Connected health is a healthcare model that focuses on delivering proper healthcare services and the transfer of data remotely, rather than in-house monitoring of patients in healthcare facilities.
Connected health devices help merge the gap between people’s daily activities and the healthcare professionals serving them.
The most important innovation with connected health, aside from the ability to provide health services from a distance, is the big data that it allows access to.
The Three A’s
There are three A’s related to data collection in the health industry: amount, accessibility, and accuracy. All three have increased significantly with the rise of connected health.
With connected health, a larger amount of data is now available. Wearable devices are able to transfer data to the cloud, allowing your doctor to monitor vital functioning and performance levels 24 hours a day.
No longer will your doctor only receive health updates from you during semi-annual check-ups. There is now more information/data than can currently be sorted and processed with regard to many current health issues, diseases, and treatments.
Jobs in the health landscape, among others, are growing at a rapid rate for statisticians. The Bureau of Labor Statistics predicts that statisticians will be one of the top ten fastest-growing jobs of the next decade.
With increased health connectivity is an increase in data accessibility. In the palm of your hand, data collected from the app is linked with the necessary healthcare services.
You can view your recent and historical health records from a mobile device, and so can your doctor. Decisions and adjustments can be made on a day-to-day, or even hour-to-hour basis.
Connected health has also led to an increase in the accuracy of data. No longer must you try to remember your conditions, symptoms, or health levels for months at a time before your next doctor’s visit.
Health apps are changing the nature of health data collection— from prying doctors at a medical check-up to engaged, at-home patients, supplying more accurate, in-the-moment information.
People seem to inherently dislike divulging their information to healthcare professionals in-person. This interaction incites a level of vulnerability and embarrassment that many people are not comfortable with.
Earlier this year, an article from The New York Times Magazine contrasted our relationship with our phones to our relationship with our doctors, concluding that many individuals are more honest with their phone than with their doctor. While it may be uncomfortable to reveal highly personal information to someone else, this barrier lowers when we are faced with recording personal anecdotes on our phones.
The phone becomes something of a diary/journal; only the critical information stored can be accessed with a click by your doctor. In short, the data is transferred from patient to doctor, without the strong associated feelings of embarrassment and vulnerability.
Gathering Connected Health Data
Connected data collection in the cloud can be gathered two different ways, unobtrusively or manually.
Unobtrusive data collection includes health devices that require no effort from the individual using it. Often, these devices are classified as wearables, indicating that they are worn by the individual with no additional effort needed.
Popular wearables include devices like the Fitbit. As long as the Fitbit is attached to your person, your steps and activity will be recorded, with no additional effort needed to gather data.
Manual data collection includes many health apps that require you to input your health levels throughout the day. Connected health devices that necessitate manual data input are still more effective than traditional methods; studies consistently verify that people are more likely to utilize their mobile device for data recording than to create handwritten notes and other, less convenient forms of data collection.
Additionally, even if manual data input is required for a health app, the app itself sorts and makes sense of the data, something your handwritten notes cannot do.
Impact on Clinical Trials
Increased health connectivity can lead to more efficient clinical trials.
Research and development by pharmaceutical companies is aided when connected devices are implemented. Data can be collected automatically throughout the trial, eliminating many instances of self-reporting or self-recording.
For example, expecting someone to self-record their blood pressure level, at every hour of the day, for the first two months they try a new blood pressure medication, is unrealistic. However, with Omron, a connected wristband, your blood pressure is tracked real-time with minimal effort. For a more complete list of new connected health devices, view our list of 25 New & Noteworthy Connected Health Devices.
In early studies, this has led to increased retention rates in clinical studies, since the ease of participation has increased as well. The seamless integration of connected devices in clinical trials can provide a broader range of more frequent data, in a shorter time frame.
Behavioral Economics in Connected Health
With more available health data, behavioral patterns can more easily be monitored, and the field of behavioral economics has benefitted from this increase in data. Behavioral economics combines psychological insights and cognitive thought processes with economic analysis, attempting to explain seemingly irrational decision-making behavior among individuals and groups.
Behavioral patterns related to health and fitness can faster determine studies’ value and which studies are not economically efficient. This information can allow companies to stay profitable and relevant in the health realm, so as they switch over to digital technology and greater device connectivity, they retain market share.
This ties into the aforementioned section on faster clinical trials, as data on behavioral patterns is more accessible. A faster time to realization of clinical effectiveness helps companies know which products work and which don’t, saving them time and money.
No company wants to allocate more resources towards a product that is ineffective. Knowing a medication has no desired effects after two weeks due to increased health connectivity is invaluable.
Before connected health, if your trials were a failure, you generally realized once the results were reported back at the end of the study, sometimes months later. The economic implications of more frequently uploaded data become quite obvious, as pharmaceutical companies can more swiftly cancel any drugs in the pipeline that are underperforming.
Another concept that crosses over from behavioral economics to connected health is “loss aversion,” increased sensitivity to losses, rather than gains. Loss aversion may explain why some people struggle to cut out unhealthy practices from their everyday lives, even when they are aware of the harm they are doing to themselves.
Striving for a long-term health goal can be difficult when having to eliminate many habits and behaviors in the short-term. With connected devices, more data is readily available, facilitating the tracking of short-term gains to combat the short-term losses.
People seek immediate rewards when they know there are immediate consequences, and the data connected health can deliver changes the immediacy with which healthier patterns can be noticed and appreciated.
Putting the Principles Into Action
A recent study carried out by Dr. Kevin Volpp, founding director of the Center for Health Incentives and Behavioral Economics, combined the ideas of loss aversion and immediate rewards with connected health.
He tracked people who had suffered from cardiac infarctions the previous year, to see if their health incident had led to an increase in their ability to properly take their heart attack medication. Surprisingly, subjects still struggled to take their medication properly, even in the months following cardiac arrest.
He and his team used a smart pill bottle that tracks medication usage and uploads reminders to the patient’s phone. When a subject took their medication properly, they were entered into daily drawings for modest prizes.
Fail to take their medication, and a reminder would be sent to their phone. At the end of the day, if no medication had been taken, an automated message would be sent to their phone, notifying them that they could have won the daily lottery had they properly taken their pill.
The early results from these trials produced tremendously positive results. People given the smart pill bottle with daily lotteries were much more likely to take their medication properly than those without the smart pill bottle.
Several behavioral economics concepts were incorporated in this study: loss aversion, immediate rewards, and the ‘near-miss.’
Test subjects were averse to losing, and disliked receiving the message that they lost the lottery because they forgot to take their medication.
Immediate rewards were present, as every day, there was a new prize at-stake.
The ‘near miss’ is the reinforcement we receive when we feel like we are close to winning. Knowing that lotteries are daily, people kept taking their medication in hopes of winning the lottery, whether or not they were ‘close’ to winning in reality.
The ‘near miss’ is the reason slot machines at casinos thrive; when people lose because they were one away from matching all three items on the machine, their brain tells them to keep playing. Surely, they must be close!
Unfortunately for gamblers, casinos know this too, and design slot machines to produce a ‘near miss’ result frequently, designed as encouragement.
In a similar way, these daily lotteries, wirelessly entered into via the person’s mobile device—courtesy of the smart pill bottle—appealed to a similar part of the brain that gambling does. People became hooked to their smart pill bottle, taking their medication properly as a result.
Behavioral economics fits in nicely with connected health, and the applications are continually increasing.
What Does the Future Hold
Big data has successfully infiltrated the health sector and is here to stay. Successful companies in the future will have to blend their health services with connected devices.
With this much data available, there is a great need for statisticians to rummage through it all. Proper handling and analysis of the data can lead to increased treatment capabilities and monetary savings in the long-run.