“But who is going to pay for it?!” — New Medicare Billing Codes for 2015 Include Remote Chronic Disease Management
November 5, 2014 Leave a comment
November 5, 2014 Leave a comment
April 5, 2013 Leave a comment
Asthmapolis, which launched in 2010, has been in the news the last few days after announcing a $5 million series A venture capital round of funding. They are an innovative mHealth company that is focused on improving care of asthma through a combination of hardware and software. They developed a small sensor that attaches to the top of an asthma inhaler and wirelessly synchs with your smartphone. The data can then be tracked, viewed, analyzed, sent to a physician, used for clinical research, etc. Anything you can imagine. The frequency with which someone uses their inhaler is often directly tied to how severe their asthma is, and can predict which people are headed for trouble. So, rather than each squirt of an inhaler being an invisible act lost to history, it can now be tracked and used to generate meaningful data to help patients (and for research). This is exactly what mHealth is all about. The innovators at Asthmapolis have developed a relatively simple and straightforward intervention that should add no additional hassle to a patient’s life but might be life-saving if it can serve as an early-warning system for worsening asthma.
Taking this one step further, we need to have such an add-on piece of hardware for insulin pens for use by people with diabetes. It is obviously not exactly the same: with an asthma inhaler, one press is one dose, whereas with an insulin pen, it would have to be able to capture the exact amount given; with asthma, an increasing use of an inhaler could be a sign of impending trouble, whereas with diabetes, daily fluctuations in insulin dose can often be a normal pattern. However, there are enough important parallels that make this an invention that we need in the diabetes world. We are always asking our patients to keep track of how much insulin they use, but it is an extra task for them in their already busy lives, one which could relatively easily be automated. I’ve still yet to see a prototype of such a device for an insulin pen outside of the GluBalloon project from MIT about a year ago. I hope that there is more to come in the near future for us in the world of diabetes.
Best of luck to Asthmapolis… they look to be poised to make a major difference in the lives of people with asthma.
June 19, 2012 Leave a comment
This fantastic rant about the frustrating state of diabetes technology from Scott Hanselman, a type 1 diabetic, has been making its way around the blogosphere and a few of my email chains. In his blog post, he decries the slow pace at which diabetes technology is moving, showing an example of a program he wrote for his PalmPilot in 1998 that was able to give him in-depth analysis of his blood sugar management. He correctly points out some of the major technological issues that people with diabetes still suffer from today, including less-than-optimal accuracy of blood sugar readings, a lack of standards and interoperability, and a lack of useful wireless technology.
Scott is dead-on in the most critical respect here: The typical workflow that a type 1 diabetic still has to endure to acquire his or her glucose values, transmit/download the values, collate values from different devices, and analyze the values is entirely too cumbersome, slow, and inefficient. The current diabetes technology industry has done little to solve this.
June 19, 2012 Leave a comment
Gizmodo, a well-known consumer electronics and technology blog, posted a story about progress towards the artificial pancreas. Is diabetes technology moving more into the popular consciousness?
May 23, 2012 1 Comment
Published in an Online First this week by JAMIA was the extension of the original DiaTel study published in Diabetes Care in 2010. The original study ran from 2005-2007, and patients were randomized to an “Active Care Management” (ACM) arm or a “Care Coordination” (CC) arm. The ACM arm transmitted blood glucose values daily, with a nurse practitioner adjusting their medications every 24-72 hours following ADA guidelines. The CC group received a monthly care coordination phone call offering diabetes self-management education and a referral to their primary care provider for medication adjustment. At 3 months, A1c reductions in the ACM group were 1.7% versus 0.7% in the CC group and at 6 months this was sustained at 1.7% versus 0.8% (p<0.001 for each of these).
This DiaTel Extension study was designed to see if these initial improvements could be sustained with interventions of similar or lower intensity over a six month extension period. The study design is shown here:
Methods: The population studied was a VA (Veterans Affairs) population in Pittsburgh. It is notable that this population does not reflect the typical US civilian population, as they were nearly 100% male, over 80% caucasian, <20% college-educated, and more than half were retired. The primary outcome measure was HbA1c. The mean A1c (at original DiaTel randomization) for the two groups was around 9.5%.
As you can see in the above diagram, some patients in the initial ACM group who had been transmitting glucoses daily were “stepped-down” in intensity to a “CCHT” intervention, where they continued to transmit glucose values daily but no longer had active medication management by the nurse practitioner. Other ACM patients were “stepped-down” to the CC intervention. Notably, no ACM patients were kept on ACM, and no ACM patients were sent all the way back to “UC” or usual care.
From the initial CC group (this is the group who got monthly phone calls), participants were randomized to continued CC, or “stepped-down” to usual care, UC. Usual care consisted of primary care visits every 3-6 months.
The results of the study? They did not show a benefit in continuation of the higher-intensity intervention, eg continued home telemonitoring. The authors write that this suggests that a lower intensity of contact can be used after the initial period to maintain the same level of improvement in glycemic control. Some of the results are shown below, from Figure 3 in the paper, and please note that the initial DiaTel study is indicated by months 0-6 below, with the extension period being months 6-12.
So what does this study mean?
Though a very interesting, necessary, and useful study, as with most studies, there are some limitations to it, many of which are pointed out by the authors. The population studied was a typical VA population, but this does not reflect the typical civilian US population. Because the extension trial could only be done in original study participants, the statistical power of the study was limited. This means that even if there was a true difference between groups, the study might not have been “powerful” enough to show it. Interestingly, looking at the graphic in Figure 3 above, you can start to visually see a worsening in A1c in the ACM to CCHT arm of the trial, however, there was no statistical significance seen (was the lack of significance only because of insufficient power?). The authors chose not to create an ACM to ACM group or an ACM to usual care group for the extension of the trial, so we don’t know how those would have stacked up. We do not know what the duration of A1c lowering from an intensive telemedicine intervention would be, and we also don’t know how long the initial intensive management period needs to be in order to achieve an improvement.
The authors point out that to generalize and disseminate a telemedicine intervention like this one will require a reimbursement mechanism and consideration of cost-effective ways of deploying it.
The bottom line is that a six-month long, intensive telemedicine intervention for diabetes management appears to improve A1c in this VA population, and that A1c improvement might be sustained even when the intensity of management is reduced.