Going out with a complete stranger hasn’t been the same since OkCupid, Tinder, Bumble and all the rest hit the scene. Before the era of dating apps, a blind date typically involved being matched up with another person based on the matchmaking skills of mutual friends, who likely had limited knowledge about what we might look for in a romantic partner. Not only were blind dates selected from a much smaller pool of people (most usual friends of friends), but also based only on a few broad parameters — such as two potential matches living in the same area, being the same age, or having a shared love of creating vision boards.
Online dating has changed all of this.
Not only do online dating tools have access to a much wider number of possible matches, but they can also do more precise matching, based not on one or two shared traits but a far more forensic level of similarities.
Imagine if the world of healthcare could do something similar with patients. That’s not to suggest finding romantic dates by matching people based on both parties suffering from asthma, but rather applying that same level of deep matchmaking to help people find others who are going through shared medical experiences.
This could be valuable for physical and social reasons: perhaps sharing information about how a particular diagnosis has developed in the patient journey or offering emotional support based on a shared experience.
For a long time, this wasn’t possible. Patients had no way of meeting others in the same boat that they are. Even with certain aspects in common, the medical diagnosis itself is only one part of the bigger picture. Whether it’s genetic background, lifestyle factors, other demographic information, gender identity, and more, patient journeys — and, thereby, patient similarity — is far more complex than just the fact that both people may have been diagnosed with the same condition.
That is not to suggest that services like patient support groups are bad, but that there may be a limit to how much information could be extracted from them. For instance, a younger person who shares a diagnosis of Systemic lupus erythematosus (SLE) with a much older patient may experience the diagnosis and health journey very differently if their health profiles are vastly different. In the case of most patients, the end result was that they simply wouldn’t speak to others going through similar circumstances.
This is changing thanks to patient similarity networks. Doctors have long known that there are circumstances in which matching patients is important. For example, the success of blood transfusions and organ transplants depend on them coming from and going to the right individuals. Failing to do so could have disastrous effects. However, in the age of AI and big data, it’s now possible to match patients in all sorts of new ways in order to optimize the treatment process.
One company doing this is the pioneering digital health company Alike, which uses cutting-edge technology in the form of smart algorithms and a patient similarity network to aid individuals in finding their medical “alikes,” patients who share similar profiles. Alike carries this matching process out by using de-identified data that comes from uploaded electronic medical records (EMRs), then using algorithms to establish similarity scores for every pair of individuals on its system. If two people match highly enough, they can be connected.
Like an online dating service with large numbers of users on its books, Alike gets to leverage the power of the online crowd to help individuals find others they should be communicating with.
Once this matching process is carried out, patients can then share insights, lessons they have learned, health tips, and other information within their ultra-personalized social network. This can assist them in better managing and dealing with the conditions they have been diagnosed with. The result is a more proactive, holistic approach to healthcare that will help redefine the way that medicine is practiced in the years to come. You can download the Alike Health app from Google Play and Apple Store.
It’s still early days for this revolution in healthcare. But all signs are pointing to this being the start of sweeping changes. Not only is AI technology helping make this kind of matching possible, but laws are changing to accommodate. For instance, legislation such as the 21st Century Cures Act gives people greater control over their health by giving them more access to their health records. This leads to more information, which they can then use to make better informed decisions when it comes to healthcare and wellness.
While there’s still a long way to go until this is standard for everyone, the presence of companies like Alike is paving the way for early adopters. It won’t be too much longer before the rest of the world follows suit. Remember how few people would use, or admit to using, online dating 20 years ago? Today, it’s the most common way to meet partners.
Expect the same to happen when it comes to healthcare. Frankly, it can’t happen soon enough.
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