Folding in the Internet of Things (IOT)

Technology innovation doubtlessly enables us to provide more data, in real time, at the point of clinical decision-making. Until now, most of this innovation is “internal” HIT and its associated data created in our care delivery organizations, like lab test results, imaging studies or written impressions of a physician’s clinical thinking. This is already a lot of data, but its volume pales in comparison to information from innovative systems and “external” data already beginning to inundate health care delivery. Consider the following emerging technologies and data as examples.

First, in 1999, Kevin Ashton of MIT coined the phrase, “The Internet of Things” (IoT). The IoT is a “network of physical objects…embedded with electronics, software, sensors and connectivity to enable it to achieve greater value and service by exchanging data with the manufacturer, operator and/or other connected devices. Each thing is uniquely identifiable through its embedded computing system but is able to interoperate within the existing Internet infrastructure.” 1  In health care, using the IoT and its associated voluminous data takes many forms. For example, we use fetal monitors, electrocardiograms, and temperature monitors both within and outside our health care institutions to generate and track extensive vital patient health data.

Second, in March of this year, Apple introduced the Apple Watch. This technology joins other wearables like FitBit, Nike+ FuelBand and Jawbone Up fitness trackers. While “wearable computing” including “smart clothing” is still in its infancy, Gartner predicts that the smart clothing market will grow from its very early stages to a multibillion dollar a year market over the next year (i.e., 2016). 2 Given this expected growth, the volume and velocity of the associated technology and data is overwhelming.

Third, social media, (e.g., Facebook, Twitter, Instagram) also generate huge amounts of data. Social media data can transform health care both for individual patients and for population health. For example, Cliff Bleustein, MD, Chief Medical Officer and global head of health care consulting at Dell Services, suggests “Social media listening tools can be set up to search for words or phrases related to asthma. This can give you a sense of the scope of the problem within a population and help you pinpoint individuals who might be at risk for a health crisis. Using air quality data, EHR data, and pharmacy purchase data for asthma related medications and devices, you can see if someone is struggling with asthma, or if there is an air quality issue that could cause a big uptick in asthma symptoms.” 3

HIT and its associated data tsunami have both seen and unseen implications – implications that require revisiting how we train physicians and how physicians provide personalized care with individual patient interaction. Charles Friedman proposed one vision for training future physicians for a data-rich HIT-driven environment. He suggests that by 2020, we will work in settings with ubiquitous EHRs where, “computable data will be increasingly woven into a learning health system so we can study ourselves and improve.” Best practices, like the orders sets mentioned above, will be broadly available through a “knowledge cloud.” This includes physicians working in both “push and pull modes” with physicians trained to query the system, and the system providing advice and recommendations when needed. In such an environment, physicians must have a different mindset. Medical trainees will need training to be “attuned to their own knowledge, with the ability to evaluate what they do know—and what they don’t.” As Friedman suggests, “The emphasis moves from the facts to the scaffolding that organizes those facts.” 4

It is not enough to focus solely on supporting this future data-rich world with HIT innovation. We must also design innovative care delivery. One way of encouraging this wider focus includes creating “innovation labs” such as Kaiser Permanente’s Garfield Innovation Center 5, a “place where clinicians and team members can engage in innovative, hands-on experiential scenarios—well in advance of their adoption in the patient care environment. The combination of people, place, and process creates a unique environment where human-centered ideas are developed and tested in a safe, mocked-up clinical environment.” Here we can test innovations, fail, learn from mistakes and plow insights from failures into the next testing cycle, without overlooking unintended consequences. Each subsequent test cycle removes obstacles and clarifies the next evaluation’s boundaries. By proceeding through these cycles, we move closer to solutions that improve health care delivery, and minimize what Bastiat calls “short-sightedness” resulting in unintended consequences.

  1. Ashton, Kevin (June 2009). That ‘Internet of Things’ Thing. RFID Journal. Retrieved from http://www.rfidjournal.com/articles/view?4986
  2. Gartner “Top 10 Mobile Technologies and Capabilities for 2015 and 2016”, 12 February 2014 G00260239, Analyst(s): Nick Jones
  3. Bleustein, Cliff (November 12, 2014). Using social media to transform health care data integration analytics. The Health Leadership Forum. Retrieved from http://www.athenahealth.com/leadership-forum/using-social-media-transform-health-care-data-integration-analytics
  4. How supercomputers will change med ed, practice (May 2014). American Medical Association (website). Retrieved from http://www.ama-assn.org/ams/pub/meded/2014-may/2014-may-ms_print.html
  5.  What We Do. The Garfield Innovation Center (website). Retrieved on April 9, 2015 from http://xnet.kp.org/innovationcenter/what-we-do.html
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Posted on December 2nd, 2015 in Innovating Health Care IT
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