Healthcare Big Data:Connected Healthcare’s Mountains of Data


The tsunamis of data generated by connected care will be nearly useless to caregivers without systems that help digest it all. Can the systems and methods already developed to manage big data in supply chain be useful for healthcare?


Recently I attended the 2012 Connected Health Symposium in Boston. I noticed here and in other forums that different people tend to mean different things when they talk about Connected Care / Connected Health. But regardless of definition, one thing was clear, connected care is going to generate the proverbial tsunami of data. So, in order to understand what this data is all about, we start with a definition of what we mean by Connected Healthcare and what are its main data-generating elements. Across the different perspectives I’ve seen, the common thread and essence of Connected Healthcare is continuity and integration of care — that care-givers stay connected to patients before and after visits, whether the patient is in the hospital/clinic, at home, or away. And that care-givers provide continuity and integration of care within an organization (when doctors come and go and when patients move between the various functional departments), and between organizations (when patients receive care from different provider networks and individuals).

Connected Healthcare therefore encompasses the following commonly referred to elements (Note: The first three elements have significant areas of overlap, and provide a foundation for supporting the last two elements):

Source: ChainLink Research
Figure 1 – Elements of Connected Care
  • Telehealth — The remote delivery of healthcare services and information, including remote examination, consultation, diagnosis, monitoring, treatment (such as robotic surgery), and prevention.
  • Instrumented Care-giving Environments1 — Outfitting hospitals, clinics, doctors’ offices, nursing homes, and at-home care with Real-time Locating Systems (RTLS), various sensors, tracking and monitoring devices, and identifiers (e.g. RFID), enabling the precise tracking, coordination, and use of OR and other equipment, supplies, pharmaceuticals, prosthetics, assets, as well as tracking and coordinating the flow of skilled personnel (nurses, specialists, etc.), and the patients themselves. For more on this, see “Technology Integration Can Transform the Hospital and Patient Care Experience
  • Mobile Health — The use of mobile / portable devices for delivering healthcare, including smart phones and tablets, as well as portable monitoring and treatment devices. As illustrated in Figure 1 – Elements of Connected Care, there is some overlap between Telehealth, Mobile Health, and Instrumented Care-giving Environments.
  • Healthcare Provider Internal Integration — Within a single delivery network, connecting together the different facilities, functions, departments, and elements of the patient experience to provide highly coordinated care. This includes tracking and monitoring the patient from the point of check-in to discharge and post-discharge to orchestrate care-giving resources, based on the patient’s needs and current status. This means having the right skilled care-giver available at the right time and place — reducing wait times for patients, while increasing efficiencies in hospitals and clinics. Internal integration can also help tremendously in reducing medical errors, to ensure the correct dosages and timing of drugs being administered, or that the correct procedure is being performed on the correct patient and the correct limb or organ. Internal integration relies heavily on underlying telehealth, instrumented environment, and mobile health infrastructures to facilitate the integration across the delivery network.
  • Inter-provider Integration — The ability to provide more seamless, interconnected care, regardless of which geography or provider network is giving the care. The ability to exchange electronic health information between disparate providers is key.

Each of the above five interwoven elements generates enormous amounts of data. Table 1 below describes examples of the diversity of data generated and/or consumed by each of these connected care elements.

Source: ChainLink Research
Table 1 – Types of Data Generated and Consumed by Elements of Connected Healthcare

The emergence and growth of all these dimensions of healthcare data (telehealth, instrumenting care-giving settings, intra and inter-provider integration) generates a huge range of types and granularity and amounts of data — everything from the moment-by-moment recording of various monitors and sensors, to diagnostic images, precise and detailed recordings of care provided, cost data, outcomes data, and enrichment data. The variety, volumes, and potential uses are staggering. Care-givers already have too much paperwork and too much data. A big challenge therefore is how to absorb all this additional data and make life easier for care-givers and patients, rather than placing yet more burdens on them.

Other industries can also lay claim to dealing with massive amounts of very diverse data, as evidenced by how hot the ‘Big Data’ buzzword has become.2 What can healthcare learn from these other industries about effectively dealing with Big Data? Figuring that out is a tall order.3 In the article “Can Supply Chain Big Data Solutions Be Leveraged in Healthcare?,” we put a ‘toe-in-the-water’ towards answering that big question.


1 RTLS (Real-Time Locating System) is a central element of the Instrumented hospital, but there can be many other sensors as well, such as motion detectors, temperature sensors, RFID readers, door sensors, etc. RTLS is not common in an instrumented home setting, which may have its own array of sensors such as a pressure sensor under the mattress of the bed, various sensors in the bathroom, infrared motion detectors (useful for detecting falls or just measuring activity levels), sensors on pill bottles to detect when medications are consumed, exercise equipment sensors, and so forth. — Return to article text above
2 The amount of electronic data generated by mankind has been growing exponentially since the start of the computing age. For several decades, the amount of data storage per person has doubled every 3-4 years.  Every day, approximately 2.5 quintillion (2.5X1018) bytes of data are created (as of this publication). The rise of “Big Data” as a popular term and concern marks a tipping point, where the volumes of data have become so immense that traditional tools and methods have trouble doing the desired monitoring and analysis.
3 For one thing, healthcare is highly regulated, which places certain constrains on what can be done and how quickly. But that does not mean there are no lessons that can be learned from other industries.

To view other articles from this issue of the brief, click here.

Scroll to Top