Abstract
Health systems are complex organizations with many moving parts. Ultimately, however, each patient views the health system as a place that should address his or her health needs. Increasingly, patients are bringing more information to the care process, adding complexity and potentially both useful and erroneous input to the process. We focus on the movement by the general public to document important daily activities and how this practice may impact an individual's care.
Are you familiar with the notion of the “quantified self”? You probably are familiar with it, but not by that term. The quantified self is the practice of an individual using monitoring devices, apps, self-recorded data, and so on to track, record, and analyze their daily life. Technology often plays a key role in data acquisition, management, and presentation for interpretation. As an aside, Quantified Self Labs is a company that grew out of a blog that focuses on the quantified self movement. The company provides tools and services (including conferences) for those interested in quantified self activities.
The weaving of the Internet into our everyday lives is a clear indication that access to information is facilitating a fundamental change in society. The quantified self takes the model of power from information access and applies it to an individual's self-knowledge. Fitness trackers are an easy and widely popular example of how individuals are tracking themselves and creating large amounts of data. For those who have trouble sleeping, a variety of tools exist that record sleep patterns and brain activity. There are tools for chronic diseases like hypertension, diabetes, and asthma to enable data capture through very little (if any) overt action by the individual. If there is a condition that you are interested in quantifying, search for the condition in the app catalog for your smartphone. Smartwatches are the latest entrant into the quantified self movement. We are following these tools as well.
While chronic diseases are a hugely important problem for the US health care system, the majority of quantified self tools in use today are fitness related. In fact, 1 in 3 US households with a broadband connection have some type of connected health device. As we learn more about the importance of maintaining an active lifestyle, it appears to be a positive indicator that fitness tracking tools are very popular. Calorie tracking tools and health indicator measures like blood glucose and blood pressure values are all being quantified.
If we continue the discussion about phone-based apps, we know that in general more than 20% of smartphone owners have downloaded a medical app. Although referential apps are certainly an important category of medical apps, we know that exercise/fitness apps are actually the most frequently used of all health app categories. Considering all health-related apps, 17% of smartphone users have reported using their health-related apps at least one time per week. Quantifying oneself is not as popular as social media or gaming on smartphones – yet – but the sources we follow indicate that this practice is only going to increase in the coming years.
Our smartphones are creating an environment where tracking is, in many cases, a set-it-and-forget-it activity. While some variations in functionality exist across smartphone platforms, there are core capabilities that are generally consistent across phones from the major manufacturers. Accelerometers and GPS allow us to track the speed and distance of our exercise or similar activities. Bluetooth allows us to connect to the peripheral devices that monitor weight, blood pressure, and blood glucose. The camera can even be used to document physical changes or conditions that relate to our health. In addition to weather forecasting, barometers on our smart phones can determine elevation, an important feature for those who exercise.
Thinking about the data that your patients may begin to record in their quest to quantify their daily lives, we have to wonder just how valuable it is. Certainly, decision making that is based on anything but accurate data can be fraught with undesired outcomes. Evidence-based medicine (EBM) is the gold standard in today's health care environment. The core philosophy of EBM is the use of reliable evidence of rigor to support decision making. Similarly, data that patients may record must be reliable if health care providers or patients are going to use it to make decisions impacting their health.
Although there are hundreds of smartphone-based apps and tools that can help patients quantify their daily lives, the percentage of these tools that have been through US Food and Drug Administration approval or have been clinically validated to provide accurate and reliable readings is small. This is an important point that patients and providers should appreciate. It is also important for enthusiastic patients to realize that their providers may not be very interested in seeing months of data regarding their jogging history, for example. Time spent vigorously exercising and changes in weight and body mass index are likely more useful than number of steps.
We do not want to discourage enthusiastic patients, however. There is a middle ground where the patients' desire to quantify their lives should be supported because of its power to encourage the patients to “get in the game.” At the same time, providers' reluctance to use the data (in many cases) is going to continue to be the reality until the reliability and validity of the data can be proven.
Our current review of the quantified self reflects previous discussions of “big data” and “little data.” The quantified self is little data in action: individuals focus on themselves to collect data that are readily available to them. The purpose of the data is to help the individuals see themselves better; at some point, the individuals may grant others access to their data. What challenges do you see with the quantified self? What about opportunities? The first question was probably easier to answer. We welcome your comments (Brent at foxbren@auburn.edu and Bill at felkebg@auburn.edu).