The Most Important Digital Health App of 2013: Now THIS is a Learning Healthcare System

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.

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.

Redesigning HealthCare: More Thoughtful, More Caring

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.

Spa Robe and Sonos at Doctor's Office

 

 

 

mHealth is “so hot right now”… Ten themes from the 2012 mHealth Summit

To quote Mugatu, Will Farrell’s character in Zoolander, mHealth is “so hot right now.”  In this spirit, nearly 4,000 people came together for the past several days outside of Washington DC for the 2012 mHealth Summit organized by mHIMSS.

For anyone who was sitting at home and playing buzzword bingo during the conference, here are the words that would have comprised the winning row: interoperability, gamification, wellness, big data, social, consumer, adherence, re-admission.

 

My Top Ten Takeaways From the 2012 mHealth Summit

1) mHealth adoption will be consumer-driven.

At this point, I think few people question this.

2) User interface and user experience are lacking.

Because of point 1 above, user experience and user interface are critical.  For something to have durability (or “stickiness”) with consumers, it is going to have to be simple, engaging, intuitive, and heck, maybe even delightful.  Most of the current crop of products has work to do here.  One up-and-comer in the StartUp Health class that I really enjoyed seeing was designed by a RISD graduate and is called Thryve.  I have also yet to see a person interact with the ECG-in-an-iPhone-case, AliveCor, and not get excited.  More products need to generate these enthusiastic reactions.

3) We need to use mHealth to solve real problems, and do so in thoughtful ways.

Sometimes the trouble with an mHealth app is simply that it wasn’t designed based on a real clinical problem or need.  No amount of snazzy UI can fix this.  I was encouraged to meet many very intelligent and thoughtful people at the conference who are working hard on big problems and using rigorous, scientific approaches, for example Ginger.io and the team at University of Toronto, among many others.

4) Business models are still being worked-out.

There are still not a lot of success stories to guide the industry and everyone seems to be feeling their way around in the dark.

5) Corporate wellness is “so hot right now.”

One of the proposed business models that seems to be popular is to market a product to large employers as a method for improving employee wellness.

6) Scott Peterson (Verizon): “We cannot allow walls around data to continue.”  We need real interoperability.  

Although the term “interoperability” falls into the “so hot right now” category, this often seems to mean, “I want everyone else to interoperate with me.”  I participated with Open mHealth at the conference, who is trying to foster a community towards the goal of true interoperability.  Open mHealth recognizes that patients should be the ones to control access to their own data.  I hope the rest of the industry catches up to this idea.

7) Physicians need to change.  Now.

Vinod Khosla famously and provocatively predicts that “80% of the work that physicians do today can be done in the future by computers.”  Everyone can waste their time arguing the details, but would be better off realizing that the spirit of this comment is accurate, and instead focus on how to facilitate and shape this transition.  This does not mean that 80% of doctors will not be needed.  It means that what we do will change.  Big data, analytics, and artificial intelligence will be able to do many tasks better than physicians.  I, for one, am happy about this… I believe that these tools, when built properly, will make me a far more effective and efficient physician.  My colleague at UCSF, Dr. Seth Bokser, told me that he focuses training his pediatric residents on empathy and decision-analytic skills, worrying less about rote memorization and knowledge.  He’s right, and medical education should reinforce this.

8) Research techniques are needed that better fit mHealth.

There was an excellent panel at the conference where this was discussed by Dr. Joe Caffazzo from the University of Toronto and Dr. Bonnie Spring from Northwestern.  The general consensus was that traditional randomized controlled trials (RCTs) are too slow and too expensive, and that by the time they are completed, the technology they are studying may often be obsolete (Dr. Spring gave the example of a recently-completed RCT using a Palm Pilot!).  Usability testing and other qualitative methods are important for building a good, user-centered product, but may not provide high-quality evidence for clinical effectiveness.  Newer models are needed.

9) Despite being a buzzword, “wellness” actually is important. 

The current healthcare paradigm focuses too much on treatment of end-stage diseases.  In so many cases today, these diseases are all linked by stemming from the milieu of obesity, insulin resistance, and inflammation… heart attacks, strokes, sleep apnea, diabetes, kidney disease…  I think that “wellness” as a buzzword grates on people when it is used in the context of the “worried well” obsessing over minor details.  But as a US and world population, where the above health problems are becoming overwhelmingly expensive, we really do need to figure out (and soon!) how to promote healthy eating, exercise, and other good lifestyle choices for those who are not yet on board.

10) Take the stairs.

There was a lot of high-tech, whizz-bang, cutting-edge stuff on display at the conference.  And yet every time I looked, at least 90% of the people seemed to be taking the escalators instead of the stairs between conference sessions (reminding me of the below photo).  If the 4,000 people in the US who are the most gamified, FitBit’ed, and social networked won’t take the stairs, we must still have our work cut out for us.

 

take-the-stairs

 

Seven tips to prevent medical technology from ruining the doctor-patient relationship

Does this sound like something that has happened to you?  You are driving, you stop at a red light, and all of a sudden you find that your iPhone has migrated its way from your pocket or the passenger seat of the car into your hands.  You push an elevator button and pull the phone out of your pocket to glance at it in that split second while waiting for the door to open.  You eat dinner with a group of six friends and everyone is buried in Facebook rather than making eye contact.  In all facets of life, we are quickly becoming more entangled with our machines, allowing them to become extensions of ourselves.  The hallowed walls of the doctor’s office have not shielded out this rising tide.  This “Piece of my Mind” by Elizabeth Toll in the June 20th JAMA eloquently captures what so many of us have been feeling and seeing over the last few months and years.  Here is an excerpt of her opening paragraph and the drawing she discusses:

Dr. Toll goes on to discuss how this particular physician is someone overflowing with empathy for patients and enthusiasm for medicine.  Unfortunately, the computer has now demanded his attention, which he can no longer fully devote to his patient.  I agree wholeheartedly with Dr. Toll and I hope that her article will spark a dialogue about this issue in the medical community.

Part of the problem is the current generation of electronic health record (EHR) systems.  They demand too much cognitive effort to use.  In fact, Horsky et al showed that users of a CPOE system used twice as much cognitive effort on system operation as on patient-centered clinical reasoning.  This balance has to shift.  Nobody wants her physician wasting his energy and focus like this.

This improvement in EHRs will happen.  As was pointed out on Twitter this morning by @ReasObBob: “#EHRs will get better. Poor EHRs are not the problem but the symptom. New approach needed. We’re working on it.”  Bob is right.  The current generation of EHRs has been built to meet the demands of a healthcare system that is focused on compliance and billing.  We got what we asked for.  This time around, let’s ask for what we really want.  Let’s ask for EHRs that are sleek and streamlined, easy to use, and that augment the high-quality and high-empathy medical care we want to provide.

What are physicians to do in the meantime?  I have spent some time in the last few years thinking and reading about this.  How can we best maintain the doctor-patient relationship in the age of the EHR?  I offer you seven tips:

1) Set-up your office properly, with placement of the chairs, monitor, and keyboard to best support good eye contact between you and the patient.  Don’t allow your office to become like this drawing, where your chair could put your back to the patient.  This is common sense, not Feng Shui.  (I will post some photos of exam rooms at the bottom of this blog piece to allow you to start to think about what works and what does not work)

2) Get a quiet keyboard.  If you think this sounds trivial, try this: Spend one day in your clinic using a loud keyboard and then switch to a quiet one.  You’ll see.

3) If you can, spend thirty seconds preparing the electronic visit before you walk in to see the patient so that you are ready to hit the ground running.  You want to be immediately ready to let a patient start talking to you without interruption to start the visit.  Visits get off to a bad start when they go like this: “So, what brought you in here?”  “Well, my thyroid…” “Hold on a minute, I have to log-on and get a new progress note open so I can write down what you say.”

4) Let the patient see your screen.  Hopefully you are not reading ESPN.com when you are talking to your patient.  Let them share the experience with you, and share the fact that you are populating their medical record.  I have on many occasions had this lead to bonding moments with my patients when we are both hunting through the CPOE (computerized provider order entry) system for a particular type of glucose test strip prescription or some other seemingly hidden or obscure task.

5) For part of your visit with the patient, stop typing, take your hands away from the mouse and keyboard, and use the body language we learned how to use as first year medical students in Introduction to Clinical Medicine.  Every visit has at least one natural moment when the patient has to be certain that one-hundred percent of your attention is focused on her.

6) Practice.  Seeing patients while using an EHR is a learned skill.  None of us were able to handwrite a perfect note while talking to a patient the first day of medical school.  The new generation of medical students will learn how to talk to patients while typing from day one.  At UCSF, the new Kanbar Teaching and Learning Center has simulated exam rooms to help medical students learn this (although, embarrassingly, you’ll notice in the photos on their website that the computer monitors are buried in the corner of each exam room, assuring the “back-to-patient” syndrome).

7) Remember that this is our chance to take back the medical record.  Let us not forget that, even with paper charts, the medical chart has increasingly become about legal protection, billing, and reimbursement.  The EHR gives us a clean slate, a new opportunity that brings us legible notes and notes that are immediately visible to colleagues.  Take advantage of this.  Write good narratives.  Tell your patients’ stories.  Make the medical record useful again.

Sample photos of exam rooms

                     

(Note: This was originally a guest-post on the blog of my friend and colleague, Dr. Russ Cucina, at http://russcucina.wordpress.com/ and is re-blogged here for my readers)

Diabetes is hard: A humbling experience with “Er5”

I don’t have diabetes.  But I do think about diabetes a lot, read about diabetes a lot, and certainly talk about diabetes a lot.  So, this past week, I decided it was time to walk the walk.  I opened up a shiny package for a new glucometer with the plan of monitoring my glucose 3 or 4 times a day for several days.  I actually read the instruction manual on how to properly set the time and date, and did so within a few minutes.  As long as I was going to do this, I at least wanted my data to be accurate, a true “quantified-self” experiment (of course, choosing a night where I went out for a hamburger and fries was a true test of my pancreas’ abilities!).

Then, like a know-it-all physician, I tried to check my sugar.  “Er5” said the screen.  Hmmm.  Did it again.  Punched hole #2 in my finger.  Ouch.  “Er5.”  Maybe I didn’t get a big enough drop of blood.  So, I cranked up the dial on the lancet device from “3” to “9” so I could get the deepest finger puncture and guarantee a burgundy nugget for the test strip.  This time, “ouch” out loud.  “Er5” on the screen again.  I did this several times, howling in pain down the hall of my apartment, and said to my fiancee, “this hurts!  I can’t believe I ask people to check their sugar multiple times a day!  And worse, I can’t even do it right!”  At this point, I figured the test strips must be defective so I googled “Er5 onetouch ultramini” to see what was going wrong.

I didn’t have another vial of test strips so I was hopeful that “test strip damage” was not my issue.  If it was, my experiment would be over rather quickly.  I had to read a little further to find out that an “incompletely filled confirmation window” actually means, “you are not putting the blood on the test strip properly.”  It turns out, rather than placing the drop of blood to the side of the test strip for it to be sucked in to a small channel, I had been just plopping the blood on top of the strip.  Whoops!  Embarrassing!

After discarding nearly a dozen wasted test strips into the garbage, I finally struck gold and got a real, live number on the screen.  “86” it read, and though my finger stung, I had finally erased the humiliating sting of “Er5.”  For the next 24 hours, I checked my fingerstick on schedule, but noticed that it REALLY hurt and that I had to talk myself into pressing that button on the lancet each time, knowing the pain that would follow.  I commented about this to one of our diabetes educators, Catherine, who laughed and spent ten minutes showing me the proper way to use a lancet to get a blood sample, ie using the side of my finger instead of the tip and shaking my hand toward the floor to get blood flowing into it.  Turns out, if you do it the right way, you can get a drop of blood with a lot more ease and a lot less pain.  Though I consider myself pretty good at helping analyze blood sugar patterns, I finally now, after four years of medical school, three years of Internal Medicine residency, a year as Internal Medicine faculty, and nearly a year of Endocrinology fellowship, actually know the right way to check a blood sugar.

Luckily for me, this experience was only that, and is not something I have to endure on a daily basis.  But as I spend my career trying to improve diabetes technology and caring for those of you with diabetes, you can at least know, that I do understand your pain.  And if a patient one day asks me why her meter says “Er5,” I hope she will forgive me if I take a moment to laugh at the dozen half-filled-with-blood test strips in my garbage can.

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