There is an enormous opportunity to use personalized, and continuously collected health data to positively impact health outcomes, and drive up economic value propositions. We can see a clear path toward technology being able to not only capture more and more detailed biometrics, but also breaking through the barrier of poor patient compliance. This, combined with intelligent and predictive cloud analytics, provides a compelling opportunity for all stakeholders.
To this end, there are some key capabilities that technology can provide. For example, the use of non-ionizing, very low power, electromagnetic wave energy for health diagnostics is one of the ways we are seeing the realization of low-cost, non-contact, yet accurate and detailed medical diagnostics. This is the type of technology that will drive a revolution in early health screening for the masses, and solve many compliance problems. For some applications, this technology can be completely off body, allowing them to be simply built into environments, or as a convenient wearable, or even integrated into the one essential device that has emerged – the mobile phone. For patients in a known disease state, such technology can be augmented with a number of other noninvasive and minimally invasive health sensors collectively providing the deepest of diagnostic and monitoring capabilities.
Mobile Personalized Health Monitoring Ecosystem
An entirely mobile and personalized health monitoring ecosystem built around these capabilities will have a radical impact. With people being able to conveniently and continuously feed their health status to powerful cloud based analytics, we will see the emergence of new healthcare workflows. A distributed health provider network, designed to maximize scarce resources, will be empowered to improve outcomes, lower costs, and widen access. Provider decision-making will be dramatically enhanced through heavily instrumented personalized health diagnostics.
The fusion of information and analytics available to healthcare provider networks, medical device and pharmaceutical firms, patients, and patient advocates will drive a new era in medicine. This fusion will come from many sources as the world marches onwards to becoming more and more connected. The Internet of Things (IoT) will play a key role in providing rich sets of data, enabling comprehensive diagnostic capabilities to advance. With the type of health sensors described above we will realize key abilities, such as:
-
Continuous real-time collection of personal health data:
-
All of the primary vital signs.
-
Detailed diagnostics based on known conditions/risks, such as a blood chemistry analysis or maybe the status of a Pneumonia infection, etc.
-
Access to intelligent analytics based on current and past personal and family health data.
-
Access to rapidly evolving population based health analytics.
-
Access to data from relevant IoT environmental sensors relevant to health.
This new era in medicine will be characterized by a dramatic shift toward preventative measures based on the very early diagnosis of health problems. The ability to provide affordable screening services based on known risk factors or even genetic analysis will be a key enabler. People with known disease states, and who currently have a treatment plan, will have access to continuous health status updates and recommendations; again, driving early intervention to improve treatment efficacy.
Such an integrated, highly convenient, and deeply comprehensive health monitoring system is what we call True Mobile Health. Previous generations of mobile health systems have been flawed due to their limited utility and inherent inconvenience. This next generation system that we envision will finally shift both the underlying economics, and cause the realization of better clinical outcomes.
The Adoption Cycle
For the underlying technologies described above, we actually see adoption being driven by hospitals first. The benefits of non-contact, continuous health monitoring of all primary vital signs is an overwhelming value proposition in hospital care settings. A few examples are as follows:
-
Continuous, Touchless Blood Pressure Monitoring (BPM). Allowing BPM without the need for any contact with patients has enormous value propositions in hospitals. It will mean the elimination of all wires, cuffs and arterial lines. This will drive up workflow efficiency, reduce infection risks, and result in better outcomes in multiple areas. In areas where non-contact is critical, such as burn victim care, and neonatal care, such a capability has clear utility. However non-skin contact BPM offers solutions to unmet needs in many different settings.
-
Pneumonia Diagnosis and Monitoring. The ability to rapidly diagnose the early onset of hospital acquired Pneumonia, then easily and continuously monitor recovery is a massive value proposition. Doing this without having to rely on vigilance from intermittent physical assessments, or using expensive imaging equipment, while the patient is not even aware of the monitoring, is a big win in hospital settings.
Both of these capabilities, among many others, are possible with the type of non-contact health monitoring technology described earlier. Once adopted in hospitals, we will see expansion into clinics, specialists and primary care facilities. The impact on primary care workflows is considerable, but the proven benefits in both outcomes and costs will force system-wide adoption.
A critical driver for adoption will be the avoidance of health information saturation, and a focus on providing actionable and succinct information to the right stakeholders, in the right format, at the right time. For example, the healthcare consumer cannot synthesize various disparate streams of biometric data, and understand deep clinical impacts. The consumer needs to be alerted appropriately for them to take specific and timely actions. The healthcare providers, on the other hand, will be more interested in seeing the underlying clinical data that drives an alert or diagnosis. Payers and Patient Advocates may find compliance reporting very helpful.
Pressure to adopt these new technologies and workflows will come directly from all of the payers of healthcare. Whether it be government departments, private insurance companies, or individual consumers, the economic forces that govern supply and demand will force the adoption of systems that provide far superior value and better health outcomes.
The Impact on Healthcare Economics
We have seen the impetus towards adopting ”pay for outcomes” based medicine grow over the last several years now. A major implementation barrier has been how to effectively incentivize the key stakeholders to adopt this approach, and how to measure performance in a fair and realistic way. Better data and analytics from this new healthcare ecosystem will surely help address many adoption problems.
The biggest economic value proposition comes from early diagnosis and treatment being far more cost effective in many cases. In a recent study on Estimating Cost Savings from Early Cancer Diagnosis (Kakushadze, Raghubanshi, Yu), the economic impact for the early detection of cancer would be $26B/year in the U.S. alone. There are several major disease states and health conditions that would also have multi-billion dollar economic impacts, if diagnosed and treated early. The combination of better length and quality of life for the healthcare consumer, and the extreme positive economic impacts for payers, make the realization of this opportunity highly compelling.
Realizing these economic benefits does have a major impact on healthcare workflows. As described earlier, we expect hospitals to adopt these technologies first. They have the information management infrastructure already in place within their closed ecosystems. The ability to create more efficient workflows in both emergency and critical care settings clearly yields better clinical outcomes and improves the business performance of the hospital through things like better use of scarce resources and care flow optimization. The data from these initial changes will drive rapid adoption throughout the entire hospital care setting.
The broader economic benefits will be realized when workflows change with respect to the management of patients in decentralized settings. Through cost effective screening of patients with known risk factors, the major value of early diagnosis can be captured. The infrastructure to achieve this is available, although it is currently in a highly fragmented marketplace. However, with health monitoring solutions that are truly convenient, and that seamlessly fit with one’s lifestyle, we will finally see the rise of True Mobile Health.
Conclusion
A new generation of low-cost, off-body, wearable and minimally invasive health sensors will be the catalyst for a major change in healthcare workflows. This new generation of sensors is characterized by their convenience and, yet, deep medical diagnostic capabilities. An example of such technology is the use of non-ionizing, very low power electromagnetic waves for body tissue interrogation and real-time organ diagnostics that do not require skin contact. The barrier of patient compliance, for example, is shattered when such technologies can become integrated into mobile phones.
The wide spread availability of personalized, clinically validated, deep health diagnostic information will force major changes in healthcare workflows. This change will be driven by payers finally having a compelling means to systematically drive earlier health problem diagnostics, earlier treatments, and better outcomes – at lower cost. The economic impact is so enormous that the demand from payers will ensure rapid supply as well as the adoption of solutions by patients and providers. In concert with this will be major value propositions for patients in realizing better length and quality of life. Providers will also see workflow efficiency gains, but market forces and/or regulations will also force them to suitably modify their workflows.
The outcome will be a widely connected healthcare ecosystem that is centered around personalized patient needs, and with rapidly improving machine learning and intelligent analytics, we will see clinical decision-making dramatically improve and become more streamlined. Networks of providers will be able to operate telemedicine practices with much higher efficacy than today. Clinicians across all care settings will have highly instrumented patient diagnostic and treatment informatics based on real-time health data. Treatment efficacy and patient safety will elevate to higher levels as closed loop diagnosis-treatment-outcome results enter rapid self-improvement cycles.
Let’s accelerate bringing these new medical sensors, and their supporting information management and analytics ecosystems to market.
