Healthcare IT reading list

My Programmable Self Behavior Change Reading list has been one of my most popular posts.

I still think any Health IT expert should be well-versed in behavior change science, since so many healthcare issues boil down to behavior change problems… either for patients or providers or both.

But the other day, I was having drinks during HIMSS with Keith Toussaint, Matt Burton (both Health IT rock stars at Mayo Clinic) and Sulie Anna Tay (a rising star at Cisco). Soon talk turned to “have you read this, have you read that” (you know how those conversations usually play out) and we started creating a “Required Reading List for Health IT”. I forgot about it until today, when I needed to find some references in one of the books… and realized I had left the project undo. So here are my required reading list for Health IT and healthcare reform, in no particular order:

 

I think its important to listen to end of life issues from Alex Drane. And read the same topics from Atul Gawande Letting Go.

 

 

 

I hate to humblebrag so I will just be plain: David Uhlman and I wrote what is probably the most popular book on Health IT, Hacking Healthcare.

 

Expert Healthcare Hackers

(This is a preview of a talk that I am going to give next week at Healthcare::Refactored, with Karen Herzog)

There are two definitions of the word “Hacker”. One is an original and authentic term that the geekdom uses with respect. This is a cherished label in the technical community, which might read something like:

“A person adept at solving technical problems in clever and delightful ways”

While the one portrayed by popular culture is what real hackers call “crackers”

“Someone who breaks into other people computers and causes havok on the Internet”

People who aspire to be hackers, like me, resent it when other people use the term in a demeaning and co-opted manner.  Or at least, that is what I used to think. For years, I have had a growing unease about the “split” between these two definitions. The original Hackers at the MIT AI lab did spend time breaking into computer resources… it is not an accident that the word has come to mean two things.. It is from observing e-patients, who I consider to be the hackers of the healthcare world, that I have come to understand a higher level definition that encompasses both of these terms.

Hacking is the act of using clever and delightful technical workarounds to reject the morality embedded default settings embedded in a given system.

This puts “Hacking” more on the footing with “Protesting”. This is why crackers give real Hackers a bad name. While crackers might technically be engaged in Hacking, they are doing so in a base and ethically bankrupt manner. Martin Luther King Jr. certainly deserves the moniker of “protester” and this is not made any less noble because Westboro Baptist Church members are labeled protesters too.

Like protesting, Hacking is all about taking a certain set of ethical issues that are important to you, and then performing an act whose central purpose is to restore ethical balance. People with screwed up ethical compasses will give good protesters and good Hackers a bad name.

I like this broader definition because it really shows that Hacking is not at all limited to technology. It relates to “systems”, as long as the “system” is complex enough to encode moral notions. This means that protesting is really just a special kind of Hacking, in fact we might rename it “public opinion hacking”.

Consider Richard Stallman. Stallman realized when he couldn’t get access to printer control software because of a proprietary license, that the license itself was encoding something he had an ethical problem with. Rather than accept that embedded morality, he created a workaround solution (copyleft licenses) that created an alternative with an embed morality that he could live with. The system that Stallman was hacking was copyright and licensing and the modern Open Source movement is the result of this hack.

The notion that technology and other complex systems can have moral notions embedded is neither new, nor mine and I recommend Lessig’s Code and Other Laws of Cyberspace for a full discussion.

I came to this conclusion as we renamed our “meaningful use” book to “Hacking Healthcare“. David Uhlman (my coauthor) and Andy Oram (my editor) seriously considered “Hacking Healthcare Software”, as an alternative title. But in our discussions it became apparent to us that David and I were really hoping to teach people how to use software to change the Healthcare system itself. The software was merely the type of hack that we were proposing, rather than the system being fixed with the hack.

Any efforts to hack healthcare should be embraced because the default settings on the Healthcare system really suck.

We have too many medical errors. We have overtreatment, undertreatment, fraud and disconnected care. Worse, until very recently, we had incentives that were virtually guaranteed to make these problems worse. These problems are merely symptoms of the wrong set of morals being encoded into the healthcare system.

Which leads me to introduce Karen Herzog to you. Karen makes my efforts to hack healthcare look somewhat childish. Like other, more famous e-patients like e-patient Dave and Regina Holiday, Karen, along with her husband Richard Sachs refused to accept the default settings of the healthcare system when their daughter Sophia was born with a rare genetic disorder. Shortly after Sophia’s birth, Karen and Richard were informed that their daughter disease was incurable and that she was dying.

The default settings for the healthcare system in these circumstances could not have been worse. Karen and Richard were offered occupational therapy, physical therapy, grief counseling and “when she turns blue let us know..” by their doctors in a manner that was obviously code for “we cannot help you, sorry for your situationa but get out of our hair”.  Karen and Richard refused to accept this. They did go home, but rather than allow the healthcare system to “wash their hands” of Sophia they created a garden. This literal garden was the first step in creating a community of care that re-engaged their doctors, who were themselves feeling hopeless and overwhelmed a safe environment to try to make Sophia’s life better and to seek a cure. Like all of the greatest “Hacks” Karen and Richard repurposed simple solution and made it apply to a problem that was regarded as unsolvable. They created a literal space that was so welcoming that it inspired collaboration in a group of clinicians that were not used to collaborating worked beautifully. They found ways to make it obvious that Sophia’s space would not be a deathbed, but a different kind of space altogether.

Eventually Sophia died, but only after receiving care that was orders of magnitude better that what could have been accomplished if Sophia would have been hospitalized full time. Hundred of clinicians, friends and family came together to make Sophias garden into a success, in a collaboration that never could have occured inside the walls of any given healthcare institution.

This success was hard-fought. Together, Sophia, Karen and Richard experienced just about every significant problem that patients and caregivers can have. For each hurdle, Karen and Richard continually refused to accept the “default settings” that the healthcare system offered, by responding with hack after hack.

I am humbled to be speaking opposite Karen. Since Sophia died, Karen and Richard have pivoted their design group into one of the preeminent “Patient UX” shops in the country. They have leveraged their troves of poor experiences with the healthcare system, and their methods of working around them, into a series of fundamental insights about how to improve patient experiences with technology and design. They are my default recommendation for design work in the healthcare space.

I have been watching what e-patients like Karen and Richard are able to accomplish for years and I have come to realize that in many ways, they are far more deserving of the honorific of “Hacker” than the bozos who deface websites to make political points. In much the same way that the recognition that MLK Jr was a protester, makes it embarrassing that we have to label the Westboro church members with the same label.

Like the original Hackers who built the Internet and the first computers, e-patients are blazing a trail through the healthcare system. Decades from now we will look back on this class of patient and realize that they remade healthcare by simply refusing to accept the aspects of the healthcare system that typically suck. In the future, when the new norm for doctors is respect patients enough to actually let them finish sentences, we will have this generation of e-patients to thank. Much the same way that we recognize that our iPhones and Androids would not be possible without the pioneering Hackers of the *nix community.

Karen and I will be doing a “dueling keynote” at Health::Refactored, asking each other difficult questions about the state of the art in design and technology in healthcare. I hope that the audience will learn some tidbits from me about how to work with software to help fix healthcare, but I think I have made my case that Karen will be the real healthcare Hacker on the stage.

-FT

 

How to change the world over the weekend

I love hackathons.

I love winning them. I love competing in them. I love winning them.  I love judging them. I also love not losing them.

This weekend, I am acting as a mentor to the first Health 2.0 hackathon in Houston Texas. As far as I know (which is not that far, really) this is the first hackathon in Houston to be focused exclusively on healthcare. Serving as a mentor rather than having the opportunity to directly win might seem counter intuitive, given how competitive I am. But I have had complaints about being a “professional” Health IT expert entering these contests, and as one of the organizers of the event, I do not want to be seen as unfair. This was a hard decision to me because in most cases, if I have to choose between winning and being unfair, I choose winning.. but my Houston Health 2.0 co-conspirators prevailed upon me this time…

I do well in hackathons because I know how to avoid the number one pitfall in healthcare hackathons: It is too tempting to make toys.

To really rock a Healthcare Hackathon you have to have a real strategy to build something that will make a difference, but something that you can still prototype in two days. Here are general thought strategies that have worked for me:

  • Have you carefull searched the web for someone implementing your first-blush idea? The android iphone app stores? Your idea is probably not original?
  • Rather than focus on original “ideas” to find “original problems”, clinician partners on your team are critical for this perspective!
  • Seek problems where there is no money to made solving them. Problems that already have money already have attention, it is hard to do original work in those spaces!
  • Only a few doctors are enlightened enough to pay attention to the hacking approach. How can we multiply the impact of a very few doctors?
  • Most patients are not e-patients, they are reactive and unwilling or unable to change their own healthcare behaviors. How can we minimize what each patient must do, but still have an impact?
  • Are there patient pain points so strong that we can rely on at least a few highly motivated beta testers?
  • How can we leverage the cloud, even with HIPAA limitations?
  • How can we crowd-source effectively, ensuring that every participant is evenly and instantly rewarded for contributions? How can we make crowdsourcing fun?
  • How can we leverage pre-existing Open Source code or APIs? Stand on the shoulders of giants… Hello! Obvious!!
  • How can I flesh out my team at a hackathon by pitching to clinical, educational, design, art or video collaborators?
  • If a programming task is hard for me, can I find a geek that can do in a few minutes what it would take a whole week for me to learn?
  • Getting a good idea is easy. Getting a good idea that is small enough for me to finish in two days is hard. How do I trim all the fat?

Here are some ideas that I will be pitching to participants to this weekends hacking contest. If I can find geeks with the required programming skill-sets and the team to ensure that they have the clinical and design backup that they need, I think these are all doable in two days.

Big Data on medical students:

Medical students are the only ones who understand the problems in medical school. I have designed a hack that will allow us to use big data on them directly to discover and fix the issues with our process for making doctors. I think this will require a team who can code in cross-platform Java… but a web-platform programmer could be tolerated in a pinch. SQLlite experience is a plus.

Better medical wikis

Only Wikipedia has the critical mass to sustain itself, so the only way to make a medical Wikipedia is to do it inside Wikipedia. But how do we ensure that the medical parts of Wikipedia are accurate enough for clinicians and experts, but simple enough for the average patient to find them useful. I think I have found a way to use the Wikipedia API’s to dramatically improve the quality of Wikipedia articles on health issues, but I will need a team who knows how to either build a chrome or firefox module…. are perhaps super fancy JavaScript bookmarklet

Cross the channels at health conferences

Every healthcare conference has a back channel, and in my experience at healthcare conferences, many of the real experts are in the crowd tweeting. Conversely the people who line up to ask questions at a microphone are unvetted, a tragic portion of those who ask questions are actually pitching their own projects, or exercising an obsession, or asking a stupid question (and yes… there is such a thing as a stupid question… or at least there are many morons who feel comfortable wasting my time with questions). I am pretty sure it will require something like Node or Pythons Twisted, but I think we can use Twitter to hack health conference Q&A for the better….

The calculus of pain

In healthcare we have policies that help to ensure that “drug seekers” are unable to access excessive amounts of opioid pain killers. Assuming we define “denying a patient pain medications as a positive”, then these policies are “high sensitivity”  (has few false negatives). Said another way, they have been shown to reduce the number of deaths from medication overdoses in those states that apply them. But good policies are also “high specificity” (has few false positives). In this case, a “false positive” is to deny a patient who has legitimate untreatable-without-opioid pain access to effective pain control. The debate is mostly rhetoric here, with law-enforcement and organizations who represent pain patients both resorting to rhetoric  because there is no way to accurately measure false positives. But what if we could create a dynamic visualization that estimated false positives from the data that we do have? Essentially, we could create a “calculus of pain” diagram that both sides could ‘agree’ on, but use differently. As you might expect, this ‘rhetoric negation GUI’ will require extensive D3/javascript expertise.

Simple games for fitness

I am interested in creating tools that use Geocoding and QR codes together to motivate health. I need IOS and/or Android developers for this one.

Twitter plus epatients

Lastly I am interested in the ways that e-patients tend to favor twitter and I might be interested in developing an e-patient specific twitter tool. Need to code in a web-friendly language.

Quantified Self device hacking tools

The QS community very clearly needs a specific tool that I have gotten alot of requests for. You must know either hardware interfacing (usually C or C++ for usb drivers etc) or web authentication (OAuth et al)

Do something awesome using Natural Language Interfaces.

One of the API sponsors for this hackathon is Ask Ziggy which is essentially a “Siri as an API” for app developers. Its a clever idea and there are lots of possible uses here… no specific technical requirements other than to us this API.

Do something awesome with DocGraph

This is of course, our own data set.. and you can read about it at the main DocGraph site.

Do these sound vague enough?

I hope these are pretty vague ideas. I intentionally am leaving out the critical “how” part of each idea!

I hope this list is enough to spark some interest and get developers to attend this conference. I will not be the only one pitching ideas, and teams attending with pre-baked ideas typically do well at these kinds of events. Still if you want to use my ideas, and hear me explain how to do them and why they will work then you need to meet my specific criteria. First, you must be willing to develop  in the open, and under Open Source licenses. I am giving you a hackathon winning idea for no money. (and I am fairly certain, given that I have judged more health 2.0 contests than anyone else) Even if you do not win the contest, these ideas are so good that I will probably be able to make you fairly famous in the Health IT and Health 2.0 communities.

By working on my ideas you kind of hedge against losing at all. If you are able to pull of the projects, then I will give you credit publically for your awesomeness, which is valuable to anyone looking to make a name. For this valuable insurance service,  I need to be able to start from where you left off if you decide to abandon the project after the hackathon… That means github and the FOSS license of your choice (I like the AGPL)

You also -must- have the skillset that I require for a given project for me to give you the details on a project. I cannot have my best ideas just “out there” for people to run off with!! I am pretty sure that I have at least one project for every kind of developer that I can think of listed above. If I could do all of these ideas myself with my programming skill set.. guess what… I would have already done them or I would save them so that I could win some other hackathon! Each of these projects leverages a very specific hack of some kind. Either hacking hardware interfaces, user expectations, software design, data levers or something like. After I describe the “how” of each project there will be an “aha/wow” moment, when you think “We didn’t I think to do that?” (Note I felt this way after seeing IFTTT for the first time). If I am handing you a “wow” world-changing hack then I have to know that you will make us both look awesome when you pull off the hack. Don’t worry if you do not have a specific skillset I define here. I have lots of other ideas based on what you are good at! This especially applies to designers and other artistic types and to clinicians!! All of these projects could use clinical/design help!!

If you have not signed up yet, then I would get over to the signup page now. So far, every Houston Health 2.0 event has sold out so far, and we expect this one too as well. I have some pretty awesome project proposals but I can tell you now that these will just be a few of the awesome ideas that we are bringing to the table for this Hackathon. Most importantly, if you already have a project in mind, then you will be able to find a team to help you hack on your project! All you need is alot of motivation, a little skill and a willingness to collaborate. Or even just one of those three would do…

Looking forward to seeing you there!!

-FT

 

 

 

 

ePatient HIMSS 2012 Badge

Hi,

I am happy to announce with psuedo-permission from the Society for Participatory Medicine (by which I mean that they have not asked me not to do this) a Twitter badge for HIMSS 2012.

There are a handful of the epatients who are attending this years HIMSS (alas, I am not among them) and they have agreed to play a game to help get to know the e-patients. Those who complete the game get to have a digital version of the epatient badge for HIMSS12.

The game is simple. Each of the following e-patients have given me a riddle that they will answer for you either over Twitter, or in person. Plus I have given each of the e-patients attending the conference a super secret code word. That means that you have to either figure out the riddle on your own, use the riddle as an excuse to introduce yourself to each epatient over twitter, and you have to find and post a picture of yourself wearing the S4PM badge!

Then I will generate a digital badge for you that you can use on your twitter background, or any you can use in any other website where you can post an image.  The digital badge will have your twitter username written on it, to prove absolutely that you have earned the badge.

This badge will be issued only for people who complete this puzzle during HIMSS. We might issue different epatient badges in the future, but this one will never be issued again. This is truly a once in a lifetime opportunity. Everyone you know will be jealous of the small graphics file that you acquire here. Truly, your completion of this puzzle will be a story that you can relate to your grandchildren (to put them to sleep).

Seriously, this might be a fun way to get to know some new people at HIMSS and to help spark discussions about patient engagement at HIMSS. I wish I could be there in person, but at least I can provide you all with something fun to do while you are there…

You can get the S4PM badges from the Relay Health (#3618) or MedSeek (#1345) booths, or by attending the S4PM Wednesday lunch meetup or one of the following epatient events at HIMSS.

Wednesday – @ReginaHolliday: #Thewalkinggallery meets @ ECollab Forum Wed 2-22 Venetian Sands, Bellini 2102, Level Main/Level 2 6-7:30 pm

Thursday – eCollaboration Forum http://www.himssconference.org/ecollaboration/default.aspx with a variety of speakers, among them: Brian Ahier and e-patient Dave

Thursday – Engaging Consumers in their Digital Healthcare http://www.himssconference.org/Future/default.ASPX with Regina Holliday as keynote speaker

Tweet the picture of yourself wearing the badge for bonus credibility, but all I need is the pictures URL as proof.

To play, all you have to do is complete the form below!

Have a good time!!

Health Foo Camp

I am happy to announce that I have been invited to the first ever Health Foo Camp. There is not even a web-page for this yet, but it has been previously announced on the RWJF blog

FOO stands for Friends of O’Reilly. It is an invitation event that puts some of the top geeks and thinkers in the same room. This is the first health-focused FOO camp.

This is a pretty big deal for me. The moment I first heard of Foo Camp, I realized that going to one was on my bucket list.

This was similar to the first time I realized that Regina Holliday sometimes auctions off her art. I realized that being wealthy enough to win an auction of one of her art work was my new definition of being rich… I also secretly covet one of her custom jackets.

Anyways, when something like this happens I begin to realize that maybe I am making the difference I want to with my life. It looks like people are finally taking this whole Open Source Health Software thing as seriously as I do. Its a pretty awesome feeling and after sharing a celebratory dinner with my wife, and soaking up the good news for a few days, I thought my readers might like to share in my sense of satisfaction. At least I think I have readers….

-FT

Hacking data: showing patterns in kids health

Here is my submission for the Local Children’s Data Health 2.0 developer challenge. The challenge was to make data available through kidsdata.org come alive.

Generally, the red circles correspond to the percentage of child allergy suffers who had -seen- a doctor, but had no specific plan to address their condition. The red tags, are healthcare providers from the NPI database that are listed as experts in kids allergies… the top of the field for asthma treatment. We are using these “super experts” as a proxy for the availability of specialist care for allergies generally. Notice the under-served areas… The specialist are clustering in the high-population areas. Hopefully this map will inspire an expert to move to Eureka, or Santa Maria..

Here was my process for this for my hack:

  • I would only use Open Source software or Open APIs. The idea here is to show just how powerful FOSS tools can be in health data analysis.
  • I have just created the best API to the National Provider Identifier database at docnpi.com, so I have this rich datasource that previously has not been available as an API.
  • I wanted to target something from kidsdata.org that was directly related to the availability of healthcare, something that you can measure geographically using the docnpi.com API.
  • I chose Asthma, because this is something that clearly responds to treatment.
  • I wanted to document my process to show how easy this kind of analysis is with the right tools.

Ok here’s what I did…

  1. First, I browsed kidsdata.org for asthma information. That leads you straight to this analysis of asthma hospitalizations for young children over the last few years.
  2. Then I started digging for source data. It looks like the California Health Interview Survey was a substantial source of the data.
  3. They offer Public Use Files of the original survey data. I signed in, and the terms of use for the data were reasonable, and not contrary to my purposes or Open Source. So I signed up and went to download the data.
  4. Sadly, the data was only available in three proprietary data formats, Strata, SPSS and SAS. This was obviously designed for academics that think using proprietary software is ethical and normal. Thankfully there are other options. The R project is where I usually turn first for stats help, but I actually found that there was an Open Source SPSS alternative called PSPP. Using PSPP I was able to open the SPSS data file. Victory for Open Source! It would be nice if organizations like CHIS would release in simple XML or CSV, which is much friendlier to hackers and people who believe in software freedom.
  5. My feeling of elation was short lived. The data had no geo-coded information. Which makes sense, that would make re-identification much easier. There had to be another way to get geo-coded data.
  6. And there was. AskCHIS is a powerful data reporting tool that allowed for xls data download. Again, I am amazed that CHIS would chose to run with a proprietary format without an open alternative. They used alot of advanced xls layout options that meant that an export to CSV would never work. An API would be even better, but at least CSV would allow me to actually parse a file instead of cutting and pasting which is what I ended up doing.
  7. But I had access to lots of data. I could see several different measures of asthma that I could have used in my mashup. This included lots of stuff like missed school days, emergency room visits, diagnosis of asthma, symptoms in the last twelve months… etc etc. If CHIS had given this data up using an API, I would have been able to merge the various asthma measures into an overall asthma status score… but it would have take a week of cutting and pasting to do that manually.
  8. So I had to choose one data point and run with it. I chose “Health professional ever provided asthma management plan“. This was asked to parents whose kids already had a doctor who was “treating” the asthma. I thought this was an interesting question because it seemed to correlate strongly with doctor-availability, something that I had good geo-coded data on.
  9. Now what provider data should I compare it to? Using docnpi.com I can easily grab a list of all/most of the doctors in California who specialize in treating allergies in children I decided to use that as a proxy for “available allergy specialists”. Of course, I had a serious advantage here, because I had already done the work of changing the NPI database into something I could access using an API (that is the idea behind docnpi.com). This easily saved me 30 hours of work on this project alone.
  10. So now I have the data I want… but what now? I had addresses for the doctors and clinics from the NPI database, but the asthma data was coded by county. No problem, I just needed to geocode the counties into longitude and latitude. If I had a rich data source from CHIS, it would have been worth writing a script to do this, but since I was using cut-and-paste data, with about 75 rows, it was much simpler to just manually geocode everything. Which is what I did. More cut-and-paste.
  11. But now I have geo-coded data for both data sources.
  12. I needed a method to graphically display geo-coded scoring. This is pretty easy to do using proprietary GIS tools, even costless tools like Google Earth. But I wanted to keep things simple and Open Source at the same time. Enter the EInsert extension to Google Maps API v2. This allowed me to overlay png circle graphics on a Google Map, and size them in accordance with their percentage (bigger is worse, it means more of the kids did not have asthma plans).
  13. Then something tickled my brain. Using circles to represent scaled data is problematic. There is solid research indicating that humans have trouble estimating the area of circles in relation to each other… So I used the ratio suggested by James Flannery to counter this effect. Now the circles are sized in a way that indicates their relative meanings in a somewhat more appropriate way.
  14. Now I had a Google Map that displayed data regarding the frequency of plans as meaningfully sized circles over the California state. This data shows some predictable effects. First, the worst areas are either very urban or very rural. Exactly the places that have trouble attracting medical talent. That means that on this map, Ureka and Los Angeles urban counties have similarly sized circles.
  15. Now all I needed to do was overlay the doctor data on this map. This turned out to be pretty simple. I already have a link to provide a Google Map display of any small search on docnpi.com. For instance, here is the link for the map for the search on allergists in California. All I needed to do was copy the html and javascript for the doctor map and integrate the map with the Asthma data map I had already made.
  16. So far, that maps looks pretty good. However, there is no easy way to tell which county, specifically, a given circle represents. I decided that the simplest way to address this was to dynamically rewrite the png using the gd library of php. I would pass the php script a label, and it would generate a circle with a label on it. This would allow me to label all of the circles on the map. As usual, stackoverflow provided a quick and dirty solution. (update 4-20) I realized that the label should show both the name of the county, and the percentage without a plan… now it does.

Take a look at the final result.

Notice that the shapes scale automatically as you zoom in. Try zooming in to Los Angeles or San Francisco to compare the compacted counties more closely. Also note that you can actually get the name of particular doctor that specializes in the treatment of asthma directly from the map. If you click the link you can get all of the contact information from docnpi.com

Which brings us to the point of this exercise.  A better view of the data can prompt change.

If you are a parent of a child with Asthma in one of the “big circles” you need to know that the long term treatment of Asthma requires a plan. If you do not have a plan, the reason might be that there are not enough doctors around you to provide the help you need. This map can put you in touch with the nearest expert.

If you are a doctor, who specializes in childhood allergy treatment, this is an opportunity map for you. Eureka is much smaller than LA or San Francisco, but you would have a near monopoly on a population that needs help with asthma. These people do not have the same access to specialized care and that might be a business opportunity for you. Moreover, a doctor who chose to focus on the urban areas in the larger cities might also be able to gain patients and profit. The data here shows that while there are lots of experts -around- the densely urban areas they are not meeting the demand for care. If a doctor could find a way to make money on a Medicare/Medicaid population in these urban areas, this might also be an opportunity.

Seeing the health data in a new way can provoke change. I hope you think my application is cool and sexy, but frankly I do not give a damn about that. I want to make a difference, not toys.

People remember Florence Nightengale as the mother of modern nursing. But she once made a diagram that changed the way people thought about war. It was that diagram that gave her much of the political clout she needed to create the field of professional nursing that we know today.

I have made the NPI data more liquid with docnpi.com. Organizations like CHIS need to a much better job of making their data accessible. If I had been able to access the data from AskCHIS in a normalized and open format using an API, I would have been able to make mapping system that would allow the overlay of -any- type of doctor with -any- health data measure that they survey.

So that leaves me with a call to action for three groups: Patients -> find better care near you. Doctors -> go where the patients need you. Researchers -> expose your data in open formats using APIs and open file formats.

Of course, I publish my source code under an Open Source license. Enjoy.

-FT

A patient by any other name

Recently two communities have been discussing a pretty basic question. What should we call the artist formerly known as “patient”?

The two communities are the e-patient community and the “patients” in the patient safety movement, specifically those that met at the last IHI meeting.

But why would we want to call patients anything other than “patients”?
The word patient has some negative connotations. Indeed, the Websters dictionary entry has exactly two definitions of the word patient as a noun.

1 a : an individual awaiting or under medical care and treatment
b : the recipient of any of various personal services
2 : one that is acted upon

It does indeed seem that a historical definition of the word directly implies passiveness. The second definition is particularly problematic, but even the notion that a patient is one that “waits” for care in the first definition is contrary to the participatory and proactive ideals of both of these groups.

But we should not pretend. “Patients” are in fact very often passive.
If we define the leaders of these communities as “fully engaged patients” then what is typical in “patients” is not merely “not fully engaged” but “not at all engaged”.  Paternalism in medicine is not just a problem in the attitudes of doctors, but for many “patients” as well. In fact the word “patient”, with its passive context,  is probably the right meaning for most people.

So both of these communities have been talking about two problems here at once, and conflating them frequently.

First we have a problem that patients are frequently passive and even when they are engaged they are not effective because they are not typically well-equipped. This problem can be summarized as “Lack of patient engagement”.

But then we also have the problem of how to describe a person who is successfully taking a proactive, engaged and effective role in their own healthcare.

I think it is a mistake to conflate these problems. If we are going to be asking doctors to change their behaviors and/or perspectives we need to be clear whether we are asking them to change the way they relate to a typical patient, even when that patient may be entirely passive, or whether we are asking doctors to recognize that “patients” in our communities are moving beyond the passive role and expect to be treated differently. When we discuss whether we should keep the old name, “patients” or create a new name, we need to be clear if we are talking about something new for everyone, or just those that embrace a new ethos and responsibility. Are we debating a name for “everyone” or a name for “us”?

Given that distinction, we can more clearly discuss the various terms that we are suggesting. Here are some of the alternative words that have come up in our groups:

The term consumers emphasizes that as “patients” we are having an economic transaction. All patients, both passive and proactive are obviously consumers. The notion here is that by referring to market forces and discussing things in business terms, that we might bring competition into play. The fundamental problem with this notion of bringing a market to bear in healthcare is that fair markets only exist when there is information parity. Consumer reports, for instance, serves to provide information parity in the automobile market, as does Kelly Blue Book. Both the relative performance, and the current average price of any automobile are generally known both the buyer and seller of automobiles. But when we talk about patients as consumers, they have dramatically reduced information regarding both the price and the quality of the services that a doctor provides. Do not get me wrong, I think these problems are solvable and as a result the “consumerism” movement within healthcare has value, but it would be silly to simply pretend that by calling a patient a consumer we can ensure that they are actually playing this role in economic terms. So the notion that patients -are- consumers is pretty weak, but the notion that they -should be- consumers is a great idea. The consumers union has important healthcare efforts that should be supported and embraced.

The second term is client. The benefit of this term is that it emphasizes that the person under care is providing payment for care and should be treated with respect as a result. The term client has very different meanings in different professional relationships. We certainly would not equate the relationships  lawyers, prostitutes, hair dressers and mental professional with their “clients”. The word is quite flexible. This can be both a strength and a weakness. Moreover, it is often not strictly true. At least one definition of client is “someone who pays for goods or services” and often the “patient” is not actually the one paying for care. Sometimes parents or children pay, sometimes society or the government pays and at least usually, a third party is actually “payed” by the patient for care, and that third party then pays the clinician. One could argue that many of the woes in our healthcare system are the result from treating insurance companies as the clients to the detriment of both the patients and the doctors.

The term patient 2.0, like health 2.0 refers to the iterative improvement that we have seen in technology. Health 2.0 itself was a controversial term when it was created, both described as being both the application of web 2.0 technologies to healthcare (the Holt definition) and the fundamental rethinking of healthcare itself (the Shreeve definition). Since those debates, both definitions have held up well. If we accept a “Shreeve” style definition of Patient 2.0, then we label our efforts as a natural successor and a fundamental improvement at the same time. Unfortunately many will hear a “Holt” style definition and assume that Patient 2.0 means patients who like to use software, which misses the point entirely.

This problem is shared with the term e-patient. To the initiated the “e” in e-patient stands for “empowered” or perhaps several “e” words like “empowered”/”engaged”/”enabled”/”educated”. But reporters and other bloggers constantly refer to the parallel of “e-mail”, assuming that the “e” means “electronic”. Again the notion that an e-patient is a patient who e-mails misses the point entirely. However, e-patient does have very strong brand, mostly due to its very popular blog and the wonderful white-paper. It is one of the most recognized terms in our larger movement. Empatient has been suggested as a dis-ambiguous improvement on e-patient, one that is not subject to confusion. It also is a play on words with impatient, (which I find delightful, because I am a word-geek).

Patient expert has been suggested as an acknowledgment that patient’s can often be very informed about their disease and conditions. But this term is also controversial; if a patient truly had the required health expertise, then there would often be no need for a doctor. Doctors, as experts, might resent this term, because it makes an implication that is clearly false… that both the doctor and the patients are experts in healthcare. Of course one could argue that the right term should be expert patient. Rather than suggesting that a patient “has healthcare expertise” which might be insulting, this arrangement implies that a person has become an expert, at being a patient. Hopefully this would not be as insulting to doctors and probably be a more accurate description. Of course the problem here is that people might be told “expert patient” and presume that it means “patient expert”.In this same vein a notion of a licensed patient, has been proposed, but it unclear what specifically licensed might mean.

Patient advocate is a term that is well-suited towards those with deep experience being patients, who are engaged with helping others who are being overwhelmed by just becoming patients. This has some overlap with the ‘advocate’ relationship that a lawyer might have.  Patient activist is a good term for those who attempt to speak for larger groups of patients at once.  The problem with these terms is that it very accurately describes certain individuals in our communities, but fails to capture the ethos that we would hope to instill in everyone who receives healthcare.

In the quantified self movement, which overlaps with the n=1 movement, they often refer to themselves as #quants. This movement is focused on collecting data on oneself in order to achieve a deeper understanding of ones own health and wellness.

A clear trend with these terms is that they often represent terms that are 100% appropriate for a specific subset of our overall movement. We need to have people who specifically attempt to be engaged and proactive patients using software, and patients 2.0 is a great term for that. When we are trying to get healthcare to respond to consumer forces, calling patients consumers is appropriate. Sometimes the “e” in e-patient might really refer to a person who want to be fully engaged… by e-mailing his or her doctor. In a shameless plug I argue that the term cautious patient, coined by Dr. Oliver and the subject of my work at the Cautious Patient Foundation is the right term to use when you are discussing patients who are A. fully engaged  B. educated about patient safety and therefore C. able to take steps, as patients, to avoid medical errors.

But all of these alternatives should be compared with efforts to rehabilitate the original term “patient”.

Over time, the meanings of words in any language changes. Perhaps it is simply time to redefine this word. In many cases, this work has already begun. One of my personal favorites is e-patient dave’s catchphrase “Patient is not a third person word” (not sure if he coined this, or merely popularized it… either way, when I say it, I am quoting Dave.)

Perhaps we just need to re-embody the word patient with a new meaning, one that is more compatible with our movement. One way to do that might be to temporarily use a term like true patient, pure patient or real patient ( perhaps a way to take advantage of the fact that this can be an adverb/adjective as well?)

I want to be clear that I have no specific preferences on what term(s) are most appropriate.  I would not have added something to this post if I thought it was ridiculous, and I am trying to summarize and evaluate positions that I have heard others take on these issues. If I have missed something or been to critical to an idea that you favor, leave me a comment and I will update this post if you are convincing.

Regards,

-FT

Update 12/21/2010:

e-patient dave had the following to say in response:

Hey Fred – when I was in college in the Nixon years, my more radical friends often debated the power of language especially during a revolution. I’m no radical compared to them, nor to some of the more intense people I know in the patient movement, but I agree there’s something to it. Revolutions (race, gender, whatever) involve unshackling, and a lot of shackling lives in language.

I’ve always thought there are two changes in a social revolution: the underlying reality and the language we use to discuss life. There’s a period of intense discomfort during which the reality is shifting and the language no longer fits – just like a bad shoe. People start to see themselves (and others) in the new reality, and they say “That old language isn’t me, no sir!” Others say “It *is* me – I’m the NEW [whatever].” Some take over the old words, even the pejoratives, and take ownership in the new world, as some blacks have done with “nigger.” They assert that that signifies real power – “The Man no longer gets to say. We get to say. The language of your dominance no longer applies.”

I don’t mean to sound like an expert on this because I was no expert, just an observer. My point here is that we in the movement ought to be thinking about where we sit, collectively, on the timeline of transition. Many of us are awakening to our power, just as blacks and women did during their revolutions. Perhaps we should track both issues independently: the reality, and what we call – AND what others hear when they hear our words. Because a social revolution’s not complete until the old meaning’s obsolete.

The only point I would disagree with about this is the notion that Dave is “just an observer” on this issue. Some of the things I have heard him say, esp the ‘third person’ thing, have clearly raised my own awareness about how I discuss patients.

Kaiser Ontology Interview

To the novice, the term “interoperability” means that two systems can talk.

To the expert, it means that they can understand each other. To much of our current data interchange is “meaning poor”.

To get past that problem, we need to do lots of work with ontologies, which, loosely put, are knowledge dictionaries. Most clinicians in the US have no training in ontologies and their real-world experience is limited to billing ontologies like CPT and ICD. As a result, the value of proper coding is largely lost on the average clinician in the US. ( I wonder how this issue is understood by common clinicians outside the US…)

Those of us who obsess with the future of Health IT recognize that we need to find ways to make Ontologies more productive.

At this year’s health 2.0 conference, I caught up with Dr. John Mattison of Kaiser Permanente to discuss a tremendously important contribution that they are making to the Open Source Health IT community. I have already blogged about this significant ontology development from Kaiser. So I was really pleased to be able to get these kinds of details from the horses mouth. These details include that the license will be the Apache 2.0 license.

Part 1

Part 2

Speaking at OSCON

Hi,

I am honored to announce that I will be speaking at OSCON 2010 on the healthcare track.

This talk is my “Health of the Source” talk. My intention in this talk is to cover both the “spirit” of Open Source in Healthcare as well as the “letter” of what is specifically going on right now. If you are unfamiliar with Open Source in Healthcare, and you can only attend one single talk on the subject, you should attend my talk. You will learn the most about the most different things. If you want to attend more than one talk, you should probably read Andy Orams summary of the OSCON healthcare talks.

As always, I am asking my readers and followers to tweet me about things that are happening in Open Source Healthcare that I should mention. If you could not get a spot at the conference but you are doing something wonderful, let me know and I will try and mention your work to the right people.

-FT