Different roads to the same destination

Different roads to the same destination

The theory behind interconnected diabetes management (IDM) is that someone will transform all the data that’s being sent to the cloud into patient relevant patient actionable information. That these actions taken by the patient will ultimately produce better outcomes which will result in fewer complications. The bottom line for IDM is the bottom line as the goal here is not noble, the goal here is to save money, yes patients will benefit but like all things diabetes IDM is as much about money as it is outcomes.

It should also come as no surprise that while there are many players in this category, ultimately the battle is between two tech giants, Google and Apple. These two tech heavyweights in their own way hold the keys to the kingdom, just as a payor can determine the success or failure of a drug though how it’s positioned on the formulary, these tech giants own the platform all these systems run on.  Although Diabetic Investor has long advocated that systems be platform agnostic, that they work with both Apple and Android devices, the fact is few are built this way.

Another key difference between Apple and Google is their approach. While there was a time when it appeared that Apple would move aggressively into the device side, all indications are they have abandoned this approach and have instead decided to provide an environment that any device can communicate with. This is different than Google who not only has the way cool whiz bang contact lenses that measure glucose, but also is partnered with Dexcom (NASDAQ: DXCM) in developing a low cost continuous glucose monitoring system that can used by any patient with diabetes regardless how they are treating their diabetes.

It also appears that Google and Apple differ on what the patient will do with the data that has been transformed into actionable information. Put another way Google seems more targeted at insulin using patients while Apple is trying to expand beyond insulin using patients. As we have pointed out on several occasions it’s much easier to impact insulin using patients as they can take immediate action based on the information provided. This is not the case for non-insulin using patients who need an intervention with their physician before initiating a change to their therapy regimen.

Think of it this way, let’s say you have an insulin using patient using the Dexcom/Google system. The system through data analytics detects a patient is experiencing hypoglycemic events each morning, additional analytics discover that this path to hypoglycemia begins hours earlier while the patient is sleeping. Let’s also assume that this patient is following a standard multiple daily injection (MDI) therapy regimen. Insulin which in the future will be delivered by a smart insulin pen which shares data with Dexcom/Google system. So not only does the Dexcom/Google platform have the glucose data but now has the insulin data as well.  Even without any carb data, which could be gathered if the patient is using a bolos calculator app, the Dexcom/Google system could tell this patient who’s experiencing morning hypoglycemic events when and how much insulin they should be dosing to prevent these events from occurring in the future. Even better the patient can immediately act on the information provided, while they could consult with their physician they are not required to do so.

This is in sharp contrast to a patient who’s on multiple orals, for purposes of this example let’s say metformin and Januvia. Let’s also assume that this patient is also using the Dexcom/Google system. A system that discovers the patient is not under good control, additionally let’s also assume analytics indicate a high degree of glycemic variability. Let’s even go a step further and say this patient has a cloud enabled scale which sends readings to the Dexcom/Google system, a scale which indicates that the patient is also overweight. Ok so we’ve got a patient who’s not under good control, has a high degree of glycemic variability and in addition to all this is also overweight. What immediate action step can the patient take to help rectify these problems? The real answer is there isn’t one. Even if the patient immediately changes their eating habits it will take time before results appear.

It also doesn’t help any that one key piece of data is missing for the non-insulin using patient. Unlike the insulin using patient we have no idea whether or not the non-insulin using patient is taking their metformin or Januvia as prescribed. There is no “smart” pill that communicates with the cloud.

Still even if this information was available the only immediate step a patient could take is to contact their physician who in turn would have to agree that a change in therapy was needed. Then the physician would have to write a new prescription and hope the patient would take it as prescribed. Yet these changes may or may not work. Simply put unlike an insulin using patient it could take months before anyone knows if these changes in therapy for the non-insulin patient has worked or not.

The hard reality here is non-insulin patients are actually more difficult to work with. They need as much help as insulin using patients yet given that there is no “smart” pill, a critical piece of data is missing. Not only that but as our example notes while an insulin using patient will see near immediate results from a change in dosing patterns, it can take months for a non-insulin patient to see results.

This is why for the moment anyway we’d give Google a leg up over Apple, as Apple is merely in the data collection business while Google is in the data analytics business. Apple is basically providing a sand box for others to play in, while Google is building the sand box and playing in it. Apple’s goal seems to be to sell more Apple devices. Google goals are broader extending beyond selling more Android devices into selling more sensors and ultimately into health insurance where premiums are determined based on data gathered from the patient.

The problem facing both Apple and Google is how to expand successfully beyond insulin using patients. A problem which we believe can be solved provided these companies understand the dynamics of the non-insulin world. A world which requires the same data collection and data analytic tools as the insulin using world, yet requires a higher degree of patient motivation and patience. The simple fact here is that insulin using patients are the low hanging fruit when it comes to IDM. The real payoff will come from any company who can successfully navigate the complex dynamics of the non-insulin market.