“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
September 19, 2014 Leave a comment
Epic’s User Group Meeting (UGM) is a Healthcare Conference
The Epic EHR is so ingrained in healthcare now that the UGM conference is really a healthcare conference, not an IT conference. This was a conference where more than 10,000 healthcare professionals met to share best practices about how to run a healthcare organization and deliver care, and oh by the way, the tool you’re using is this software called Epic.
There were clearly dominant themes this year among the priorities of the healthcare organizations in attendance:
1— Population health and ACOs
2— Patient-______: patient-engagement, patient-centeredness, patient reported outcomes, patient collected data, patient portal, etc
3— Health information exchange
4— Capture and use of discrete data by physicians
5— E-visits and video visits to improve access (and maybe end the long reign of the office visit)
6— Algorithms and analytics, especially with combining of multiple data sources
7— Personalized medicine using genomic data and home-collected data alongside traditional clinical data
Epic Should Do SaaS
If I were Epic, I would develop a SaaS (Software as a Service) version (call it “EpicLite”) and cannibalize my own business from the bottom up. Epic is making some fantastic improvements to their software, but a major complaint you hear around the lunch tables at UGM is that no organization has the resources to implement all of Epic’s features and functions. Epic has made their software endlessly customizable in an attempt to please customers who asked them for such customization. But the end result is that we all bog ourselves down. I’d like to see Epic push back a bit more against what we all tell them we want, be bolder, and push out software to us all that just works out of the box. They can start with the “EpicLite” version and sell it to organizations less complex than the very large customers they most frequently serve now. Follow the 80/20 rule, pick the things that work best, and give it to people. I promise that we will complain, but then we will deal with it and save a lot of money and effort. They could then slowly move up-market with this SaaS version to sell it to the more complex and large customers in true Clayton Christiansen-esque disruptive innovation to disrupt their own core business. To analogize based on one of Christiansen’s examples, they won’t want to be selling mainframes in ten years when everyone wants PCs.
Open.Epic and Apple HealthKit Integration
I’ve heard a lot of skepticism about this effort over the past year because Epic has always had the reputation of being a very closed system, but Open.Epic should change that perception. I think that this is going to be a big deal. I believe that a major reason for the lack of success of many digital health apps is that they are silos and built in standalone fashion. Let’s face it: the EHR is the hub of clinical workflows and no matter how cool and important your app is, it is still just an add-on. Apps cannot be successful if they don’t fit into clinical workflows. Therefore, to be successful, the workflow of using an app needs to blend in with the use of the EHR. Epic publishing APIs through Open.Epic for people to connect apps in is a game-changer and will enable an entirely new generation of apps that bolt on alongside the EHR.
Similarly, I think the Epic and Apple Healthkit integration will catalyze many of the currently stagnant use cases for sensor and device data, as it will now easily feed into the clinical environment.
Random Thoughts and Impressive Numbers
I found myself wondering what Epic would be like if it were in Silicon Valley instead of Wisconsin. I don’t think it would be very Epic-like. You probably wouldn’t see them announcing next year’s product releases in the form of a musical.
It is hard to tell how much the healthcare system is shaping Epic’s software development plan versus the other way around. I’m sure it is some of both.
Epic is incredibly successful at energizing its customers and getting them to evangelize and espouse the virtues of their product for them. And we all pay to fly out to Wisconsin to do it! When I walked by it, their usability testing lab had a more than half-hour wait to get in and a line down the hallway.
54% of the US and 2.5% of the global population have an EpicCare chart. There were 5,000,000 Epic<—>Epic information exchanges in Aug 2014.
January 23, 2014 Leave a comment
The Most Important Digital Health App of 2013: Bugs and Drugs
In a year that saw consumer-facing digital health app after consumer-facing digital health app, the app that impressed me most was actually clinician-facing, not consumer-facing. In 2012, the digital health apps that stood out to me most were Kinsa, a smartphone-connected thermometer enabling real-time community maps of infectious disease, and GeckoCap, a wireless sensor-in-a-smartcap for asthma inhalers enabling parents to track their kids’ asthma. (Of course, for fairness sake, I’m leaving out Tidepool, the open platform for type 1 diabetes for which I’m medical advisor, and about which I am incredibly enthusiastic.)
When seeing new digital health devices and apps, I usually have one of three reactions, either: a) “Nope, next!”; b) “This has potential, I want to hear more about it”; or c) “I need to immediately call everyone I know and tell them about what I just saw”. This year, reaction C came from the AthenaHealth/ePocrates Bugs and Drugs app. This app makes me feel optimistic about real progress happening in healthcare. This app makes me feel like the promise of the Learning Healthcare System is either upon us, or truly just around the corner.
If you’ve not seen this app yet, stop reading this article for a moment (come back to finish it, of course!) and go download it from the App Store. The Bugs and Drugs app is a real-time, aggregated, cloud antibiogram.
What’s an antibiogram?
Here is an example of the 2011 UCSF adult antibiogram. First, a quick explanation for the non-clinician. To test a patient for urine or bloodstream infections, clinicians order cultures to see if bacteria will grow (literally) out of the respective collection sites from a patient. If bacteria grows from a culture and the patient is thus deemed infected, tests are done to see which bacteria is the specific cause. Additional tests are then done to see which antibiotics will be effective at killing this particular bacteria strain. This is known as sensitivity or susceptibility data. This information can make the difference between giving a patient an ineffective antibiotic and an effective one. Without it, we as clinicians are guessing about which bacterial strain we think the patient might have and which antibiotic to use. We base this on our knowledge about which bacteria are most commonly pathogenic and which antibiotics are designed to kill which bacteria. We also use available past data about cultured bacteria and antibiotic susceptibilities. This last piece of data comes from antibiograms. Many hospitals regularly publish an antibiogram, a handout that aggregates all of the culture and susceptibility data from each culture site (e.g. blood or urine) from the past year. It shows the relative frequency of the occurrence of each bacterial strain and the frequency of each particular bacteria being sensitive or resistant to each common antibiotic. For example, in the example UCSF antibiogram linked to above, there were 810 E. coli isolates (the most common bacteria isolated), and 85% of these were susceptible to ceftriaxone, a common antibiotic. You might find that in another hospital in another region of the country, say North Carolina, that the sensitivity rate of E. coli to ceftriaxone is 35%. Thus in the first hospital, the treating doctor would be likely to use ceftriaxone to treat the next patient with an E coli urinary tract infection, whereas in Texas, the doctor would certainly want to choose something else, knowing that ceftriaxone is unlikely to be effective.
So, this information can truly be life or death information. It also contributes greatly to the concept of antibiotic stewardship and appropriate use of antibiotics to maintain their effectiveness for future use. Traditionally, antibiograms are published regularly with an aggregation of the previous year’s data for each particular hospital. But, that is static data, a collection of one year at a time. It is also data bound within the physical or virtual walls of each healthcare organization or medical center.
Bugs and Drugs: An Antibiogram for the Learning Healthcare System
The Bugs and Drugs app has taken this concept and moved it into the cloud era. The app capitalizes on the fact that AthenaHealth, as a cloud EHR provider, is able to aggregate all of the clinical data from their EHR, in real-time. They have aggregated together all of the bacterial culture and antibiotic susceptibility data from all of their users and display it in real time in this app. You are a doctor in Wichita and your patient has a urinary tract infection? Pull open the Bugs and Drugs app and you can actually see what the most common bacteria are in the Wichita area right now that are causing urinary tract infections. You can see which antibiotics are effective against those bacteria in the Wichita area right now. This data is not from last year, it is from the last few weeks. This data is not just from your hospital’s lab, it is from all of the hospitals’ labs in the area.
The catch of course is that this still lacks true health information exchange. While the data does cross boundaries between health systems, it does not cross EHR vendor boundaries, coming only from AthenaHealth locations. So, in the example above, you would not be getting data from every location in Wichita, just those that use AthenaHealth.
However, the really important thing about this app is that it shows on a nuts-and-bolts clinical level what we can do with aggregated real-time clinical data when it is put into a useful format in the hands of a clinician. This information can influence care right now, for the patient sitting right in front of you. This is the realization of the possibilities of the Learning Healthcare System, moving valuable information much more efficiently into the hands of the treating physician. I predict (and hope) that we’ll see many more innovations like this in the coming year.
December 16, 2013 Leave a comment
The current paradigm of office visits every three months for PWDs (people with diabetes) is not the right model (nor is it for other similar chronic conditions). The management of diabetes requires a patient to make dozens of daily self-management decisions. “How much insulin should I give for this slice of pizza? Do I need to eat a snack to prevent my blood sugar from going low before I go for a jog?” Diabetes related questions and issues do not occur on an every-three month basis in synch with this current model for office visits. They are predictably unpredictable. Accordingly, to best serve our patients, our system must be flexible and nimble.
In the current model, I see a PWD in my office and let’s say, for example, that we decide together to make a change to his insulin to carbohydrate dosing ratio. He then leaves my office and we wait three months to reconvene and see if that dosing plan change is working or not. It’s not that it takes three months to decide. We could probably know within a week or two if the change is working. It’s just that healthcare isn’t set up that way. Our entire world now, in every industry and facet of life, is about data, analytics, and metrics. Other industries have learned that rapid feedback loops are effective. Adjusting a PWD’s insulin to carbohydrate dosing ratio should be no different. By the time he comes back to my office three months later, the opportunity for learning may already have been lost. Neither one of us has gotten timely and relevant feedback about our decisions. We may have lost the opportunity for a teachable moment. Healthcare needs to develop a new model where these feedback loops are much tighter and much faster, actually capitalizing on opportunities for teachable moments. (Sidebar: One doctor who realized this years ago was Dr. Jordan Shlain, who founded HealthLoop) Research studies show that PWDs are more successful and confident with managing their diabetes when they feel like they have the backup and support of their clinical providers looking over their shoulders to make sure things are going ok. If we were to design the system from scratch to accomplish these goals, we probably would not have built it to rest on the concept of office visits every three months.
So, what should be the future model of a Diabetes and Endocrinology clinical practice? Here’s what I imagine my practice looking like in the (hopefully near) future. Instead of having 16 office visit slots per day of 30 minutes each, I imagine myself seeing 5 patients a day for 45-60 minutes each, allowing us to take our time working together in person and truly addressing the needs and goals of the patient. These longer visits are essential for a patient new to my practice, a patient with a complicated or unknown diagnosis, a patient with complications or a major change in their disease state, or for discussing major changes in therapeutic course or strategy. The rest of my day will be spent using a dashboard to do remote population management, looking for trouble spots among my patient population and focusing in on those, and doing telemedicine, connecting with patients through video-chats to make more minor adjustments and to do brief “check ins.” Ten minutes spent with a patient at the point where there is a teachable moment like a low blood sugar from walking the dog might be more effective than a standard 30 minute office visit every three months. We’ll have to test this hypothesis, of course, but we must try it.
This is why I’m brimming with so much enthusiasm and excitement about working with the non-profit, Tidepool, who is building an open data platform and a new generation of software applications for the management of type 1 diabetes. Tidepool will provide us with the technology infrastructure to reach this vision of more frequent feedback loops and teachable moments. I’m also very excited about the work that my UCSF colleagues, Drs. Ralph Gonzales and Nat Gleason, are doing to pilot the use of telephone visits and e-visits with patients in place of office visits. Their work is paving the way toward demonstrating efficacy of e-visits, helping to achieve payer reimbursement so that such a model can take root.
December 11, 2013 1 Comment
I recently had the fortunate opportunity to be part of the inaugural UCSF Lean Launchpad course, formed by Erik Lium and Stephanie Marrus at UCSF, founded by Steve Blank, and taught by Steve and our digital health cohort instructor, Abhas Gupta. This was a very intense and demanding ten week class that was not about reading and memorizing and taking tests, but about going out and talking to people; “getting out of the building,” as Steve famously says. The fundamental insight that led to the offering of this course was that scientific and clinical innovation in healthcare does not happen in a vacuum. While everyone knows how important it is to test and validate scientific hypotheses, it turns out that it is just as important to test and validate your business hypotheses. Moreover, these should happen in parallel. This business model hypothesis testing cannot be outsourced after your scientific validation is completed. This business hypothesis testing cannot be done by sitting in your office and bouncing ideas off colleagues. Just as we demand data to prove scientific hypotheses, we need data to prove business hypotheses. Otherwise we’re just guessing.
The Business Model Canvas and Lean Launchpad provide the framework for innovators to literally get out of the building and talk to dozens of customers, partners, and others to help validate, or more often, invalidate, their hypotheses. Without doing this, talented people will often waste literally years of effort pursuing a product that nobody really wants to use and that nobody will pay for.
This is not news to the world of entrepreneurs at large, who have heard these ideas from Steve, Eric Ries, and others for years. However, I think this is still a novel concept in the life sciences and healthcare. Without validating product-market fit, revenue strategy, channels, and the other parts of the business model canvas, healthcare innovators are hurting their chances at disseminating their products to reach broad audiences. To fully realize the efficiencies of translational medicine, healthcare has to buck the belief that science and commercialization happen sequentially rather than in parallel. One caveat: There’s obviously something still to be said for early basic science, where one can explore basic mechanisms without having the constraints of having to worry about commercialization. But for anybody who is working on the more translational end of the innovation spectrum (i.e. the entire digital health industry), doing this is mandatory.
It was amazing to see the changes in strategy among the teams in our class as the weeks went by. Making Friends started out planning to build a game to help socialize children with autism, but realized along the way that parents and special needs schools were much more interested in having a dashboard to communicate and track the childrens’ progress. Tidepool, for whom I’m a medical advisor, started out thinking that our early customers would be tech-savvy 20-somethings with type 1 diabetes, but quickly learned that the most interested customers would be parents of children with type 1 diabetes (see the video about our process here). The Lean Launchpad class was filled with similar stories — we all found that most of our initial guesses were flat out wrong once we went out and talked to people. As Steve always notes, one smart person is not as smart as the collective wisdom of hundreds of customers.
Following these lessons will be crucial to future successful innovations in healthcare and I sincerely hope that this curriculum spreads throughout the healthcare community. We in healthcare have to have the courage to get out of the building and test our assumptions early instead of blindly plowing forward. We should apply the same rigor to our business plans and dissemination strategy as we do to our science. We should shed the attitude that, “if we build it, they will come.”
A hearty thank you goes out to all of those who designed this curriculum and ran this class.
April 29, 2013 1 Comment
I went in to the dermatologist last week for an annual skin check and, instead of a humiliating, cold, and uncomfortable paper gown, this cotton spa robe was instead waiting for me to change into. My experience of whether I was working with an empathetic and caring physician was shaped before she even set foot in the exam room. Small touches like this robe can make a dramatic difference in the patient experience. This does not mean that “luxury” can or should replace high-level medical care. However, thoughtful touches like this robe can enhance and augment high quality medical care to make it even better, and we should not ignore these opportunities to make our patients feel more comfortable.
April 19, 2013 Leave a comment
I am just finishing up a packed few days at TEDMED 2013 as a FrontLine Scholar. There were over 1,800 people there, from a broad spectrum of occupational backgrounds, countries, skills, and areas of interest within healthcare. This made for an unending cascade of “unexpected connections,” the theme of the conference. Indeed, though there were many engaging speakers who told stories about turning personal tragedies into discoveries and new passions, to me, the real action at TEDMED was away from the conference stage at “The Hive” (set up with booths showcasing innovators as well as comfortable and open meeting spaces). I met dozens of amazing people, with whom I had dozens of thought-provoking conversations. I will follow with another blog post about some of the specific companies that I met and spoke with at The Hive. There is more to write about from 3 1/2 days at TEDMED than can fit in a “short” blog post.
Here are some of the overall themes that emerged at TEDMED this year:
The popular themes among the startup companies at the Hive (or discussed in speeches):
I would love to hear from others who were at TEDMED or following via Twitter or TEDMEDLive to hear your thoughts and opinions. I’ll be blogging more later about other aspects of TEDMED…