accurate than the other means of measuring(2), its convenience has made it such that it is often used as the first means for blood pressure collection even in a health care setting and use at home mitigates problems such as white coat hypertension and can allow for patterns to be seen such as increasing blood pressure in the morning or at night.
Fall detection is generally done via simple accelerometer data. It has become most widely used on the fourth generation Apple Watch . This device was the first apple watch to incorporate fall detection and can be used to transmit the data to emergency services and has even been known to save lives after high speed bike accidents . However, should you have a sibling in her 30s who has suffered the shame of having two simultaneously broken feet, use caution when recommending this technology as it has connotations of elderly fall risks and implications of diminished agility.
Continuous Positive Airway Pressure (CPAP)
CPAP devices are worn to help keep an individual’s airway open while sleeping. These devices were one of the first to monitor and store patient use and reimbursement for the device then became dependent on whether the machine reported that the user was wearing it for the minimum required amount of time .
A 2019 review found that weight was the most common area of PGHD studied(1). This is done both through digital scales , as well as activity monitors  and nutrition logs . Unlike other technologies mentioned here, nutrition logs are PGHD dependent on patient input rather than a digital assessment of the patient’s health status.
There are numerous other devices entering the market right now. Metrics such as heart rate variability, sleep quality, real-time EKG  and cigarette consumption are a few of the data available through various devices. I would assume that this list of what data can be collected will be the part of this page to need updating most frequently, as the data we can gather often outpaces our ability to know how best to use these data.
Sharing and Communicating PGHD for RPM
The FDA requires that certain data standards be maintained when sharing and communicating the PGHD . However, most of the devices are not set up to automatically integrate data into mainstream electronic health records (EHR). For example, continuous glucose monitors allow for downloading data, but in general those data are then uploaded as an attached PDF rather than integrated as discrete data into the EHR. Furthermore, users must have connectivity in order to use many of the devices. One subject in a recent weight study reported needing to place the digital scale outside her apartment and weight herself naked on a patio in order to get proper Bluetooth connectivity. While RPM is ideal for patients in remote areas, these are still the areas most likely to have poor cellular reception.
Interpretation and Utilization
This is the largest area of challenge for RPM. First, many of the datasets generated need to be viewed slightly differently than traditional data. For example, it is known that blood pressure can be different in a clinical setting than when monitored at home. Since most of the recommendations for blood pressure management were created using blood pressures collected in a clinical setting, it is not clear whether the data generated can be interpreted using the established guidelines or if they need to be adjusted for the different collection means before applying established treatment criteria. However there are good data that home monitoring in and of itself can lower blood pressure(3). Health care providers need significant infrastructure for monitoring and utilization of the PGHD. In no small part, this is due to liability. For example, if a patient is being remotely monitored and has a dangerously low blood sugar captured by continuous glucose monitor, what is the clinic’s responsibility and how do they respond appropriately.
Active Applications of Remote Patient Monitoring
Remote patient monitoring requires the technological device, training patients and providers on how to use the device, knowledge of how to interpret the data accumulated and, possibly the biggest barrier, infrastructure set up to receive and monitor the patient data. This final challenge includes both the liability as well as the reimbursement challenge . The Veterans Administration (VA) has been the most successful at establishing widespread utilization so far. The VAs telemedicine infrastructure(4) has allowed for RPM. One of the first studies on RPM for diabetes prevention resulted in significant frustration with the technology itself, however patients who were able to overcome the technical frustrations did demonstrate improvement in glycemic control(5). Studies have successfully used RPM for many applications, including monitoring when a subject has achieved a weight loss goal or evaluating changes in physical activity or diet. Advances in our remote patient monitoring will likely have a significant impact on our ability to implement clinical studies as well as improve patient outcomes in the clinical setting.
1. Nittas V, Lun ; Penny, Ba M;, Ehrler F, Puhan MA, Mütsch M. Electronic Patient-Generated Health Data to Facilitate Disease Prevention and Health Promotion: Scoping Review. [cited 2019 Oct 17]; Available from: http://www.jmir.org/2019/10/e13320/
2. Shahbabu B, Dasgupta A, Sarkar K, Sahoo SK. Which is more accurate in measuring the blood pressure? A digital or an aneroid sphygmomanometer. J Clin Diagnostic Res. 2016 Mar 1;10(3):LC11–4.
3. Cappuccio FP, Kerry SM, Forbes L, Gutknecht DR. Review: Home or self blood pressure monitoring improves clinic blood pressure in essential hypertension. Vol. 10, Evidence-Based Medicine. 2005. p. 40.
4. Darkins A, Ryan P, Kobb R, Foster L, Edmonson E, Wakefield B, et al. Care coordination/home telehealth: The systematic implementation of health informatics, home telehealth, and disease management to support the care of veteran patients with chronic conditions. Telemed e-Health. 2008 Dec 1;14(10):1118–26.
5. Andrews SM, Sperber NR, Gierisch JM, Danus S, Macy SL, Bosworth HB, et al. Patient perceptions of a comprehensive telemedicine intervention to address persistent poorly controlled diabetes. Patient Prefer Adherence [Internet]. 2017 [cited 2019 Oct 17];11:469–78. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28424543
Submitted by Jennifer Rosenbaum