How the Internet of Things will disrupt traditional healthcare
The growing number of connected devices, when paired with analytical capabilities, will help improve care for patients and prevent expensive care interventions.
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 can justify platform adoption, we sometimes call this a “killer app.”
The irony of the term “killer” in the healthcare context aside, distributed health just may be the killer app that drives Internet of Things adoption in healthcare.
Distributed healthcare is the idea that by physically de-centralizing healthcare 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 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, the challenge of collecting data, and then transporting it to where patients might be located (i.e. outside the walls of a hospital) 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 was for a shift in the care model.
Enter the IoT, a collection of distributed devices, the networks to connect them, and the software that enables the devices to collect and exchange data.
These remote health monitoring devices 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 such as blood pressure sensors, pulse oximeters and glucometers. Complex devices such as pacemakers, 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 the IoT can definitely help make distributed healthcare real. But can distributed healthcare be considered a killer app?
Consider this: device data that flows through our networks doesn’t do any good by itself. It needs to be intelligently interpreted, 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 that provide advanced capabilities for truly bending the cost curve. This could be done through intelligent population segmentation and prescriptive analysis.
After 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 well-positioned to support the analytics requirements of a distributed health system.
Imagine a case where a patient has a history of congestive heart failure and is exhibiting symptoms. A smart scale could detect rapid weight gain, or a phone alert could remind the patient to take the prescribed diuretic medicine before crisis strikes. Without it, he could face the trauma and expense of a full-blown heart attack.
Healthcare is evolving rapidly in response to regulatory, financial and technology forces. Moving toward distributed healthcare 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.
The irony of the term “killer” in the healthcare context aside, distributed health just may be the killer app that drives Internet of Things adoption in healthcare.
Distributed healthcare is the idea that by physically de-centralizing healthcare 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 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, the challenge of collecting data, and then transporting it to where patients might be located (i.e. outside the walls of a hospital) 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 was for a shift in the care model.
Enter the IoT, a collection of distributed devices, the networks to connect them, and the software that enables the devices to collect and exchange data.
These remote health monitoring devices 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 such as blood pressure sensors, pulse oximeters and glucometers. Complex devices such as pacemakers, 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 the IoT can definitely help make distributed healthcare real. But can distributed healthcare be considered a killer app?
Consider this: device data that flows through our networks doesn’t do any good by itself. It needs to be intelligently interpreted, 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 that provide advanced capabilities for truly bending the cost curve. This could be done through intelligent population segmentation and prescriptive analysis.
After 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 well-positioned to support the analytics requirements of a distributed health system.
Imagine a case where a patient has a history of congestive heart failure and is exhibiting symptoms. A smart scale could detect rapid weight gain, or a phone alert could remind the patient to take the prescribed diuretic medicine before crisis strikes. Without it, he could face the trauma and expense of a full-blown heart attack.
Healthcare is evolving rapidly in response to regulatory, financial and technology forces. Moving toward distributed healthcare 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.
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