A Lesson In Clinical Decision Support: We Cannot Defeat Human Nature

      Our UCSF Clinical Informatics group met a few months ago with several representatives from a major Health IT vendor. The vendor, we’ll call them RxLabs, is a provider of pharmaceutical related knowledge in many domains, including decision support tools for the EHR. Our conversation centered around how to better customize medication alerts. We talked about the popular topic of “alert fatigue,” and how to improve EHR decision support tools to improve their impact, rather than just being white noise annoying clinicians.
      The vendor was walking us through a slide-deck about their hypotheses and data about EHR medication alerts and we were having a vibrant discussion about how to improve provider adherence with decision support. We saw slide after slide about how to make pop-ups smarter and about trying to get more buy-in from providers with paying attention to alerts. After all, why would a provider trying to take care of her patient ignore an alert that is trying to help provide an important message? It must be sloppiness or laziness on the part of providers!
      Ten minutes in to this conversation about drug alerts, up pops the following:
Windows 7 Display Alert
      I’ll give you a second to guess what happened next.
      Without a moment’s hesitation or thought, the presenter clicked the little X in the upper right corner. Our conversation went on. More slides. More data about medication alerts in the EHR. Ten minutes later, guess what happened?
      Up came the same pop-up Windows alert. The presenter again, hastily, without paying attention, and perhaps giving a small huff of displeasure, clicked the little X in the upper right corner. More slides, ten more minutes, same thing. You get the idea.
      This happened three times, with each passing pop-up, the presenter becoming slightly more annoyed. The fourth time the pop-up appeared, my colleague Russ Cucina, the Associate CMIO at UCSF, paused the presenter to have us all read the pop-up alert message. We took ten seconds together to learn that selecting any of the three choices rather than clicking the “x” would have satisfied the alert and kept it from coming back.
      The room broke out into laughter. We all understood our own hypocrisy. We cannot defeat human nature.

“But who is going to pay for it?!” — New Medicare Billing Codes for 2015 Include Remote Chronic Disease Management

“But who is going to pay for it?!”
This has been the common refrain for years. The world of diabetes care experienced this dilemma relatively early-on, as some of the earliest digital health tools were in the diabetes field. When home glucose monitoring became easier and more ubiquitous, and then continuous, people with diabetes were all of a sudden collecting loads of data at home that might dramatically impact their care… and then waiting 3 months to come in to the office to discuss that data. I am asked this question all the time about the startup company I advise, Tidepool, because Tidepool facilitates better and easier remote diabetes care.
It is not just diabetes. In general, there has been more hype and excitement over digital health than impact in clinical practice. A significant reason is the mismatch between payment models and digital health use cases. We still largely live in a fee-for-service world, where we are paid to provide care during a “face to face” office visit and everything is measured by having a “billable encounter.” Most digital health tools, by bringing platforms, apps, sensors, devices, and analytics onto mobile and onto the consumer at home or at work, facilitate care happening outside of my exam room. This does not generate a “billable encounter” and there is no “face to face” office visit.
I don’t think I’m revealing anything new here by saying that it has been beyond a tough sell getting the healthcare system to implement digital health innovations in a fee-for-service environment. How enticing is it to anybody to do a lot of work for free? Doctors do it, but begrudgingly and in small batches.
As for Tidepool, we’ve known that it would be a tough sell initially, but had faith that payment models would change and that we would be ready when they did. I’ve written before about how I’d like to see my future practice operate once payment models changed. And now they are continuing to do so.
Medicare now looks to be slowly facilitating change to align payment models with exciting new technologies. As many media outlets are reporting (see CNN Money, iHealthBeat, Modern Healthcare, mHealthNews), CMS has announced that it will add new telemedicine billing codes starting January 1, 2015 (the CMS document is here). Doctors will be able to start billing Medicare using the 99490 and 99091 CPT codes for providing non-face-to-face, remote care, for patients with chronic conditions. Medicare has never in the past paid for the provision of these services.
A huge caveat that, in my opinion will continue to stymie progress, is that Medicare will still require patients to be in rural areas for these payments.
But, this remains a step forward toward the holy grail of aligning payment models and incentives with new digital health technologies. Paying doctors to provide remote, non-face-to-face care for patients with chronic diseases is the right thing to do for patients and for the healthcare system. Digital health innovations that would sputter under current payment models may take flight once remote care is reimbursed.

What I Learned At Epic UGM… And Other Random Thoughts

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.

Feedback Loops and Teachable Moments: The Future Diabetes Care Paradigm

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.

UCSF Lean Launchpad: The right way to redesign healthcare

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.

The Future of Diabetes Management: Social Networking and New Technologies

I gave a talk yesterday to a great crowd at the annual UCSF CME conference, Diabetes Update.  The slides from my presentation, “The Future of Diabetes Management: Social Networking and New Technologies,” can be viewed on Slideshare.

MedX 2012 Conference at Stanford

I spent a few hours this morning watching the livestream of the MedX conference at Stanford organized by Dr. Larry Chu.  From the portions I have been able to watch, this looks so far to be a really great conference.  The speakers this morning included a panel of self-trackers, Dr Paul Abramson (a physician who uses self-tracking in his office), Anne Wright of BodyTrack, and Sean Ahrens of Crohnology.  As I’ve always found with the mhealth and quantself communities, even from my office on the other end of the peninsula watching the video via livestream, the energy, excitement, and passion are phenomenal.  A few themes and ideas stand out from MedX itself and from the Twitter feed #medx, meriting some discussion.

1) Self-tracking is about the process, not the data.

This is absolutely true.  Using diabetes as a reference point, just looking at data for the sake of data is a waste of time.  People with diabetes make decisions all day, every day, most of which are minor and subtle decisions driven by habit.  Looking at data might help them make changes, but it’s not very likely.  More important is that they actively engage with the data and learn from it.  This process leads to crucial education about the self and personal habits that might help lead to different behavior the next time they are faced with a decision.  The act of gathering the data itself also enables personal exploration and revelations that would not be otherwise possible.  Self-care behaviors and self-awareness have no choice but to improve if someone is actively engaged in self-tracking.  Data should include not just numbers but life stories and context for what was going on at the time the numbers were collected.

2) Patients want doctors who believe them.

We heard this from many of the self-trackers and e-patients at MedX.  There are many patients who have found our current healthcare system too impersonal and uncaring.  I’ve heard this over and over, seen it happen in places where I work, and experienced it with family members.  There are a million reasons why this has happened and changes have to be made to medical education and healthcare economics in order to start making patients feel cared for again.  Regardless, we have no excuse.  No matter what pressures exist on doctors, we must retain compassion for the person sitting in front of us.  Everything else follows from this simple rule.

Sometimes, the problem can be that our current body of medical knowledge and experience is inadequate and only scratches the surface of the true pathophysiology of human disease and suffering.  All physicians have had experiences with patients where we listen to the patient describe their symptoms and we know something is wrong, but we have no diagnosis, no terminology with which to describe their particular situation.  This is always an incredibly frustrating experience for patient and physician alike.  As physicians, we are left not quite sure what to do, which frustrates us, because we are trained to do (though we should more often be like jazz musicians and place more focus on the empty space, ie what not to do).  Despite our frustration, physicians still have a choice in these situations.  The patient’s symptoms can be believed and empathy given, or the patient can be told, “I don’t know what you have, but at least you don’t have ______.”  I’d imagine patients prefer seeing physicians who do the former.

3) Patients want doctors who are willing to engage with their self-tracking data.

Even as a self-tracker and innovator in diabetes data and tracking, I find this leads me to some internal philosophical conflict.  Do I believe that self-tracking will help many patients improve their health?  Yes.  Do I believe that gathering self-tracked data will play a major role in the future of healthcare?  Yes.  Do I want my patients to self-track and to share their data and their experiences with me?  Absolutely!  Does the healthcare system have the resources and ability to handle this?  No.  Not right now.

First: We’re not ready yet for self-tracking data from a technical standpoint.

The simple fact is that most healthcare organizations are still trying to get an electronic health record implemented.  Getting self-tracked data into EHRs may be on the radar, but it is not imminent.  Once we have self-tracked data in the EHR, then what?  At least the patient’s medical record then becomes more whole, but EHRs have already left physicians in the position of having information overload, and this is in a situation where physicians already lack sufficient time to spend with each patient.  New piles of data will only exacerbate the situation.  Smarter ways of organizing and filtering the information are going to be absolutely necessary to make this manageable and to allow physicians to use the data with patients in the way it should be used.  (As a slight aside, having a single, unified patient-centered record is also a precondition for a functional system.  None of this works if each patient has their data fractured over ten different healthcare organizations, PHRs, and websites.)

Second: We need to find the proper place for self-tracking tools and data within healthcare, which requires a better understanding of their effect on healthcare quality and costs. 

There was a Twitter comment in the #medx stream expressing outrage, saying, “Cannot believe that some diabetes tracking tools are not covered by some insurers. Absolutely nonsense!! give them the tools!!!”

This was in reference to a panelist with type 2 diabetes who used a Dexcom CGM and had to pay for it out of pocket.  This Twitter comment shocked me.  It is not news to anyone that the resources of our healthcare system and entire economy are strained by rising costs.  There is just no way it is sustainable, acceptable, fair, ethical, or you-choose-the-word-to-put-here for everyone to expect that their healthcare insurance should cover every device they want.  Our country has to stop expecting this.  While there have been many new devices in healthcare that have achieved better health at a reasonable cost, history is littered with examples of new devices that have either been overwhelmingly expensive for minimal health benefit or have flat-out had negative impacts on health.  So, there simply HAS to be research done (hopefully efficiently and effectively) showing that a new device has health benefit, and at some reasonable cost, before we expect insurers to cover the device.  Using the specific example of a CGM for a type 2 diabetes patients, there are too many people in the country who don’t even get basic, proven care for type 2 diabetes, like eye and foot exams, blood pressure control, or metformin, for us to be claiming that all insurers should be covering this device for all type 2 patients.  If a patient wants to pay for an unproven device or treatment out of pocket, I have no qualms, but we cannot expect society to pay.

This serves as a clear reminder to those of us innovating in healthcare that successful innovation will be mindful of the value equation, ie either better healthcare quality or lower cost, or ideally both.  I’m incredibly optimistic and excited about what lies ahead in healthcare innovation, because I think we will create things that improve healthcare value.  I believe that self-tracking will be a major component of this, and will be especially important in empowering patients, bringing new and critical data into the doctor’s office, and creating a new paradigm for the doctor-patient relationship.

What a great conference!  Thank you to Dr. Chu and all of the speakers, panelists, attendees, and other remote attendees!

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