Device connectivity and access to data are changing every aspect of healthcare. The very way that treatments and therapies are developed and deployed depends on access to dramatically increased flows of information about the human body, via networks of increasingly capable sensors.
Sensors and instrumentation provide accurate and timely data about many parameters of the human body. The data captured by these connected devices enables an increased understanding of how diseases progress and how bodies respond to various interventions.
But these physiological metrics do not exist in isolation, any more than human beings do. They are affected by personal, social, environmental and behavioral factors — and each of these domains provides a new flow of health-relevant data.
Realizing the true promise of this vast flow of data, in all of its variety, requires a new understanding of data management, analytics and decision-making. This new world is different enough from the way healthcare has typically been delivered that even those who are deeply involved in it struggle to keep up.
To demonstrate how this data will transform healthcare, a series of four articles will trace how the data that comes from a specific individual is used in different ways by different parts of the healthcare system, and how improved healthcare knowledge and treatments return to benefit an individual’s and a population’s health.
This initial article looks at the individual as the source of healthcare data — and as its ultimate beneficiary.
Most care increasingly involves not discrete, acute episodes of care but chronic and long-term disease management. The prevalence of these chronic diseases is changing everything about how diseases are understood, treated and managed.
According to CDC, today, 40% to 45% of the American population has one or more chronic conditions, and 30 million people live with five or more chronic diseases. Americans with two or more chronic conditions are responsible for two-thirds of all healthcare expenditures. Further, it is estimated that by 2060 the number of people over 65 will more than double from today, to 98 million, likely increasing the burden of treating longer-term chronic disease.
Patients with chronic diseases continually generate information about their conditions, and this longitudinal data is essential to the coordination of their entire complex care teams. Chronic diseases often result in additional conditions, such as depression, a common comorbidity of chronic conditions, and an impediment to their effective treatment.
As a result of improved understanding of such correlations, information about the individual’s behavioral health status has become increasingly important in treatment decisions, as has information about the individual’s relationship to the people around them.
A large segment of the American population has trouble gaining access to healthcare and other forms of support. Understanding how social determinants of health (SDoH) affect health outcomes is essential to more effective healthcare delivery. Everything from access to a safe place to sleep to interpersonal relationships can play a role, and information about these aspects is another source of data.
For example, the risks of preterm birth are both physiological and socioeconomic. With certain populations, addressing only the purely medical need may result in poor outcomes. A program that uses machine learning to identify mothers at risk of preterm birth has significantly reduced the percentage of preterm births in the high-risk group.
Over time, each individual, whether healthy or already in need of care, will throw off increasing amounts of data. Much of it will come from connected devices, some prescribed, plus the abundance of health and healthcare-related apps that provide consumers with greater insight into their personal condition.
For example, Apple Health™ and other fitness devices allow for monitoring fitness, while the VitaConnect™ Patch and Masimo SPO2 meter are among the many tools available for monitoring health conditions. These devices and others pair with an ever-growing set of apps for health, wellness and nutrition monitoring.
Over time, a baseline of an individual’s physiological indicators such as their heart rate and blood pressure, as well as activity, diet and sleep patterns will develop. The consequences of any clinical encounter and resulting treatment can be viewed within the context of a particular individual’s physiology.
Additional data from clinical encounters, including diagnostic imaging, lab tests, genomics, stress tests and physician notes, can be integrated with that baseline, increasing the ability to predict how this individual may respond to any particular treatment.
But even those massive flows of precise data are only part of a larger picture that includes information about emotional state, social surroundings, economic circumstances, work and physical environment. An understanding of context affects both diagnosis and treatment decisions, and will inform how treatment recommendations are presented, maximizing adherence to essential treatments that might have unpleasant side effects.
Individuals with chronic conditions will likely spend a good proportion of their life managing them. Connected devices and data will allow for a more continuous, participatory, predictive health system, improving quality of life for these patients. Additionally, likely long-term costs associated with care are expected to be reduced, or shift from highly expensive acute interventions to lower-cost, long duration engagements.
Using all pertinent and available flows of information to understand the individual and their health and healthcare needs is essential. Connected devices, consumer apps and the data they generate combine to provide unprecedented visibility into the decisions and actions that lead to health concerns and ultimately disease. Connected devices will enable a more inclusive, participatory, predictive health and healthcare approach. Yet smart devices are only the first step.
When it comes to data generated by connected devices, there is a lot more going on than a short summary like this one can include.
Parts 2, 3 and 4 of this series will examine how the ability to monitor and understand the context of health is bringing hospital-level care back home. All the information that flows into the clinical encounter, including not only patient physiological data, but also the patient’s health history, social context, genetics and individual treatment responses, and how these specific treatments will be created; this starts from patient data, clinical trials and real-world evidence and progresses through the control systems of the extensively monitored and software-controlled pharmaceutical plant of the near future.
This article was written by Rodan Zadeh, Head of Connected Care Strategy within Cognizant’s Digital Business, and Brian Williams, Chief Digital Officer within Cognizant’s Life Sciences Practice.
Also contributing to this article were: David Staunton, Sashi Padarthy and Naveen Nayar from Cognizant’s Life Sciences, Healthcare Consulting and IoT practices.