The Four Key Features of EHR Integration: Move Beyond “Data Dumping”

A rapidly growing number of health innovations such as mobile apps, diagnostic tools, and sensors are being developed with a focus on enabling health and wellness outside of the traditional medical office visit. As Eric Topol points out in his new book, The Patient Will See You Now, many of these tools will help people independently understand and manage their health. A long history of medical paternalism will be overturned as health information is returned to the individual and autonomy restored. This is a great trend.

However, we do not have to create an “either-or” dynamic where some health information is held by the healthcare system and other information by the individual. These new technologies will be maximally useful when they enable and facilitate a deeper, richer dialogue within the context of existing doctor-patient relationships. To achieve this more coherent and comprehensive healthcare, we need to bring together the patient, her digital health information from new sources, the doctor, and the EHR.

These concepts of interoperability and EHR integration are being widely recognized as crucial over the next few years in healthcare, as evidenced by the JASON Task Force’s recommendations and the formation of the Argonaut Project.

What concerns me as a practicing physician and informaticist is when I hear people discuss EHR integration as if it means only this:

Data Dump

This represents the idea of taking every single data point collected by mobile apps, sensors, and other tools and passing it all straight through into the EHR. I am always reminded of one of my favorite scenes from I Love Lucy, but instead of desperately trying to stuff chocolates into my cheeks and clothing, the medical conveyer belt could make physicians unable to keep up with massive quantities of inbound data from patients.

I Love Lucy

I think it is this sentiment that has led to articles like this one posted in August 2014, saying that “doctors don’t care about your FitBit data.”

Doctors Dont Care About FitBit Data

I disagree. The truth is that I might care about your FitBit data, depending on the clinical situation, the context of that data, and the way in which it is presented to me. I just don’t know yet. I think it is very likely that there will be many of these situations where your activity tracker data matters a lot! We can do better. We can use new information sources when they are helpful and add value by weaving together a comprehensive view of a patient’s health information that facilitates better conversations between individuals and their doctors, and thus better care. This means that patient-generated data cannot be siloed off from the EHR. It instead must be incorporated into clinical workflows as part of the EHR. To achieve this vision of a more complete EHR integration, I think we need the following:

Four Key Features of EHR Integration

1: Discrete data points: I know, I know. Didn’t I just say we don’t want this? I actually believe we still do want access to discrete data. It just cannot be the beginning and then end of integration. Also, this refers not just to data coming in to an EHR from outside, but clinical data flowing out from an EHR to an app or analytic tool, such as your medication list, medical history, or recent hemoglobin A1c values.

2: Analytics and decision support: We need intelligent rules, filters, and analytics to help route information at the right time to the right person and right place. These rules will work best if they can use data from inside the EHR along with these new, patient-generated data sources.

3: App and workflow integration: Talented and innovative software developers and others are creating new ways of presenting information, such as disease-specific data visualizations. We need to make it easy for physicians to access these within the context of their daily work in the EHR. Physicians are not going to launch and log-on to their EHR and three different applications to compare data, no matter how snazzy and how much media buzz your new app has. Moreover, we should be able to do clinical documentation, make a therapy change, or order further diagnostic testing from within the confines of a new tool and have that documentation, prescription, or lab “order” feed back into our EHR for action. This will keep your medical chart and health record more comprehensive and easier to follow, with less information scattered around different places.

4: Communications integration: Finally, with all of this information passing back and forth, each system is going to be capable of sending and receiving messages between the doctor, patient, family members, and other care team members. Nobody will want to log-on to every individual account to check messages. So, we need to be able to intelligently integrate and route messages so that each person can send and receive messages from the “hub” application that makes most sense to them.

At the UCSF Center for Digital Health Innovation, we are excited to be working toward this vision of comprehensive, workflow-driven EHR integration.

(This post is based on a talk I gave at the Diabetes Technology Meeting in Bethesda, Maryland in November 2014.)

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“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.

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.

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.

TEDMED 2013: Reactions and Themes

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:

  • Watch your backs! Those entrenched in the current model of the healthcare system need to be innovating and disrupting themselves from within their own organizations, or else risk being out of business in a short number of years.  Lip service to change will not suffice.  There are many, many companies and innovators taking aim at current models of healthcare, and while most of these companies will fail, and while change may be slow and halting, it will happen.
  • Bottom-up innovation: Change in healthcare cannot come only from the ivory towers and healthcare professionals.  As a doctor at UCSF, I recognize that this means me.  America Bracho spoke passionately about how innovative ideas should come from within local communities in a bottom-up fashion rather than a top-down manner.  We in the healthcare establishment need not only to listen, but to include the people who are most easily able to identify their actual problems and the potential solutions.
  • Interdisciplinary problem-solving: As discussed by Tim Brown in Design Thinking, to creatively and successfully tackle a big problem, an interdisciplinary team is needed.  Five doctors sitting in a room are not going to solve a major healthcare problem.  We need engineers and patients, designers and artists, marketers and people in finance.  We need them to work together.  The cross-disciplinary problems in healthcare require cross-disciplinary attention.  I was encouraged to see how many talented people with backgrounds outside of healthcare are now turning their attention to solving healthcare-related problems.  While some are doing so with a Willie Sutton “that’s where the money is” philosophy, most are truly dedicated to innovating and solving important problems, and we need their energy and their ideas.
  • Courage: Have the courage to ask difficult questions that everyone else is afraid to ask, and to pursue the answers in ways that other people are afraid to pursue.

The popular themes among the startup companies at the Hive (or discussed in speeches):

  1. Medication adherence.  This was true at the mHealth Summit several months ago and remains true.  There is a lot of attention being paid to trying to track, measure, and improve medication adherence.  Some of the companies at TEDMED: AdhereTx, AdhereTech, GeckoCap, NudgeRx, RxAnte, and others.  There are a number of different approaches being tried, from “smart pill bottles” to reconciling claims data with EHR data.
  2. Crowdsourcing.  This concept is being applied across different fronts and in different ways.  Docphin is creating a social experience around reading medical journals, allowing clinicians to see what the most popular articles are in their field or across all fields.  Science Exchange is creating a TaskRabbit for scientific tasks, matching scientists who have a particular skill with those who have a specified task requiring that skill.  UpRise is converging all of the patient education materials that they can into one common platform for distribution to patients.  Crowdmed is applying the wisdom of the crowd to diagnosing diseases.  Roni Zeiger spoke about “networks of microexperts,” allowing patients to share their knowledge and best practices, announcing his company, SmartPatients.  Larry Brilliant spoke about infection monitoring tools for public health, like FluNearYou.
  3. Psychosocial and behavioral interventions.  The companies on this list included Empower Interactive, Healthify, Omada Health, and Sense Health.
  4. Digitizing the patient. (Slight tangent– Jay Walker made a great point that we don’t really have a word for what to call people in the healthcare context who aren’t sick, ie not “patients” in the traditional sense.  Do we just call them healthcare consumers?)  There is a ton of work being done in terms of capturing physical and biometric data to augment the clinical data available today, both expanding the scope of the type of data we currently collect but also expanding out into the home (shameless plug for my JAMA Internal Medicine commentary).  At MIT, they are developing a portable set of glasses that allow an easier view of the retina as a “window into systemic diseases.”  There are sensors for everything– oxygen, heart rate, falls– you name it, somebody is building it, and the data is most often now able to be transmitted wirelessly to somebody, somewhere (what we’re going to do with all of it workflow-wise is another question for another day!)

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…

 

Asthmapolis: Why Can’t Inhaler Sensor Be Adapted For Diabetes and Insulin Pens?

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.

Asthmapolis TechCrunch Headline Apr 2013

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.

GluBalloon Insulin Dose Tracker

Best of luck to Asthmapolis… they look to be poised to make a major difference in the lives of people with asthma.

 

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.

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