How the Internet of Things will disrupt traditional healthcare
- Posted on June 27, 2016
This article originally published in Health Data Management.
There are occasional moments in the evolution of business and technology that offer opportunities to re-think the status quo and fundamentally change the way business is done. When the application that intersects business and tech is so compelling that it alone can justify platform adoption, we sometimes call this a “killer app.” The irony of the term “killer” in the health care context aside, distributed health just may be the killer app that drives Internet of Things (IoT) adoption in health care.
Distributed health is the idea that by physically de-centralizing health care services we can provide better care, with greater patient satisfaction, and do so more efficiently. The core hospital environment is very good at providing intensive, highly specialized care for acute conditions, but is inefficient at managing preventative and chronic care. Accordingly, there is a growing trend to manage these care modalities outside of the traditional hospital-based environment. One of the key differences between the traditional and distributed models is the location of patient data collection. In the traditional model, data collection and decision making are co-located. In the new model, data collection will come from the distributed patient “endpoints” and drive decisions and actions at a centralized agency.
In the past, this data collection and transport challenge made distributed health a relative non-starter. Creating the required infrastructure was simply too hard and too expensive, no matter how compelling the business case for a shift in the care model. Enter the IoT. At its most general definition, IoT is a collection of distributed devices, the networks to connect them and the software that enables the devices to collect and exchange data. In the health care context, the devices are remote health monitoring devices which can perform a large and growing number of functions. Healthcare IoT devices can be as simple as activity trackers or smart scales, or more specialized devices like blood pressure sensors, pulse oximeters, and glucometers. Complex devices like pacemakers and home dialysis machines and even social networks will also be part of the healthcare IoT. This IoT infrastructure enables a wide variety of scenarios such as post-discharge and chronic care tele-monitoring, care plan management, medication adherence, coaching and numerous other scenarios that are only now being imagined.
So, it seems clear that IoT can definitely help make distributed health real. But can distributed health be considered a killer app? Is there a special synergy that elevates its potential from interesting to compelling? The answer is yes, and the special synergy is analytics.
Consider this: first, all of the device data flowing through our networks doesn’t do any good by itself. It needs to be acted upon intelligently, in the correct context, and with as much automation as can be safely applied. Second, the IoT is fundamentally a cloud capability, and any significant IoT implementation will ride on one of the major cloud platforms. These platforms all support big data, machine learning and streaming analytics – a very powerful set of tools providing the advanced capabilities that will allow us to truly bend the cost curve through intelligent population segmentation and prescriptive analysis. Third, to tie it together, once the data is already collocated in the cloud with analytics tools, the job of building out the analytics capability becomes dramatically easier. For example, adding a threshold monitor to a data stream can be done with a few lines of code, or invoking powerful machine learning capabilities is as easy as calling a service. In short, the IoT infrastructure that moves the low-level data around so well is also extraordinarily well-positioned to support the analytics requirements of a distributed health system. One infrastructure, multiple capabilities. That is synergy; a sweet intersection of IoT, cloud, and analytics addressing a pressing need with manageable complexity in development, deployment, and operations.
Imagine a case where a patient has a history of congestive heart failure and is exhibiting signs of an oncoming crisis. With distributed health and the IoT, we might detect this with a smart scale that detects rapid weight gain and head off the crisis with a phone call reminder to take the prescribed diuretic medicine. Without it, we could face all of the trauma and expense of a full-blown heart attack. Can we afford not to have this capability?
Health care is evolving rapidly in response to regulatory, financial and technology forces. Moving toward distributed health offers efficiencies and improved care. Using the Internet of Things to support distributed health not only provides us with a ready-made infrastructure, but also folds in the advanced analytics capabilities to truly make this killer app a lifesaver.