Next generation #OpenAPS hardware work in progress – Pi HATs

tl;dr – No, you can’t order one yet, this is coming soon! Yay for new & more hardware options!

Over the years, people have had a lot of awesome ideas on how

to improve the hardware that can be used with DIY closed looping. One such example, Oskar’s work with mmeowlink, led us to later work on smaller computer boards with built-in radio stick, aka the Edison/Explorer Board rig. We started working on that last fall; they were produced and available around November, and the community has been using those widely ever since.

However, like all things, the Edison/Explorer is not without it’s downsides. One of which is – there’s no screen. You historically have needed to plug in cables, or remote login to the rig, or have connectivity via your phone, to see what it’s doing. Sometimes this is more annoying than others.

Patrick Kelly, who has a daughter with T1D and began experimenting with OpenAPS, was one of the folks who wanted a screen on the rig. He suggested the idea, which Scott and I thought was awesome – but we don’t have the expertise to build that kind of hardware. Luckily, Patrick and his dad Jack Kelly, *do* have that expertise! They began exploring some of the options around creating a rig with a screen.

(This is one of my favorite parts of the OpenAPS community, where people bring in various types of expertise and we’re all able to collaborate to make everything from hardware and software and usability improvements!)

And at the same time…the rumors became reality, and we learned that Intel has decided to discontinue the Edison module. SAD PANDA. (Intel, if you’re reading this, please bring it back! We love the Edison!) That expedited the need to find the next generation hardware. Luckily, Patrick and Jack had been progressing on the screen, focusing on incorporating it into a “HAT” (board) for the Raspberry Pi. So after discussion with others in the community about pros/cons and availability about various other computing options other than the Pi, given the widespread availability of different types of Pi’s, we’ve decided to move forward with the Pi and a HAT (board) being the most usable option for the next round of hardware that we’ll be recommending to the community.

What exactly does a Pi HAT look like?

I’m so glad you asked 😉 Here is the Pi HAT with screen on a “Pi Zero W” (which I sometimes type as “Pi0” or “Pi 0”) and a “Pi 3” (pi three), compared to the Edison/Explorer Board. My trusty Chapstick is my unit of measurement, but given some of my international friends claim to not understand that yardstick, I threw in some Euro coins on the right as another measurement stick .;)

The Pi 0 is flipped on it’s back like a turtle – but the same Pi HAT can be used for the Pi 0 and the Pi 3. The HAT is bigger than the Pi so the radio stick doesn’t get blocked.

It’s the same radio as the Edison-based Explorer block, so same expected range.

What’s the point of the screen?

With a screen, you can easily see the logs of what the loop is doing: Pi_HAT_screen_OpenAPS_example_DanaMLewis

YOU CAN EASILY ADD AN OPEN WIFI NETWORK ON THE GO! (Yea, that all caps was intentional! :)). You can also see which wifi network it is on, check for IP address, etc.

Pi HAT adding wifi exampleWe’re still working on adding to the menus and playing around with what’s possible and what’s worthwhile for displaying on the menus by default.

You can do all kinds of fun stuff – which Scott found out after asking me one day, “what else should we add to the menu?” and I promptly said “a unicorn”. Scott said, “these don’t have emoji’s, though”.

Five minutes later, we have a DIY diabetes/OpenAPS unicorn built in ASCII, because why not? 😉


Ahem. Back to technical topics.

How is this board/HAT going to be made and when is it going to be available?

Like the Edison-based Explorer, the Pi’s Explorer HAT is an open source hardware design, and ERD (who sold the Explorer for the Edison) will also be doing the Pi HAT.

Timeline is not 100% nailed down yet, but it will probably be another month or so. (Which is about a year after the Edison Explorer was first ready…crazy how time flies in the open source community!) We’ll of course, as always, shout from the rooftops when it’s ready for ordering & experimenting with. We’ll also be updating the OpenAPS docs to reflect the new gear recommended to buy, the steps for getting it up and running, troubleshooting, etc.

What about Edison/Explorer boards? Will that rig type still be supported by OpenAPS? Should I get any more of those?

Yep. Edison/EB will still be supported & widely used. There are some still left.

  • But – if you already have an Edison/EB rig – I would make your next rig purchase a HAT for one of the Pi’s.
  • If you’re new to the OpenAPS community and supply still exists, I’d still consider grabbing the parts for an Edison/Explorer rig – they’re still great, and we’ll continue to use the ones we have for a long time, and will still be supported in documentation. But you’ll likely want a HAT for a Pi rig of some sort, too, to take advantage of the screen & all the features that go with that for ease of use.

What about battery life for the Pi0/Pi3? How fast does it run? AND YOU HAVEN’T ANSWERED ALL OF MY OTHER QUESTIONS?!?!

One of the downsides of our (Scott/my) approach of getting everything to the community as fast as possible – both hardware and software – means that sometimes (every time) we share things that are works in progress. (And we are testing a whole lot of stuff on software, too.) The new hardware is no different. We don’t have all the answers yet, and we’ll hope you’ll help us figure things out as we go! Here’s some of the pending questions we have:

  • Cost. (Pi’s are cheaper than Edison’s. Explorer HATs with screens are slightly more expensive. However, we’re expecting in sum that the HAT+screen rigs with Pi of choice will likely be cheaper than an Edison/Explorer.)
  • Battery life. We know the Pi0 itself is not as efficient as the Edison, so it’ll likely require a bigger battery for the same run time. (No idea exactly how much bigger because I’m not using these rigs in the real world 100% of time yet, because…)
  • Some Pi optimizations still need to be done. (The current code works just fine on a Pi3, but the Pi0 needs some optimization work done. The Pi 0, as you can see from the picture, is smaller, and will likely be the ‘mobile’ rig for many folks, while the Pi 3 might be a backpack/home rig.)
  • Other options for “HATs” that don’t have a screen. (Eric has also been prototyping another Pi HAT, that doesn’t have a screen, and it’ll be great to test and see how that works as a potential option, too. Hop into the openaps/hardware-dev channel to chat with him if you have questions about his approach. )

As we work on the optimizations (great place to dive in if you’re looking for a place to help out!) and updating the scripts and the docs to reflect the Pi suite of options, I’ll begin carrying this kind of rig and doing my usual break-everything-in-the-real-world-and-fix-all-the-things testing approach.

I’m excited. It’s so great to have this kind of collaboration with expertise in so many areas, with everyone centered on the goal of making life with diabetes easier and safer! Shout out to the Kelly family & their colleagues for all the work on the screen & HATs; to Scott for a lot of development work on both hardware and software side; to Morgan & ERD for continuing to be a part of making great open hardware more widely available; and many other people who are working on bits and pieces to make everything possible!

Why a non-academic (patient) publishes in academic journals

Today I was able to share that my Letter to the Editor was published in the Journal of Diabetes Science and Technology. It’s on why we need to set expectations to help patients successfully adopt hybrid closed loop/artificial pancreas/automated insulin delivery system technology. (You can read it via image copies in the first link.)

JDST_screenshot_LTE_expectationsI’ve published a few times in academic journals. Last year, Scott and I published another Letter to the Editor in JDST with the OpenAPS outcomes study we had presented at the 2016 ADA Scientific Sessions conference.

But, I’m sure people are wondering why I choose to do so – especially as I am 1) a patient and 2) a non-academic. (Although in case you missed it – I’m now the Principal Investigator on a grant-funded study!)

While there are many healthcare providers, researchers, industry employees, FDA staff, etc. who read blogs like this and are up to speed on the bleeding edge of diabetes technology… there are easily 10x the number that do not.

And if they don’t know about the existence of this world, they won’t know about the valuable lessons we’re learning and won’t be able to share those lessons and knowledge with other healthcare providers and the patients that they treat.

So, in my pursuit to find more ways to share knowledge from our community with the rest of the diabetes community, this is why we submit abstracts for posters and presentations to conferences like ADA’s Scientific Sessions. Our abstracts are evaluated just like the abstracts from traditional healthcare providers (as far as they can tell, I’m just another academic, albeit one with fewer credentials ;)), and I’m proud that they’re evaluated and deemed worthy of poster presentations alongside mainstream researchers. Ditto for our written publications, whether they be letters to the editor or other types of articles submitted to journals and publications.

We need to find more ways to share and distribute knowledge with the “traditional” medical and academic research world. And I’d love to do more – so please share ideas if you have them. And if you’re someone who bridges the gap to the traditional world, I appreciate your help sharing these types of articles and conversations with your colleagues.

Choose One: What would you give up if you could? (With #OpenAPS, maybe you can – oref1 includes unannounced meals or “UAM”)

What do you have to do today (related to daily insulin dosing for diabetes) that you’d like to give up if you could? Counting carbs? Bolusing? Or what about outcomes – what if you could give up going low after a meal? Or reduce the amount that you spike?

How many of these 5 things do you think are possible to achieve together?

  • No need to bolus
  • No need to count carbs
  • Medium/high carb meals
  • 80%+ time in range
  • no hypoglycemia

How many can you manage with your current therapy and tools of choice?  How many do you think will be possible with hybrid closed loop systems?  Please think about (and maybe even write down) your answers before reading further to get our perspective.

With just pump and CGM, it’s possible to get good time in range with proper boluses, counting carbs, and eating relatively low-carb (or getting lucky/spending a lot of time learning how to time your insulin with regular meals).  Even with all that, some people still go low/have hypoglycemia.  So, let’s call that a 2 (out of 5) that can be achieved simultaneously.

With a first-generation hybrid closed loop system like the original OpenAPS oref0 algorithm, it’s possible to get good time in range overnight, but achieve that for meal times would still require bolusing properly and counting carbs.  But with the perfect night-time BGs, it’s possible to achieve no-hypoglycemia and 80% time in range with medium carb meals (and high-carb meals with Eating Soon mode etc.).  So, let’s call that a 3 (out of 5).

With some of the advanced features we added to OpenAPS with oref0 (like advanced meal assist or “AMA” as we call it), it became a lot easier to achieve a 3 with less bolusing and less need to precisely count carbs.  It also deals better with high-carb meals, and gives the user even more flexibility.  So, let’s call that a 3.5.

A few months ago, when we began discussing how to further improve daily outcomes, we also began to discuss the idea of how to better deal with unannounced meals. This means when someone eats and boluses, but doesn’t enter carbs. (Or in some cases: eats, doesn’t enter carbs, and doesn’t even bolus). How do we design to better help in that safety, all while sticking to our safety principles and dosing safely?

I came up with this idea of “floating carbs” as a way to design a solution for this behavior. Essentially, we’ve learned that if BG spikes at a certain rate, it’s often related to carbs. We observed that AMA can appropriately respond to such a rise, while not dosing extra insulin if BG is not rising.  Which prompted the question: what if we had a “floating” amount of carbs hanging out there, and it could be decayed and dosed upon with AMA if that rise in BG was detected? That led us to build in support for unannounced meals, or “UAM”. (But you’ll probably see us still talk about “floating carbs” some, too, because that was the original way we were thinking about solving the UAM problem.) This is where the suite of tools that make up oref1 came from.  In addition to UAM, we also introduced supermicroboluses, or SMB for short.  (For more background info about oref1 and SMB, read here.)

So with OpenAPS oref1 with SMB and floating carbs for UAM, we are finally at the point to achieve a solid 4 out of 5.  And not just a single set of 4, but any 4 of the 5 (except we’d prefer you don’t choose hypoglycemia, of course):

  • With a low-carb meal, no-hypoglycemia and 80+% time in range is achievable without bolusing or counting carbs (with just an Eating Soon mode that triggers SMB).
  • With a regular meal, the user can either bolus for it (triggering floating carb UAM with SMB) or enter a rough carb count / meal announcement (triggering Eating Now SMB) and achieve 80% time in range.
  • If the user chooses to eat a regular meal and not bolus or enter a carb count (just an Eating Soon mode), the BG results won’t be as good, but oref1 will still handle it gracefully and bring BG back down without causing any hypoglycemia or extended hyperglycemia.

That is huge progress, of course.  And we think that might be about as good as it’s possible to do with current-generation insulin-only pump therapy.  To do better, we’d either need an APS that can dose glucagon and be configured for tight targets, or much faster insulin.  The dual-hormone systems currently in development are targeting an average BG of 140, or an A1c of 6.5, which likely means >20% of time spent > 160mg/dL.  And to achieve that, they do require meal announcements of the small/medium/large variety, similar to what oref1 needs.  Fiasp is promising on the faster-insulin front, and might allow us to develop a future version of oref1 that could deal with completely unannounced and un-bolused meals, but it’s probably not fast enough to achieve 80% time in range on a high-carb diet without some sort of meal announcement or boluses.

But 4 out of 5 isn’t bad, especially when you get to pick which 4, and can pick differently for every meal.

Does that make OpenAPS a “real” artificial pancreas? Is it a hybrid closed loop artificial insulin delivery system? Do we care what it’s called? For Scott and me; the answer is no: instead of focusing on what it’s called, let’s focus on how different tools and techniques work, and what we can do to continue to improve them.

Introducing oref1 and super-microboluses (SMB) (and what it means compared to oref0, the original #OpenAPS algorithm)

For a while, I’ve been mentioning “next-generation” algorithms in passing when talking about some of the work that Scott and I have been doing as it relates to OpenAPS development. After we created autotune to help people (even non-loopers) tune underlying pump basal rates, ISF, and CSF, we revisited one of our regular threads of conversations about how it might be possible to further reduce the burden of life with diabetes with algorithm improvements related to meal-time insulin dosing.

This is why we first created meal-assist and then “advanced meal-assist” (AMA), because we learned that most people have trouble with estimating carbs and figuring out optimal timing of meal-related insulin dosing. AMA, if enabled and informed about the number of carbs, is a stronger aid for OpenAPS users who want extra help during and following mealtimes.

Since creating AMA, Scott and I had another idea of a way that we could do even more for meal-time outcomes. Given the time constraints and reality of currently available mealtime insulins (that peak in 60-90 minutes; they’re not instantaneous), we started talking about how to leverage the idea of a “super bolus” for closed loopers.

A super bolus is an approach you can take to give more insulin up front at a meal, beyond what the carb count would call for, by “borrowing” from basal insulin that would be delivered over the next few hours. By adding insulin to the bolus and then low temping for a few hours after that, it essentially “front shifts” some of the insulin activity.

Like a lot of things done manually, it’s hard to do safely and achieve optimal outcomes. But, like a lot of things, we’ve learned that by letting computers do more precise math than we humans are wont to do, OpenAPS can actually do really well with this concept.

Introducing oref1

Those of you who are familiar with the original OpenAPS reference design know that ONLY setting temporary basal rates was a big safety constraint. Why? Because it’s less of an issue if a temporary basal rate is issued over and over again; and if the system stops communicating, the temp basal eventually expires and resume normal pump activity. That was a core part of oref0. So to distinguish this new set of algorithm features that depart from that aspect of the oref0 approach, we are introducing it as “oref1”. Most OpenAPS users will only use oref0, like they have been doing. oref1 should only be enabled specifically by any advanced users who want to test or use these features.

The notable difference between the oref0 and oref1 algorithms is that, when enabled, oref1 makes use of small “supermicroboluses” (SMB) of insulin at mealtimes to more quickly (but safely) administer the insulin required to respond to blood sugar rises due to carb absorption.

Introducing SuperMicroBoluses (or “SMB”)

The microboluses administered by oref1 are called “super” because they use a miniature version of the “super bolus” technique described above.  They allow oref1 to safely dose mealtime insulin more rapidly, while at the same time setting a temp basal rate of zero of sufficient duration to ensure that BG levels will return to a safe range with no further action even if carb absorption slows suddenly (for example, due to post-meal activity or GI upset) or stops completely (for example due to an interrupted meal or a carb estimate that turns out to be too high). Where oref0 AMA might decide that 1 U of extra insulin is likely to be required, and will set a 2U/hr higher-than-normal temporary basal rate to deliver that insulin over 30 minutes, oref1 with SMB might deliver that same 1U of insulin as 0.4U, 0.3U, 0.2U, and 0.1U boluses, at 5 minute intervals, along with a 60 minute zero temp (from a normal basal of 1U/hr) in case the extra insulin proves unnecessary.

As with oref0, the oref1 algorithm continuously recalculates the insulin required every 5 minutes based on CGM data and previous dosing, which means that oref1 will continually issue new SMBs every 5 minutes, increasing or reducing their size as needed as long as CGM data indicates that blood glucose levels are rising (or not falling) relative to what would be expected from insulin alone.  If BG levels start falling, there is generally already a long zero temp basal running, which means that excess IOB is quickly reduced as needed, until BG levels stabilize and more insulin is warranted.

Safety constraints and safety design for SMB and oref1

Automatically administering boluses safely is of course the key challenge with such an algorithm, as we must find another way to avoid the issues highlighted in the oref0 design constraints.  In oref1, this is accomplished by using several new safety checks (as outlined here), and verifying all output, before the system can administer a SMB.

At the core of the oref1 SMB safety checks is the concept that OpenAPS must verify, via multiple redundant methods, that it knows about all insulin that has been delivered by the pump, and that the pump is not currently in the process of delivering a bolus, before it can safely do so.  In addition, it must calculate the length of zero temp required to eventually bring BG levels back in range even with no further carb absorption, set that temporary basal rate if needed, and verify that the correct temporary basal rate is running for the proper duration before administering a SMB.

To verify that it knows about all recent insulin dosing and that no bolus is currently being administered, oref1 first checks the pump’s reservoir level, then performs a full query of the pump’s treatment history, calculates the required insulin dose (noting the reservoir level the pump should be at when the dose is administered) and then checks the pump’s bolusing status and reservoir level again immediately before dosing.  These checks guard against dosing based on a stale recommendation that might otherwise be administered more than once, or the possibility that one OpenAPS rig might administer a bolus just as another rig is about to do so.  In addition, all SMBs are limited to 1/3 of the insulin known to be required based on current information, such that even in the race condition where two rigs nearly simultaneously issue boluses, no more than 2/3 of the required insulin is delivered, and future SMBs can be adjusted to ensure that oref1 never delivers more insulin than it can safely withhold via a zero temp basal.

In some situations, a lack of BG or intermittent pump communications can prevent SMBs from being delivered promptly.  In such cases, oref1 attempts to fall back to oref0 + AMA behavior and set an appropriate high temp basal.  However, if it is unable to do so, manual boluses are sometimes required to finish dosing for the recently consumed meal and prevent BG from rising too high.  As a result, oref1’s SMB features are only enabled as long as carb impact is still present: after a few hours (after carbs all decay), all such features are disabled, and oref1-enabled OpenAPS instances return to oref0 behavior while the user is asleep or otherwise not engaging with the system.

In addition to these safety status checks, the oref1 algorithm’s design helps ensure safety.  As already noted, setting a long-duration temporary basal rate of zero while super-microbolusing provides good protection against hypoglycemia, and very strong protection against severe hypoglycemia, by ensuring that insulin delivery is zero when BG levels start to drop, even if the OpenAPS rig loses communication with the pump, and that such a suspension is long enough to eventually bring BG levels back up to the target range, even if no manual corrective action is taken (for example, during sleep).  Because of these design features, oref1 may even represent an improvement over oref0 w/ AMA in terms of avoiding post-meal hypoglycemia.

In real world testing, oref1 has thus far proven at least as safe as oref0 w/ AMA with regard to hypoglycemia, and better able to prevent post-meal hyperglycemia when SMB is ongoing.

What does SMB “look” like?

Here is what SMB activity currently looks like when displayed on Nightscout, and my Pebble watch:

First oref1 SMB OpenAPS test by @DanaMLewisFirst oref1 SMB OpenAPS test as seen on @DanaMLewis pebble watch

How do features like this get developed and tested?

SMB, like any other advanced feature, goes through extensive testing. First, we talk about it. Then, it becomes written up in plain language as an issue for us to track discussion and development. Then we begin to develop the feature, and Scott and I test it on a spare pump and rig. When it gets to the point of being ready to test it in the real world, I test it during a time period when I can focus on observing and monitoring what it is doing. Throughout all of this, we continue to make tweaks and changes to improve what we’re developing. After several days (or for something this different, weeks) of Dana-testing, we then have a few other volunteers begin to test it on spare rigs. They follow the same process of monitoring it on spare rigs and giving feedback and helping us develop it before choosing to run it on a rig and a pump connected to their body. More feedback, discussion, and observation. Eventually, it gets to a point where it is ready to go to the “dev” branch of OpenAPS code, which is where this code is now heading. Several people will review the code and approve it to be added to the “dev” branch. We will then have others test the “dev” branch with this and any other features or code changes – both by people who want to enable this code feature, as well as people who don’t want this feature (to make sure we don’t break existing setups). Eventually, after numerous thumbs up from multiple members of the community who have helped us test different use cases, that code from the “dev” branch will be “approved” and will go to the “master” branch of code where it is available to a more typical user of OpenAPS.

However, not everyone automatically gets this code or will use it. People already running on the master branch won’t get this code or be able to use it until they update their rig. Even then, unless they were to specifically enable this feature (or any other advanced feature), they would not have this particular segment of code drive any of their rig’s behavior.

Where to find out more about oref1, SMB, etc.:

  • We have updated the OpenAPS Reference Design to reflect the differences between oref0 and the oref1 features.
  • OpenAPS documentation about oref1, which as of July 13, 2017 is now part of the master branch of oref0 code.
  • Ask questions! Like all things developed in the OpenAPS community, SMB and oref1-related features will evolve over time. We encourage you to hop into Gitter and ask questions about these features & whether they’re right for you (if you’re DIY closed looping).

Special note of thanks to several people who have contributed to ongoing discussions about SMB, plus the very early testers who have been running this on spare rigs and pumps. Plus always, ongoing thanks to everyone who is contributing and has contributed to OpenAPS development!

Improving #OpenAPS connectivity with automatic Bluetooth tethering (and switching)

One of my favorite things about developing and designing new OpenAPS tools is that if it works for me, it probably will work for someone else, too, and is worth sharing. These little tweaks and hacks add up to improving the real-world lived experience (usability) of living with DIY devices quite a bit…and I’m hoping that continuing to remove that friction enables people with diabetes to live their lives & take action more easily elsewhere, less distracted by diabetes.

So this weekend, Saturday was about enabling easier re-running of the setup scripts to add advanced features more easily in the future.

But Sunday became all about Bluetooth.


Recently, several people have made a concerted effort to create and improve the directions to enable people to connect their OpenAPS rigs to their phones, using Bluetooth.

Without Bluetooth capabilities, when someone left the house or a known wifi network, they would either have to plug in a CGM receiver to get BGs (or have xDrip); or “hotspot” their phone to connect the rig to the Internet. It wasn’t a big deal, but it was something else you had to get into the habit of doing every time you left.

With Bluetooth tethering, you can connect your rig to the phone. And we added the feature so that if you dropped off a wifi network (you left home; or your router at home went down), then your rig automatically established Bluetooth connection and your phone would provide Internet connectivity to your rig. Great!

Making it easier for PWDs with loved ones (spouses/partners/parents/etc.) supporting them

However, today I noticed that because I have both Scott and my phones enabled and configured, sometimes the rigs would grab my phone’s hotspot, and sometimes his (depending on the timing). As the PWD, I would prefer my phone to be the primary phone for Bluetooth, and to only grab Scott’s if mine is out of range/unavailable. And I realized that this will probably be true for most people: kids may sometimes carry a phone, but not always, so it’ll make sense to check for a PWD’s phone first before cycling to try their support network’s phones next. off we went to build that in. Scott also added code that makes it so that if your rig spots an open wifi, but it has a captive portal (meaning it requires passwords or accepting T&C, which the computer can’t automatically do, so it really doesn’t enable Internet access) and wifi ultimately doesn’t work, it will turn off wifi so the Bluetooth can provide connectivity..until the Bluetooth goes away. So it makes it easier for the rig to automatically stay online while you’re going to and from various places that do and don’t have open wifi networks for connectivity.

More connectivity is awesome

I was telling someone the other day why having easier connectivity and remote troubleshooting options is awesome – even as an adult. When a PWD is busy (at school, or on a stage presenting, or at a meeting, or whatever), a loved one can remote in and see what’s going on in the rig and resolve any issues, allowing the PWD to live their life.

That’s something to ask the commercial manufacturers of AP systems as they are in the pipeline to roll out to the broader community of people living with diabetes. For any commercial system you’re considering, ask the manufacturer:

  • How will your system enable me to live my life successfully?
  • How can see I easily see my data in the ways that I want to see it, on the devices that I want to see it on?
  • How will my loved ones be able to see my data?
  • How will my loved ones in a different location be able to help troubleshoot when things are going on?

These are the details that make the difference. This is why #WeAreNotWaiting.

Feedback on proposed FDA guidance on interoperable medical devices

Our friend Anna McCollister-Slipp first alerted us to the proposed draft guidance recently released from the FDA, covering medical device interoperability. (You can read the draft guidance linked here.) We were subsequently among those asked by Amy Tenderich, and others, to share our initial thoughts and comments in response to the draft guidance. We wanted to publicly share our initial thoughts as a draft comment in response to the proposed guidelines (which we plan to officially submit as well), in hopes of encouraging subsequent discussion and additional commentary submitted in response to the draft guidance. We’d love to hear your thoughts after you read the linked guidance, as well as our comment below, and also encourage you to consider submitting a comment to the FDA regarding the guidance.

Draft comment response by Scott Leibrand & Dana Lewis:

The proposed FDA guidance on medical device interoperability is a gesture in the right direction, and is clearly intended to encourage medical devices to be designed with interoperability in mind. However, in the current draft form, the proposed guidance focuses too much on *discouraging* manufacturers from including the kinds of capabilities necessary to allow for continued innovation (particularly patient-led innovation as seen from the patient-driven #WeAreNotWaiting community).  Instead, much of the guidance assumes that manufacturers should only provide the bare minimum level of interoperability required for the intended use, and even goes so far as to suggest they “prevent access by other users” to any “interface only meant to be used by the manufacturer’s technicians for software updates or diagnostics”.  There is also much note of “authorized users”, which is language that is often currently leaned upon in the real world to exclude patients from accessing data on their own medical devices – so it would be worthwhile to further augment the guidance and/or more specifically review the implications of the guidance with an eye toward patients/users of medical devices.  The focus on including information on electronic data interfaces in product labeling is a good inclusion in the guidance, but it would be far more powerful (and less likely to be interpreted as a suggestion to cripple future products’ interoperability capabilities) if manufacturers were encouraged to properly include interface details for *all* their interfaces, not just those for which the manufacturer has already identified an intended use case.

Specific suggestions for improving the proposed guidance on medical device interoperability:
  • The guidance needs to more explicitly encourage manufacturers to design their products for *maximum* interoperability, including the ability for the device to safely interoperate with devices and for use cases that are not covered by the manufacturer’s intended uses.
  • Rather than designing device interoperability characteristics solely for intended uses, and withholding information related to non-intended uses, manufacturers should detail in product labeling the boundaries of the intended and tested use cases, and also provide information on all electronic data interfaces, even those with no manufacturer-intended use.  Labeling should be very clear on the interfaces’ design specifications, and should detail the boundaries of the uses the manufacturer intended, designed for, and tested.
  • The guidance should explicitly state that the FDA supports allowing third parties to access medical devices’ electronic data interfaces, according to the specifications published by the manufacturers, for uses other than those originally intended by the manufacturer.  They should make it clear that any off-label use by patients and health care professionals must be performed in a way that interoperates safely with the medical device per the manufacturer’s specifications, and it is the responsibility of the third party performing the off-label use, not the manufacturer, to ensure that they are making safe use of the medical device and its electronic data interface.  The guidance should make clear that the manufacturer is only responsible for ensuring that the medical device performs as specified, and that those specifications are complete and accurate.
With these kinds of changes, this guidance could be a powerful force for improving the pace of innovation in medical devices, allowing us to move beyond “proprietary” and “partnership” based solutions to solutions that harness the full power of third-party innovation by patients, health care professionals, clinical researchers and other investigators, and startup technology companies.  The FDA needs to set both clear rules that require manufacturers to document their devices capabilities as well as guidance that encourages manufacturers to provide electronic data interfaces that third parties can use to create new and innovative solutions (without introducing any new liability to the original manufacturer for having done so).  If the FDA does so, this will set the stage to allow innovation in medical devices to parallel the ever-increasing pace of technological innovation, while preserving and expanding patients rights to access their own data and control their own treatment.