Continuous Glucose Monitoring: What It Means for the Definition of Diabetes

I recently published a Commentary on CNBC about the future of glucose tracking using continuous glucose monitors.  Here is the link –  – and here is the Twitter thread that I wrote with further thoughts.

In my editorial on use, I cite this fantastic article on ‘glucotypes’ from geneticists & endocrinologists (). One of my favorite papers from 2018. I want to explain a bit more why I think this paper is so important.

First, here is the editorial in – on where I see use going in next few years in management of diabetes and increasingly in use for people not diagnosed with diabetes.

How we define ‘diabetes’ and make a diagnosis has changed dramatically over the decades. See a short presentation I gave on this in 2012 here – . We’ve progressed from urine testing to OGTT to fasting glucose to A1c.

The paper from Hall et al demonstrates that our current diagnostic tests are probably insufficient. They’re missing lots of people, now labeled as ‘normal,’ who shows actually have dysregulated insulin responses to glucose consumption.

Do these people have diabetes? Prediabetes? These categories were historically defined based on what we know about A1c correlating to risk of microvascular complications (ie retinopathy). That is, it is ‘worth’ diagnosing someone with diabetes if A1c correlates w increased risk.

Really, what we mean is, would the benefits of treatment for diabetes outweigh the harms of treatment for a person with a certain degree of risk based on their A1c?

But… A1c is just an average, fraught with issues. What really matters is, is a person metabolically healthy and are they at increased risk for heart disease or microvascular complications down the road? So, there is a long road ahead for future research here.

How do we categorize ppl based on insulin-glucose response seen with ? Are people with abnormal ‘glucotypes’ at higher risk for heart disease & microvascular complications? What are long-term outcomes? Will they change behavior & improve outcomes when faced w CGM data?

So, to summarize: Not only is a necessary tool for all with , & massively valuable for most with type 2 diabetes, but I believe its use will help us redefine what we think of as , how we define a continuum of risk and categorize individual physiologic responses.

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Diabetes Technology in 2018

Linking here to two resources I published recently:

First, my presentation at the April 2018 UCSF Diabetes CME course.  Those slides on a 2018 Update in Diabetes Technology are here:

Second, I wrote “A Clinician’s Guide to the Latest Diabetes Devices” for Medscape recently.  Here is the first section of that blog post:

This has been a huge year for technological advances in diabetes management. We are on a rapidly advancing path with continuous glucose monitoring (CGM) technology and finally approaching the holy grail of fully automated, closed-loop insulin delivery. Within a few years, patients with type 1 diabetes may never need to do another fingerstick or have another A1c test. For many clinicians, recent developments may seem to present an array of head-spinning options. Here, I’ll try to cut through the noise and focus on technologies that have the biggest implications for clinical practice and our patients.

CGM Data Directly to Your Smartphone

CGM technology has been advancing rapidly in accuracy, number of options, and ease of use, and the problem of inaccurate, painful, alarming, needy, and annoying CGMs feels long in the past. It is hard to believe that it was as recently as December 2016 that the US Food and Drug Administration (FDA) first decided that a CGM (the Dexcom G5®) was accurate enough to no longer require supplemental fingersticks for insulin dosing decisions.

In 2018, Dexcom released the G6 CGM, which is slimmer (and less likely to snag on clothing); requires no fingerstick calibration; and is the first to have the FDA indication of “interoperable,” meaning that it can “plug and play” in the future with other interoperable devices.

Medicare finally started covering CGMs in 2017, and in June 2018 agreed to stop blocking the ability of the Dexcom G5 (which is reimbursed by the Centers for Medicare & Medicaid Services) to transmit data directly to a smartphone, something most users of the G5 had already benefited from for a few years. This was a big deal, as I believe that the ability to view CGM data directly on a smartphone may be the technology advance that has most positively affected my patients with diabetes.

In the past year, billing codes for CGM improved to enable providers to be reimbursed for analysis and interpretation of CGM data. This brings diabetes management one step closer to population health, where a provider can review CGM data without an office visit; correspond with the patient over the telephone, by email, or by text; and be reimbursed for that work. I plan to try this out in my practice during the next few months, blocking off time every 1-2 weeks to review CGM data in web software and communicate recommendations to patients via our electronic health records portal or telephone, with no scheduled visit required.

Immediate Feedback, No Fingersticks Required

Of everything that has come out recently, Abbott’s FreeStyle® Libre Flash CGM has had the greatest impact on my practice. The Libre is a disk-shaped device worn on the back of the arm (see any recent photo of British prime minister Theresa May). My patients have been consistent in their appraisal that the Libre is relatively or even entirely painless to insert, nonintrusive on the arm, and stays on during activity or contact with water. Most important, it entirely changes their approach to diabetes management.

For more, please continue on to Medscape (free Medscape log-in required)

 

HIMSS 2018

Another HIMSS conference is in the books. Amidst the craziness that HIMSS can be, it is always a pleasure to spend time running into friends, collaborators, and former colleagues.  There have been lots of great pieces written about 2018 HIMSS, including by Chrissy Farr and by Lisa Suennen. Here are some of my thoughts and takeaways:

1 – Where’s the Peds?

HIMSS pretty much has a little something for anybody. However, walking the exhibition hall and seeing vendor booths, attending sessions, and talking with colleagues, there was a noticeable under-representation of anything having to do with pediatric care. I’m guessing this has something to do with $$, but I would love to see more attention paid to the specific needs of children, parent caregivers, pediatric care, and children’s hospitals.

2 – Cash and Flash

HIMSS had its usual plethora of vendor swag giveaways, plush carpeted booths, sponsored parties and happy hours, steak dinners, and other signs of the amount of money flowing through the system. One couldn’t help but wonder, if the biggest challenge facing American healthcare is one of cost and value, how could we be spending this much money on HIMSS while telling each other we were there to save money?

Some great tweets on this subject:

Screenshot 2018-03-12 10.20.56Screenshot 2018-03-12 10.20.33

 

3 – Interoperability’s Day Has Arrived

With many thanks to years and years of tireless work by Ken Mandl, Josh Mandel, Aneesh Chopra, Micky Tripathi, Graham Grieve, and so many others, there was a palpable sense that FHIR APIs are crossing from “early adopter” to “mainstream.” CMS announced “Blue Button 2.0,” an API containing four years of Medicare claims data for 53 million beneficiaries that allows individuals to allow third parties to receive that data via API. The VA announced its Lighthouse platform, which gives external developers access to data and tools from the VA in order to more easily build apps to serve the needs of veterans. This is happening.

4 – 2018 HIMSS Word Cloud

AI. Cloud. Interoperability. Security. Provider Burden. API. Connected. Engaged. Consumer. Coordinated…… and Blockchain

4b – My favorite 2018 HIMSS pitch

Started off with the company saying, “even though all our founders come from an AI-background, and all our competitors use AI, we do not use AI in our product.”

5 – From EHR Implementations to Pilots to Mainstream Digital Health

Lots of thought and effort is going into thinking about how to scale innovation and move digital health into the mainstream. How can we create the infrastructure, processes, and tools to try things out, iterate, and scale innovations to get beyond the pilot trap? You can still feel the tension as people try to move past the era of EHR implementations to actually using their EHRs as an underlying platform to achieve care delivery goals like patient engagement, population health, and precision medicine. How can we best use EHRs as a platform on top of which we can integrate novel apps, analytics, and decision support?  To me, solving this at scale is the key question and challenge of the next several years.

 

 

Smart Insulin Pens are here… finally.

The first “smart” insulin pen has finally hit the market. This is a big moment for diabetes care, as the digital toolbox expands. (I wrote a post in 2013 about this topic, asking for someone to make a smart insulin pen)

From the perspective of a person with diabetes, this has the potential to solve many daily challenges. First, did I remember to take my insulin dose? Or, did I recently take a dose and forget that I did, leaving me at risk for hypoglycemia if I inject now? Another key  question for a PWD is, how much “insulin on board” do I have (that is, how much of my recently injected insulin is still affecting me)? Of course, another key element is the ability to track and capture insulin doses and not have to write them down in a logbook for your doctor!

From the provider perspective, we gain a huge amount of data to help us help our patients make decisions and learn from their experiences. For years, if we wanted to review a glucose and insulin time series, we either needed a patient to write down numbers in a logbook or to put someone on an insulin pump. More recently, manually entering data into an app became an option. The “smart” insulin pen finally means that glucose and insulin data can relatively easily (and passively) be captured into one place. This can help guide care in real-time as well as for retrospective review and analysis.

For the many people with type 1 diabetes who do not want an insulin pump, and for the people with type 2 diabetes for whom a pump is not covered or necessary, these smart insulin pens are likely to offer real benefits.

The next ask?

An automated way to capture food intake!

 

Other sources:

DiabetesMine DData 2017 has some slideshows on smart insulin pens

 

Health systems cannot rely on individuals to be our HIE

John Halamka’s blog had a guest blogger, Amy Stiner, who related her story of a tortuous, difficult, painful path of getting her son’s medical information relayed from health system to health system as they moved around the country. This story is all too common and relatable. Among the many striking things in this story is this — even if patient-facing APIs lead to an “HIE of One” scenario, health systems must not absolve ourselves of the obligation to do a better job of information exchange. This woman endured much difficulty in trying to assemble and send her son’s records to the new or next provider of care. But, even if this part were “easy,” why should it be her responsibility to do this?

Yes, it is a moral obligation and a huge benefit to care to allow patients access to their health data. We should be going full steam ahead with implementation of patient-facing APIs and tools to let patients access and use their data.

However, when it comes to creating a functioning healthcare delivery system, health systems cannot rely on patients to solve our problems for us. Health systems cannot rely on each Amy Stiner to find and bring data from place to place, shuttling health information around for us, even if it is done digitally and even if the work effort is much less than it is today.

We must achieve both aims: 1) Enabling patient access to their health data, because they deserve it, and 2) Creating seamless flow of information around the healthcare system, from provider to provider, in the service of providing effective and seamless patient care.

HealthCare Innovators Podcast: Patient-Generated Health Data

I recently had the opportunity to sit down with Travis Good, MD, MBA, Co-Founder and CEO at Datica to discuss emerging trends in the use of patient-generated health data (PGHD) in healthcare delivery.

Here is a link to the Podcast episode

Thank you to Travis for a fun and engaging conversation and for all of the great work Datica does promoting a vibrant digital health ecosystem!

Doximity Dialer

Sometimes simple is the best. I recently tried a new smartphone app – Doximity Dialer – that is just that. I have been so struck by it that I have started showing it off to people at any opportunity. It is incredibly simple to use (from download to using it in <5 minutes) and solves a straightforward, but common problem. It is 8pm and you’re at home working on messages in your EHR. You need to call your patient back about a lab test result. Enter this conundrum… You can either use *67 to block your caller ID in which case the patient will think it is a telemarketer calling and not answer. Or you can leave your caller ID on, in which case the patient now has your cel phone number. While some physicians have become comfortable with their patients having their cel phone numbers, many still have not.
Doximity Dialer allows you to “trick” Caller ID into showing a phone number of your choice, e.g. your office number, to the call recipient. This means that you can make calls to patients from your cel phone, but the patient sees your office number on Caller ID.  Now, they recognize the number as their doctor and will answer the phone, and doctors do not have to feel squeamish that a patient will have their personal cell phone number.
Win-win. Simple.