One Step Closer to Automated Personal Health Management
With both Google and Apple investing this year in developing and launching their respective health platforms, the serious intent and opportunity surrounding personal health technology is apparent. Apple’s HealthKit—and now more recently Google Fit’s SDK—are taking similar but different approaches. With access to core APIs, developers now have two platforms with which to start leveraging and connecting with for apps or devices.
Until recently, health and fitness apps pretty much had to operate in their individual silos. Each individual company essentially built their own system and their own dashboard showing the results. Based on a lack of interoperability and a standard platform, this made it virtually impossible to collect, view, and share a complete set of health and fitness-related information for a single individual.
Then along came platforms like CarePass from Aetna that started to allow these disparate systems to at least be pulled into a single destination, allowing an individual to see a comprehensive set of information. But this was just an aggregated view—not really aggregated data that could easily speak to or build a single health profile. It was definitely a step in the right direction in a complicated, fragmented, and diverse world of new entrants and options in health and fitness tracking.
In addition, there are new startups also trying to tackle aggregation as a platform. Companies like Validic that recently got $5MM in 1st round funding for a platform that connects patient-recorded data from digital health applications, devices and wearables into a their system and easily makes it portable into to key healthcare companies like hospital systems, providers, pharmaceutical companies, payers, and health information technology platforms.
WellDoc, with their FDA-approved app for diabetes, also took a step in the right direction by providing tools to their physicians that provide some level of health coaching along with the ability to connect data. And it is reimbursable through certain plans, further differentiating it from other devices and apps. It stands out and shows that it can be done—and initial clinical data show that it does make a difference.
However, when Apple announced its HealthKit— followed by Google’s announcement of Google Fit SDK—the silos have started to crumble. Both Apple and Google have provided a key element that was previously missing—namely, the ability for apps and device manufacturers to start aggregating information through a set of standard APIs that allow for better data interoperability. Google is taking a slightly different approach than Apple, but ultimately both are aiming to facilitate and provide developers an opportunity to consolidate data in a way that was previously challenging to impossible.
Even with Apple and Google entering the fray though, there are two things that will be really challenging to make the next hurdle towards combined health and fitness data sets to reach true diagnostic capabilities.
- Diagnostic tools require FDA approval: Moving from a simple tracker platform to a device that records and analyzes data to produce instructions that are designed to change health outcomes requires clinical testing and review by the FDA. This is a challenge that many apps and device companies probably are not ready for at this point, as they need significant investment and time to develop and launch. Tracking and displaying data forces the user to interpret the information and outcome, where diagnostic interpretation examines symptoms and medical information to provide instruction to fix or address the symptoms in order to create better health outcomes. This is where many companies may not want to go, because FDA approval is required to be truly considered a diagnostic medical device. There are many clinical decision tools that they could partner with or tap into, but the challenge becomes really the second point here:
- Lack of comprehensive sensor and data input: In order to be able to provide an accurate diagnosis of a situation that determines advice or instruction, you often need a variety of health information points to make an informed decision. So far, calorie-counting, sleep patterns, and steps taken do not really lend well to diagnostics. But with Apple and now Google paving the way to collect information like blood pressure, oxygen saturation, hydration levels, blood sugar levels, and heart rate, these apps could provide better medical insights. However, how many sensors can you expect one person to wear constantly to collect all this data? And will only those with real medical conditions actively collect data, while the average healthy person will find it too much?
So with the direction that Apple, Google, and to a degree Samsung (yes, need to include them as well), are taking, they are helping to establish the core or foundation required to set the stage for app and device manufacturers to reach that next level. So, assuming the challenges mentioned earlier can be overcome—where is this all potentially leading to?
Opening the Door for Interconnected Personal Health Services
Once a common platform for aggregating data exists, it will provide the foundation for that data to be analyzed. Moving beyond simple reactions or alerts, towards intelligent decision making designed to produce personal or individual positive outcomes—via individualized diagnosis and instruction—could bring dramatic changes to the entire healthcare system.
Here are five ways to extend these foundations towards creating a Personal Health Service Platform:
- Beacons for contextual information sharing: Collecting data and providing feedback can best happen when contextually significant. Using beacons or other proximity-based technology will allow for certain triggers to happen at specific places, increasing the likelihood for positive outcomes.
- Connecting with “the Internet of Things”: As these health platforms gather robust profiles, they can start to connect to other devices and appliances to extend directions and recommendations outward. For example, if your blood glucose level is low, your refrigerator (alerted by the platform) could provide you with options on what you have available to eat and what portions are needed to help raise your glucose level back up to normal.
- Real-time feedback from EMR or physician: Moving beyond simply porting real health data into an EMR, but doing so where it is specific to managing a particular condition, could either provide clinical decision support immediately, based on analyzing the data collected along with history and other health information—or could alert a physician or other healthcare worker to immediately reach out to a patient and communicate suggestions or a course of action if necessary.
- Telemedicine and age-in-place: Connecting these into home health monitoring systems that already exist could provide a more comprehensive and possibly less intrusive way to monitor conditions that require users to stay at home, or for elderly that may have limited mobility or challenges to getting to care centers quickly.
- Real-world evidence data gathering: Leveraging these platforms could also help speed up or improve the accuracy of clinical trials, or at least the real world evidence collection of information to better show performance of certain medications on the population at large. By collecting and looking at data in real time, it may also allow for micro-adjustments of medication where individuals do not have to simply get 5mg, 10mg, or 20mg dosages, but could provide more accurate dosages on a person-by-person basis—say, a 7mg dosage—limiting any excess medication in a patient’s system.
In the end, by starting to create simple platforms that make it easy to aggregate health-related information where interoperability is facilitated, app and device manufacturers can start focusing on moving beyond tracking, and look to start providing the direction, instruction, and value-added services that many people need to ultimately better manage their health for the best possible outcomes.
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