The world is getting older. In 2012 there were 562 million people aged 65 and older (8% of the global population). Just three years later, an additional 55 million people joined this group bringing the total to 8.5% of the global population [1]. The aging population is a concern for all countries including the United States, where it has a growing impact on government expenditures, healthcare policies, and social benefit programs like Medicaid and Medicare.

In 2014, a patient reported outcome measurement (PRO) of senior-citizen residences found that 88% of households in the U.S. would like to stay in their current domicile as long as possible [2]. This survey highlights the growing interest of aging Americans to not only live independently, but also comfortably in their own homes. Unsurprisingly, very few Americans reported a desire to live their “golden years” in a nursing home or an assisted-living facility. Thus, we must continue to develop more cost efficient, passive, medical technologies that can enable the aging population with chronic medical conditions to live in their own homes versus assisted-living facilities.

Various types of technology have already been developed and deployed to assist the chronically ill and aging patient population to live in their own home for some time [3]. There are devices that can monitor individuals that live alone and are immobilized, as well as devices that can alert and call emergency responders for on-demand urgent care. Perhaps most interesting are the recent advances in information communication technologies: invasive and non-invasive sensors that can be installed within the home, or directly on the human body for the aging patient population.

The health information captured by these devices can be analyzed and extracted to inform clinical decisions, perform remote monitoring of physical and physiological status, alert emergency responders to medical emergencies, and in the near future, predict or even prevent a medical emergency from happening.

This growth and creation of new health sensors for the aging population is partly due to the steady progress in contactless data exchanges (RFID and NFC), distributed sensor networks, short-range wireless communication (ZigBee and Bluetooth), and universal mobile access (cellular networks and WiFi hotspots). These advancements have allowed the Internet of Things (IoT) for health sensors to flourish [4]. For those that have not encountered this term, IoT is defined as any type of computing device(s) that has the ability to transfer data over a network, without requiring human-to-human or human-to-computer interaction.

A simple, semi-invasive and quasi-passive example of a IoT device is the Apple Watch – it can passively collect information regarding your heart rate and step count without much interaction with its owner. Apple recently introduced their Series 4 Apple Watch with the added benefit of being the first available direct-to-consumer FDA approved device with ECG capabilities [5].

In contrast, a complex, invasive example of an IoT device would be an implanted pacemaker for an arrhythmia, or even a subcranial impulse device for Parkinson’s that helps control motor function.

IoT Health Devices

Although these IoT technologies are rapidly being invented, healthcare professionals are slow to adopt these devices, mainly due to suspicion surrounding their accuracy, effectiveness, and lack of transparent, well-defined processes [6]. Despite healthcare professionals’ slow acceptance, end-users (patients) overwhelmingly approve of (and embrace) IoT technologies for monitoring their health in the home.

To date, numerous research studies have been conducted that have found evidence to support the monitoring of chronic medical conditions such as Hypertension and Coronary Artery Disease [7,8,9] Diabetes Mellitus Type II [10,11] and Chronic Obstructive Pulmonary Disease (COPD) [12,13,14] to name a few. With the use of such IoT wearable sensors, healthcare providers have a new exciting opportunity to continuously monitor disease markers and health behaviors to construct a completely digital, patient-centric story.

The necessity to study how IoT devices can be implemented and utilized has led to the emergence of concepts such as Telecare, Telemedicine, and e-Health [15]. Each of these appeared at different moments of technological development, starting with the integration of the telephone for remote medical appointments and monitoring, up to the integration of wearable and or passive home monitoring systems for continuous tracking.

At VirtualHealth, we have systematically analyzed and acquired knowledge on the various types of devices that can and will be used to collect new streams of patient health information, and the needs of these device companies to link their data with other sources of health information. In doing so, we created a platform that can easily bring together an unlimited number of data fields, into an actionable format that can be easily interpreted by healthcare professionals. To learn more, please visit us at virtualhealth.com

References

  1. He W., Goodkind D., Kowal P. An Aging World: 2015. US Census Bureau; Washington, DC, USA: 2016.
  2. Healthy Aging Begins at Home. [(accessed on 17 July 2017)]; Available online: https://bipartisanpolicy.org/library/recommendations-for-healthy-aging
  3. Mynatt E.D., Melenhorst A.-S., Fisk A.D., Rogers W.A. Aware Technologies for Aging in Place: Understanding User Needs and Attitudes. IEEE Pervasive Comput. 2004;3:36–41. doi: 10.1109/MPRV.2004.1316816. [Cross Ref]
  4. Atzori L., Iera A., Morabito G. The Internet of Things: A survey. Comput. Net. 2010;54:2787–2805.
  5. Comstock, J. Apple unveils Watch Series 4 with FDA-approved ECG. Healthcare IT News. Published 12 September 2018; [(Accessed on 17 September 2018)] Available online: https://www.healthcareitnews.com/news/apple-unveils-watch-series-4-fda-approved-ecg
  6. Sulaiman H., Magaireah A.I. Factors affecting the adoption of integrated cloudbased e-health record in healthcare organizations: A case study of Jordan; Proceedings of the 6th International Conference on Information Technology and Multimedia; Putrajaya, Malaysia. 18–20 November 2014; pp. 102–107.
  7. Bernocchi P., Scalvini S., Bertacchini F., Rivadossi F., Muiesan M.L. Home based telemedicine intervention for patients with uncontrolled hypertension—A real life non-randomized study. BMC Med. Inform. Decis. Mak. 2014;14:52 doi: 10.1186/1472-6947-14-52.
  8. Omboni S., Ferrari R. The role of telemedicine in hypertension management: Focus on blood pressure telemonitoring. Curr. Hypertens. Rep. 2015;17:21. doi: 10.1007/s11906-015-0535-3.
  9. Sieverdes J.C., Gregoski M., Patel S., Williamson D., Brunner-Jackson B., Rundbaken J., Treiber E., Davidson L., Treiber F.A. mHealth medication and blood pressure self-management program in Hispanic hypertensives: A proof of concept trial. Smart Homecare Technol. Telehealth. 2013;1:1–10. doi: 10.2147/SHTT.S49633.
  10. Carlisle K., Warren R. A qualitative case study of telehealth for in-home monitoring to support the management of type 2 diabetes. J. Telemed. Telecare. 2013;19:372–375. doi: 10.1177/1357633X13506512.
  11. Neinstein A., Wong J., Look H., Arbiter B., Quirk K., McCanne S., Sun Y., Blum M., Adi S. A case study in open source innovation: Developing the Tidepool Platform for interoperability in type 1 diabetes management. J. Am. Med. Inform. Assoc. 2016;23:324–332. doi: 10.1093/jamia/ocv104.
  12. Odeh B., Kayyali R., Nabhani-Gebara S., Philip N., Robinson P., Wallace C.R. Evaluation of a Telehealth Service for COPD and HF patients: Clinical outcome and patients’ perceptions. J. Telemed. Telecare. 2015;21:292–297. doi: 10.1177/1357633X15574807.
  13. Whitten P., Mickus M. Home telecare for COPD/CHF patients: Outcomes and perceptions. J. Telemed. Telecare. 2007;13:69–73. doi: 10.1258/135763307780096249.
  14. Dyrvig A.-K., Gerke O., Kidholm K., Vondeling H. A cohort study following up on a randomised controlled trial of a telemedicine application in COPD patients. J. Telemed. Telecare. 2015;21:377–384. doi: 10.1177/1357633X15572202.
  15. Bardram J.E. Pervasive healthcare as a scientific discipline. Methods Inf. Med. 2008;47:178–185. doi: 10.3414/ME9107.
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