A Match Made in Data Heaven: Why Patient Similarity Networks Are the Future of Healthcare
The idea that there’s the perfect person out there for you is a staple of all those cheesy romantic comedies we tune into when there’s nothing better to watch. In true Hollywood fashion, it assumes that whatever quirks or unique characteristics we may have as an individual, there’s another person who shares these exact same characteristics with us. All we need to do is to bump into them and wait for the fireworks to happen.
This might come as a surprise, but this CAN happen in healthcare.
What if it was possible to match you up with another patient who fit the same unique (or almost unique) profile as yourself? That’s not just taking on board a particular chronic condition, but also other lifestyle factors, demographic information, additional health conditions, gender identity, and more.
For example, a forty-something-year-old mom with Fibromyalgia might share that diagnosis with her next-door neighbor — but if her next-door neighbor is in his seventies, suffering from heart disease, and overweight, there is a limit to how similar both people’s patient journey is likely to be.
However, if they can be connected with another patient with a similar profile, this could turn out to be a game-changer when it comes to treatment. Being matched with a similar in this way could give patients a better idea about how a particular healthcare journey might progress, as well as providing them with the emotional and social support they need on that journey — by letting them speak with someone who has been through, or is going through, the same things that they are.
It’s a new way to safely connect with others on a similar healthcare journey, with all the sharing of experiences, providing support, and teachable lessons that come with it.
Digging Deep into the Data
The idea of a patient similarity network — of matching patients with others who fit a similar profile — is still a new idea. But it’s one that’s developing fast, and with good reason. Doctors have known for years about how important it is to match donors for blood transfusions or organ transplants, but the importance of applying similar personalization and patient similarity networks has not been nearly so widespread.
Not applying this kind of granularity has been a huge mistake when it comes to improving patient outcomes. A striking example of this was seen in 2020 when researchers delved into patient data to look at individuals with rheumatoid arthritis.
What they discovered was that there are five distinct phenotypes seen in patients — all with differing symptoms, differing disease progression, and differing treatments required. Treating all patients with rheumatoid arthritis the same way would have missed these distinctions, and resulted in worse treatment.
Thanks to the age of Big Data, it’s now possible to dig into data in a way that’s, frankly, never before been achievable. This is coupled with new measures designed to empower patients, such as the 21st Century Cures Act, which grants patients greater levels of access to their own health records. In turn, that can give patients more control over their health; particularly when it comes to making better-informed decisions about their healthcare and wellness.
A New Era of Personalized Healthcare
Companies at the forefront of healthcare are those that are leaning into, and embracing, this new era of personalized healthcare. Alike, for example, is a digital health company that can be thought of as a kind of Tinder-for-health: matching people with similar profiles. You can download the Alike Health app from Google Play and Apple Store.
Alike relies on a similarity network that takes de-identified data from electronic medical records (also known as EMRs) and then uses a proprietary algorithmic matching system to create a similarity score between every two individuals that it has in its system.
This means that users can be matched with “Alikes” with not only the same medical or health conditions but also ones who are taking the same medications or undergoing the same procedures and share other commonalities.
The advantage of this is that it draws on the power of the crowd to find patient journeys and treatment plans that have worked for people who match up as closely as possible to your health profile. It signals a more holistic approach to healthcare that doesn’t just take into account one or two data points, but individuals as a whole.
Healthcare Is About To Receive a Turbocharge
Alike is just one example of this new future of personalized health. Using tools such as these, doctors will be better able to predict how certain diseases and conditions will progress for patients. Patients, meanwhile, will be better informed about their own health — and be able to take into the real world actionable insights that they can use to stay as healthy as possible.
This is a new type of crowdsourcing: the idea of drawing on the wisdom of the crowd to achieve better results for individuals. Crowdsourcing can be seen in everything from traffic apps like Waze that analyze user traffic data to give drivers real-time traffic updates to the user-generated reviews on websites like TripAdvisor to websites like Kickstarter, which allow customers to put up the money in advance for products they want to will into reality.
Applying this to the world of medicine and healthcare is going to be transformative in the 2020s and beyond: providing a new way to navigate healthcare journeys by leveraging the experiences of others.
In an industry that hasn’t always changed as rapidly as it could or should, healthcare is about to receive a turbocharge. It’s something that both practitioners and patients alike should be ready to welcome with open arms.