A featured contribution from Leadership Perspectives, a curated forum for enterprise technology leaders, nominated by our subscribers and vetted by the CIOApplications Editorial Board.

University of Southern California

The Evolving Internet of Things (IoT) in Healthcare

The healthcare industry is approaching another technology cross-road. As technology continues to get smaller, cheaper and faster, the standard practice has become to make devices, tools, and just about anything else “intelligent”. At the same time, networking itself is becoming faster, more pervasive, and less expensive. Finally, software systems, which include databases, artificial intelligence, man-machine interface systems, and cloud services, are becoming increasingly more capable. Together, progress in each of these is having a compounding effect on healthcare delivery today and may ultimately change how healthcare providers interact with patients tomorrow.

Generally speaking, most technology driven advances tend to occur in compartmentalized and independent bubbles; progress achieved in one sector serves as an enabler for progress to be made in another. Properly implemented, technologies like the smartphones, EHR (Electronic Health Record), and even WiFi have allowed the healthcare industry to improve the level of care for patients, efficiencies for administrators, and returns for shareholders. However, in some cases, we limit the potential gains technology could offer by looking at these domains as compartmentalized disciplines.

For example, building an automated inpatient monitoring system for the hospital may improve operating efficiencies while improving patient care, but more could be accomplished if data from other administrative domains and consumer devices could be integrated to create a more holistic perspective.

Capitalizing on this untapped data to bring incremental value to the healthcare industry is exceedingly difficult when these systems are run by different administrations who have made independent solution purchasing decisions. Further, integration complexity problems can be expected to increase dramatically as the industry continues to shift to data-driven patient management paradigms. Consider a medical device developer who has created a next generation device that generates a plethora of patient monitoring data. Practically speaking, it is almost impossible for an IoT device developer to understand all the different ways the data can be used by a healthcare professional and limitations are imposed when the device is coupled to a specific application designed to support targeted functional need. If, instead, data collection devices were independent from applications, a single device could drive many different diagnostic applications and the issue becomes one of connecting data generators with data consumers. Concepts like VNA (Vendor Neutral Archives) have begun to move the industry in the right direction by allowing medical images to be filed with EMR systems for independent access by various applications, but this concept needs to be extended to include other IoT devices as well.

Given the lack of an IoT VNA, todays practice tends to consider an IoT application and the associated IoT devices as a complete system. This practice tends to couple IoT devices to specific applications. However, by linking devices to applications, the net effect is to create a series of IoT application silos that are individually managed. Operationally, this is a complex proposition because staffs have to be dedicated to each silo or staff members need to become operational generalists that provide basic support to a larger number of applications. This same siloed architecture also tends to limit the healthcare professional’s ability to leverage data across a broad infrastructure. If certain applications are only aware of a limited number of IOT devices, it may be necessary to duplicate IOT device deployments if a deployed device is incompatible with a new application.

Some IOT application providers have attempted to solve this dilemma by creating application layer APIs which allows their application to link with another, as long as the other application is willing to accept data from a third party. This creates a manageable hierarchy as long as the number of applications remains small. However, such an architecture begins to operationally suffer as the system scales to support a larger number of applications. In addition, because the connectivity is dependent on the behavior of the applications, each application can become a reliability/ performance choke points. Such stop-gap measures can be expected to proliferate until a VNA-type vision can be applied to healthcare IoT.

While VNA philosophies can be used to break the IoT application-device silos that are appearing, they will likely not be able to incorporate consumer-targeted medical data.

The articles from these contributors are based on their personal expertise and viewpoints, and do not necessarily reflect the opinions of their employers or affiliated organizations.