Less is More
–Mies van der Rohe

In high school English class, many of my generation were forced to study a book about writing known as “Strunk and White.” Compared to many other books we were forced to read, it had many advantages. It was short. It was to-the-point. It was full of pithy sayings, the most pithy: omit needless words.

In Cognitive Friction, we extended the idea to graphical computer user interfaces as “omit needless pixels.” In Performance, Data Pixels, Location, and Preattentive Attributes we looked at Nielsen and Tahir’s analysis of the percentage of a home page’s area devoted to different purposes; in this way, we could determine which were valid data pixels, which were not, and the ratio of data to non-data pixels.

In Lessons from Tufte, we read from The Visual Display of Quantitative Information

The larger the share of a graphic’s ink devoted to data, the better (other relevant matters being equal):

Maximize the data-ink ratio, within reason.

Every bit of ink on a graphic requires a reason. And nearly always that reason should be that the ink presents new information. …

The other side of increasing the proportion of data-ink is an erasing principle:

Erase non-data-ink, within reason.

Ink that fails to depict statistical information does not have much interest to the viewer of a graphic; in fact, sometimes such nondata-ink clutters up the data…

In Menu we discussed “analysis paralysis”: the more choices on a computer screen, the harder it is to use, and the more likely a user will make a mistake; and the importance of paring down the number of choices. We may consider the area of a computer screen devoted to choices that users never or rarely use to be made up of non-data-pixels. What is worse, these supernumerary choices distract from the data pixels, and since they are worse than other non-data pixels (they distract more), we may term them anti-data-pixels.

Want to make a computer screen or web page better? First, omit anti-data pixels. In a future post, I will discuss a heuristic (fancy name for a simple rule) for determining how to do this. Next, omit non-data pixels. What is left should be pure, clean, relevant data.

Death to anti-data pixels!

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Dr. Vivek Reddy, a neurologist at the University of Pittsburgh Medical Center, also works on its digital records effort.

In a February 19 article in the New York Times,  Julie Creswell calls the healthcare IT portion of the 2009 stimulus bill (American Recovery and Reinvestment Act of 2009)  ‘a $19 billion government “giveaway”’ resulting from the lobbying of the big HIS vendors. One of the quotes in her article points out the usability limitations of these big HIS systems: ‘“On a really good day, you might be able to call the system mediocre, but most of the time, it’s lousy,” said Michael Callaham, the chairman of the department of emergency medicine at the University of California, San Francisco Medical Center.’

Skeuomorphism has been around for a long time.

Architects including Frank Lloyd Wright have eschewed it. Alan Cooper, known as one of the founding fathers of user interaction design for computer systems, decried it in the first edition of his classic text, About Face: Essentials of User Interaction Design. And more recently (~October 2012), people have compared Apple products with the new anti-skeuomorphic Modern UI (in-speak for User Interface) of Windows 8, previously known as Metro, and accused Apple of poor design because of rampant excess skeuomorphism.

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Skeuomorphism in architecture (or car decoration) might be wood-grained vinyl. Skeuomorphism in software design might be a graphic of a spiral binding along the edge of a note-taking program’s screen.

Is it good? Is it bad?

Figure from Mullet+Sano: Designing Visual Interfaces

There are arguments in favor of skeuomorphism… it makes it easier for new users to figure out what software does. A good example is the shutter sound on cellphone cameras. There is a need for a sound that tells you that a picture has been taken. And using a sound that associates with old shutter cameras works. Even if you’ve never used a camera with an actual shutter, you may be familiar with the sound, as it’s a defacto standard for all sorts of digital still cameras. Donald Norman and Jakob Nielsen point out that if we flout standards – such as underlined blue text for links, or skeuomorphic Trompe-l’œil buttons to push with our mouse  – we do so at peril of making something unusable, something poorly learnable and poorly memorable.

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But, in a January 2013 article in Forbes magazine “Will Apple Dump Skeuomorphics In iOS?” Tim Worstall writes: this is only important in the transition from one way of doing things to a new one. You’ve only got to appeal to memories and habits of older technologies when people still have those memories and habits. Once you’ve a new generation of people, people who have grown up only ever having used the new technology, you simply don’t need those reminders of the old.

I’m not sure skeuomorphism is the best way to transition to a new paradigm. If the new paradigm has an excellent user interaction design, there is little or no need for skeuomorphism. It’s a crutch, and not a great one at that.

David Pogue writes, in the Scientific American article “Apple Shouldn’t Make Software Look Like Real Objects“: How many members of Generation Y have ever even used a Rolodex?

He points out how Windows 8 has gone the exact opposite direction: no skeuomorphs to be seen. Big, boxy tiles, which you can touch with a finger (well, unless you have a PC with a non-touch screen). No shading. No shadows. No raised buttons to provide affordance.

I have my own issues with Windows 8. Trashing the Start Button to force people  to the “Modern-previously-known-as-Metro” start screen is a blatant ploy to make people learn the new Modern interface.

Not that learning the new interface is bad, but having to switch from the desktop to the Modern/Metro interface sucks compared with the Start button as a way to quickly access programs from the desktop. As soon as I got a new PC with Win8, I bought Start8 from Stardock and installed it. Once I made that change, I found Win8 a just outstanding desktop operating system. There are many improvements from Win7. One of my favorites: I can mount .iso CD or DVD images just by double-clicking on them. This means I can make a .iso of a program’s CD for programs it will only install when it knows it’s running from a CD… and just run it from the .iso file. Slick. There are many other improvements under the hood.

But I like the Modern/Metro interface. Skeuomorphism may improve learnability the first time you use a program or device, but it gets in the way after that. Massive simplicity as in the Win8 Modern/Metro interface may take a few seconds more to learn, but it’s still quite easily learnable. And it’s easier to use than the iPad once you learn it.

Metaphor Run Amuck

Skeuomorphism is related to metaphor.

Something on a computer or cellphone screen that looks like a bookshelf is a metaphor. In Cooper’s original 1995 first edition of About Face, he gives a great example of metaphor run amuck, a product which will here remain nameless to avoid embarrassing the original coders. It’s shown to the right. As he says: Never bend your interface to fit a metaphor.

He points out that there is a difference between metaphor (and, by extension, skeuomorphism) and idiom. For example, the standard radiation symbol is an idiom. There is nothing skeuomorphic here: this is an abstract symbol. But it’s very rapidly learnable and memorable.

Cooper says: All idioms must be learned. Good idioms only need to be learned once.

Windows 8 Modern/Metro interface has good idioms. (It also has good direct manipulation (pressing and sliding tiles, for example. Again quoting Cooper’s About Face: A rich visual interaction is the key to successful direct manipulation. But direct manipulation is a story for another time.)

But my favorite About Face quote is apropos: No matter how cool your interface is, less of it would be better.

Medical software needs less skeuomorphism, such as Cerner FirsNet’s indecipherable icons (for example, the one that is supposed to look like a registration clerk and everyone refers to as “The Buddha”), and more good idioms.

Less is More
–Mies van der Rohe

Electronic Health Record Diagram

One of the supposed means to the great gains of electronic health records is that of the Personal Health Record (PHR). Big guns like Microsoft and Google dived into the PHR pool a few years ago (Microsoft HealthVault and Google Health), only to find that the water was quite shallow. Getting information into a Personal Health Record turns out to be so hard, that the effort wasn’t worth the results. Google gave up, at least for now, yet Microsoft persists. (There may be a lesson in there somewhere… ) But, as pointed out in an article on Slashdot, the Department of Health and Human Services has released newly revised rules for the Health Information Privacy and Accountability Act (HIPAA). These are effective on March 26, 2013. This is designed to, among other things, make PHRs more functional. As the press release says: “Patients can ask for a copy of their electronic medical record in an electronic form.”

The Office of Civil Rights (OCR) has an online document THE HIPAA PRIVACY RULE’S RIGHT OF ACCESS AND HEALTH INFORMATION TECHNOLOGY that discusses this in some detail (I guess the OCR has to speak in ALL CAPS). It points out that people may request their medical records by email or a web portal and this has to be accepted the same as a written, signed request. It also says

Electronic access may provide individuals with more timely access to more information in a more convenient manner. For example:

• Electronic copies of PHI may be downloaded to USB thumb-drives or copied to compact discs relatively quickly and may provide individuals with a more convenient means of transporting and maintaining the information.
• EHRs may enable covered entities to offer individuals an immediate and ongoing view into the covered entity’s designated record set(s), either through a personal health record (PHR) or otherwise, while limiting the time, expense, and labor that may be required otherwise in order to provide access to the individual.

The comments in the Federal Register say:

to the extent possible, we expect covered entities to provide the individual with a machine readable copy of the individual’s protected health information. The Department considers machine readable data to mean digital information stored in a standard format enabling the information to be processed and analyzed by computer. For example, this would include providing the individual with an electronic copy of the protected health information in the format of MS Word or Excel, text, HTML, or textbased PDF, among other formats.

This looks like an open invitation for healthcare organizations to get their acts together and support some form of a Personal Health Record, to save money on copying medical records, if nothing else.

Leslie S. Liu, Patrick C. Shih, Gillian R. Hayes of the Department of Informatics at UC Irvine published a paper online a year ago entitled Barriers to the Adoption and Use of Personal Health Record Systems. They point out the potential benefits of a PHR, but ask why only seven million Americans use one.  Yes, interoperability problems make it hard to import electronic records into a PHR, but they also analyze other barriers to wider acceptance of PHRs.

They used discount usability testing, which is described in two major books on the subject that they cite, but also on Jakob Nielsen’s website useit.com.

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Unsurprisingly, given the abysmal state of usability in medical applications in general, usability of these products was poor, which the study implicates as a major factor preventing the adoption of the PHR. The paper even uses the abbreviation “HE” for Heuristic Evaluation, which simply means that when you do usability testing, you follow some rules (duh). My advice is to use well-known heuristics, and a great example of how to do this is in Nielsen and Tahir’s book Homepage Usability: 50 Websites Deconstructed … but keeping your eye out for problems that don’t fit into your heuristic. Remember, usability heuristics have not been around for a long time, so it’s entirely possible you can find a new problem and get a heuristic named after you.

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Full disclosure: my Personal Health Record consists of (1) a folder of scanned PDFs, and (2) some of the most important information copied into Outlook memos that I sync with my phone. Not secure, but I’ve really got nothing I need to keep secure, and this way it’s easily accessible. I am waiting for a good PHR to show up so I can use it.

It’s too bad that I have to keep blogging about how poor usability of medical software is making healthcare more expensive and less efficient. I look forward to, someday, posting a gushing review of how good a particular piece of medical software is. But then, I’ve been looking forward to that for a long, long time.

In the January 2013 HealthAffairs, Arthur L. Kellermann and Spencer S. Jones of the RAND Corporation look back  at the projections of a 2005 RAND study of healthcare IT. Why, in defiance of that study’s projections, are our medical computer systems not saving us $81 billion a year? They list reasons: slow adoption, lack of interoperability, and – you guessed it – poor usability. So, just maybe, if you get vendor CEOs and hospital CIOs to spend a few hours browsing the essays on this website, you can save the country billions of dollars. (Not to mention saving hospitals’ money and making more money for vendors.) Who’d have figured?

The Cost Disease is both the name of a book, and the economic theory espoused by this book.

The theory is relatively simple at its base. There are two segments to our modern economy, the progressive and the stagnant.

The progressive sector makes rapid improvement in efficiency. Examples include manufacture, particularly of items such as computers and cellphones.

The stagnant sector, including healthcare, education and live entertainment, due to dependence on human-human interaction, does not improve its efficiency rapidly.

Thus, the fraction of our GNP (and your paycheck) spent on the stagnant sector will increase. Continously.

Note that I said the fraction.

This may seem depressing. But the authors point out that, in real terms, our society, globally, is becoming richer. Therefore, despite the increasing fraction we will spend on the stagnant sector, we will be able to afford it. We will be able to afford more and better healthcare, education, and live entertainment.

Nonetheless, we need to do what we can to make the stagnant sectors more progressive. They give examples in the book of how healthcare, in particular, can become more progressive.

It is apparent that there will be an excellent ROI in healthcare by maximizing the efficiency of our healthcare personnel. Some big projects like RHIOs will contribute to this, but at a massive cost. But think – how much of our healthcare personnel’s time is spent using – or cursing at – computers?  Given the sad state of usability of our medical software, we will get a lot better ROI by simply making simple changes to our software to make it more usable. The cost of these changes is small compared to a RHIO, but the incremental benefit is huge. Thus, this website.

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An article in the New York Times points up some of the shortcomings of the push for meaningful use of electronic medical records (EMR): it’s vulnerable to fraud. The Department of Health and Human Services is shocked, just shocked, that perhaps some physicians and hospitals may have not been entirely accurate in self-reporting how well they’ve converted to an EMR, just to get a few million dollars.

But the part of the article that got my attention was this quote from Lynne Thomas Gordon, the chief executive of the American Health Information Management Association, a trade group in Chicago:

We’ve gone from the horse and buggy to the Model T, and we don’t know the rules of the road. Now we’ve had a big car pileup.

The reason I love this aphorism is not because I am shocked at the poor HHS oversight of the meaningful use process. To that, I say “duh.”

But it encapsulates where I think we are in terms of usability of medical software. Even our best software and hardware – iPhones and Android phones, Google search, Google Maps, and the like – are still barely beyond the Model T phase. Our medical software, far behind these market leaders, doesn’t even make it to the Model T level. Maybe its to the “pileup of Model Ts” phase.

We don’t need Model Ts, we need something like the Tesla Roadster.

Faced with a long dinner menu, it’s hard to decide what to order. (Even with a medium-sized menu, my wife always says “You go ahead and order, I haven’t decided yet.” But that’s extreme.)

It’s not just an urban legend. There are scientific studies that demonstrate it.

The study When Choice is Demotivating by Sheena Ivengar of Columbia University showed this:

In a grocery store, set up a jam-tasting station.

First, put out four different jams, and let people taste, and if they wish, buy.

Four out of ten people who stop by will taste some jam. Of those people who stopped to taste, three out of ten will buy some jam.

Next, put out twenty-four jams.

Six out of ten people will stop to taste. But of those who taste, less than one in ten (3%) will buy.

Why?

Cognitive friction.

The more menu choices, the harder it is to decide.

This problem has been known for millennia. Aesop relates the traditional tale of the fox and the cat. The idea is ensconced in the pop psychology literature as analysis paralysis. You can even buy a book about it.

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In Cerner FirstNet, I am confronted with a similar plethora of choices. For instance, to get to most of the information in Cerner from FirstNet, I need to click on a menu item called Chart. (There are other ways to get to this information, but this seems the simplest.)

However, the menu I am confronted with is as follows:

ED Summary
Allergies
Orders
Med Grid
EMAR
MAR Sum
Med Review
Flowsheet
Med Profile
VS
IView/IQ
Lab
Micro
Reports
Rad
PowerNote 2G
Impression and Plan
Clin Notes
Caredex
Assess
Nurse Notes
Form Text
Forms
Problems and Diagnoses
Pt. Info
Immunizations
Communication View
36hr
Newborn view
Newborn Genview (new)
Labor _Delivery view
Health Maintenance
Clinical Calculator
Ad Hoc Charting
Depart Process
Tear Off This View
Attach to Chart
Chart Accessed by >
Close Charts

That’s thirty-nine choices. I have highlighted the only options on this menu that I use. I have no idea what most of the rest are. Nor do I need to know what they are to do my job. (P.S.: that ED Summary? I don’t find it useful. Sorry.)

Oh, how much simpler it would be to find my needles if they weren’t in such a big haystack. And I would less-often click on the wrong menu item, if there were fewer items, and they were bigger.

Why can’t I have a shorter menu? All the things I don’t use could be grouped under a single “Rarely-Used” menu item!

Wait, the developer says. People keep asking for all these menu items so we keep adding them.

But I’m not “people” or even “users.” I am an emergency physician. And in my role, I – and all the other people|users – need menus that are customized for our specific roles.

Yes, it takes more work. You have to figure out which menu items I – and my 80 partners – use, and which we don’t. So? We’re worth it. And it makes a much, much better product.

I hope someone at Cerner reads this.

But now that CMS has said

“Our ED physicians “Assign” themselves to patients using the tracking board function of EHR. Does documentation of the date/time “assigned” qualify as Provider Contact Date/Time? Otherwise, the earliest documentation of contact with the patient would typically be the first order or the first LIP progress note. Are those acceptable forms of documentation for these data elements?”

“No, this would not be sufficient documentation of provider contact. You would need to use documentation that supports the time of the first direct, personal exchange between an ambulatory patient and a physician or institutionally credentialed provider to initiate the medical screening examination.”

–Quality Insights of Pennsylvania

I predict three things:

(1) ED directors will try to persuade docs to only put their name on the patient at the instant they actually see the patient,

(2) this will be a miserable failure that fails to generate accurate data and causes much friction, and that

(3) passive tracking (using RFID smart badges that track when you enter a room) will suddenly be of great interest to many EDs. May be a good time to invest in these products.

In the Beginning: VoiceEM

Back in 1988, Ray Kurzweil came out with speech-recognition software, including something called VoiceEM. It was an emergency medicine physician charting application; there was also VoiceRAD for radiology. These were DOS programs that ran with that typical DOS 80 character x 25 character text screen. In addition to having a medical-specific vocabulary, VoiceEM had another advantage over the retail shrink-wrap Kurzweil Voice: you could access your voice profile (what the program learned about your particular voice, and the new words you had taught it) from any PC on the network. And, as it learned more about your voice, and as you taught it more words, these were saved back to the server, so you could access this updated “profile” from the network when you started up at the beginning of the next shift. VoiceEM alsom allowed electronic signature, saving your charts on the server and sending them through an interface to an electronic medical record (EMR) system.

VoiceEM employed a speech recognition engine developed by Kurzweil and his engineers. It was advanced for the time but crude by today’s standards. It only recognized

one

word

at

a

time.

The recognizer wasn’t all that good, but if you gave it a choice of just a few words, it could figure out pretty easily what you said. It was even quite good at discriminating between fifty or a hundred words.

To leverage this, Kurzweil added Applied Intelligence. (Applied Intelligence is Artificial Intelligence, only with more engineering and less hype.) They analyzed ED charts, and created templates for the most common presentations.

Let’s take, example, a “chest pain” template. (I’m grossly oversimplifying so it has only a passing acquaintance with the real template, which appears in the screenshot of VoiceEM’s successor Clinical Reporter, but bear with me, it’ll work for an illustration.)

The template looked like a regular ED note on screen, only with fill-ins (blanks) that could be filled in by voice. When you tabbed to a fill-in, a list of potential choices appropriate to that fill-in would appear along the right side of the screen.

The patient presents with a chief complaint of chest pain. The pain is [ ]. The chest pain started [ ] ago. The location is [ ]. Associated symptoms include [ ]. The pain [ ].

When a fillin was highlighted, you could use your voice to pick from choices, for example

“severe” or “moderate” or “mild”;
“pressure-like” and/or “sharp” and/or “burning” and/or “pleuritic”;
“one” or “two” or “three” etc., and “hours” or “days” or “weeks”;
“left” or “right” or “substernal”;
“shortness of breath” and/or “diaphoresis” and/or “palpitations”;
“radiates to right arm” or “radiates to left arm” or “does not radiate.”

(for some of the fillins, you could only pick one choice, and then the cursor would move to the next fillin; for others, you could pick multiple choices)

Given charting chest pain was pretty simple and standardized, you could just say the following, tabbing to the next “fill-in” (blank with an associated short list of possible answers):

“chest pain” TAB
“severe” TAB
“pressure-like” TAB
“two” “hours” TAB
“left-sided” TAB
“shortness of breath” “diaphoresis” “palpitations” TAB
“does not radiate” TAB

and the like. This then would then generate a chart that looks like this:

The patient presents with a chief complaint of chest pain. The pain is severe. The pain is pressure-like. The chest pain started two hours ago. The location is left-sided. Associated symptoms include shortness of breath, diaphoresis, palpitations. The pain does not radiate.

“Free-Text-Mode” and Continuous Speech Recognition

With Kurzweil VoiceEM, you could even go to “free-text-mode” and dictate

word

by

word.

This “free-text-mode” had the dual disadvantages that it was painfully slow, and, since the recognizer had to choose from a very much larger vocabulary than in the fillins, it was much more prone to misunderstanding you. But for some complex charts, you had to use it. Or type. I think we all typed faster than this original “free-text-mode” so that’s what we did. One of our docs used the Dvorak keyboard layout, and I installed a macro program to switch the keys for him; this way he could type a lot faster.

Even today, working as an ER doc requires typing proficiency. I think that all applicants for our group should have to take a typing proficiency test, and they have to do better than 35 words per minute to be considered. I type about 90 WPM. I credit my mother with this. When in high school, she made me take a typing class. I was outraged, until I realized the advantages of being the only male in the class.

Overall, VoiceEM worked pretty well for simple, straightforward charts. Even for those charts, it was slower than handwriting. But much more legible! I remember when one of my partners was handed one of his own handwritten charts for a QI (quality improvement) review: “What? You expect me to be able to read this?”

Continuous Speech

Later, Kurzweil started working on continuous-speech recognition. About the same time, a group of grad students at Carnegie-Mellon University were working on continuous-speech. Living close to CMU, I got to attend some seminars of the working group. The CMU project got spun off as an independent business, something called Dragon Dictate. Typical grad-student name, don’t you think? Later it became a commercial product.

Both the Kurzweil and Dragon continuous-speech recognition programs were built on a trigram model: each word is evaluated in the context of the word before and the word after. This improved recognition massively compared with Kurzweil’s original word-by-word recognizer. Having a vocabulary based on actual emergency medicine reports allowed fine-tuning of both the vocabulary as well as improving trigram recognition, as Clinical Reporter was preferentially listening for the most commonly-used emergency medicine phrases. There were problems with this model, however; the vocabulary was computer-created from analyzing many, many ED reports without much human oversight. This resulted in a “dirty” vocabulary, with some occasional proper names and misspellings creeping in.

Kurzweil’s technology and business got bought out by a Belgian company called Lernout & Hauspie. So there was an upgrade of VoiceEM called Clinical Reporter. It still had all the templates – in fact, even better templates, and more of them, and they were customizable. It switched from being a DOS program to a Windows program, but otherwise was much the same.

Two words = $$$$$

Customizable templates were important to us. For example, we realized that we were very poor at billing for critical care, which pays better than “regular” care. ER docs do all sorts of things that are billible as critical care (like taking care of bad asthma patients) that are easy for us. It’s billable as critical care, but the care is so routine for us that we forget to chart the language about critical care.

At the bottom of our standard ED provider charting template, we added a reminder:

[Critical Care?<>]

This was a non-printing prompt. If you ignored it, it would disappear when you signed and closed the report. But if you highlighted it and said “Critical Care” then this would appear:

CRITICAL CARE: The aggregate critical care time was [<30>] minutes of direct attention while the patient was in the ED, under my care, addressing the stabilization of multiple systems. My care included the history and physical examination, patient management, patient reassessment, interpretation of diagnostic tests, coordination of care, discussions with family, and decisions regarding patient treatment and disposition.

The month after we added this to our standard template, our critical care billing went up by 13%. Pretty impressive change for adding two words and a question mark! This illustrates one powerful feature of templated charting systems: reminders. (There are disadvantages of templated systems, too; we will review them in a subsequent post.)

Many of my partners complained about the slowness of charting with Clinical Reporter, but the complaints were quite muted (for a few months, at least) after our billing went up so sharply. You could also add in reminders about things like aspirin and nitrates and beta blockers for chest pain/myocardial infarction, which helps with charting compliance. Also, occasionally, with improved patient care as well; you’re charting and suddenly realize you’ve forgotten something and ask the nurse “would you put half an inch of nitropaste on the patient?”

About the same time (late 1990s), several competitors to Kurzweil appeared, and we demo’d a few of them. Many of them had innovative features.  We were looking at them as a potential replacement for Clinical Reporter, because:

Of Mergers and Acquisitions and Criminals

In 2000, Lernout & Hauspie went on a shopping spree. They bought Kurzweil. They bought Dictaphone (who had just bought Articulate Systems and their continuous speech recognition, one of those competitors we were looking at). They bought Dragon, with their successful retail speech recognition product. L&H brought out a highly-effective continuous-speech recognition product, VoiceExpress.  I used this at home; it wasn’t bad. Their stock soared. Any competition (that they hadn’t already bought) withered on the vine.

But the next year, it all fell apart. The principals were sentenced to jail over fictitious sales figures from Korea. The stock tanked. The company went bankrupt. The EDs using Clinical Reporter all followed the news with a kind of horrid fascination.

Nuance Takes Over

Scansoft, the makers of the leading Optical Character Recognition (OCR) program, Omnipage, acquired Lernout & Hauspie’s speech-recognition technologies, and changed their name to Nuance (what a bad name) along the way. They continued to market both retail and medical versions of Dragon. The medical version of Dragon was basically the standard retail package but with a medical vocabulary added and the price multiplied by a factor of 10. They even offered specialty-specific vocabularies, including emergency medicine. However, the Dragon product, unlike VoiceEM and Clinical Reporter, wouldn’t save your voice profiles to the server and allow you to load it from different PCs, nor would it send reports through an interface to your EMR system. (Years later, Nuance finally did start offering a medical version of Dragon with some network management capabilities.)

Nuance killed Clinical Reporter. They abandoned all the Applied Intelligence (templates) that Kurzweil and then the Clinical Reporter team had developed.

Too bad. Many of those templates were quite finely tuned and had a lot of smarts in them. They also abandoned Kurzweil’s work on a real-time program to analyze any text chart and code it for billing, giving advice if the report was close to but not quite up to a coding level. I used a beta version and it worked quite well. The code for this was developed based on a NIST (National Institute for Standards and Technology) grant, so I suppose the code is still available somewhere in the public domain for any enterprising individual to take and develop further.

Nuance took technology acquired from Dictaphone and started marketing a program called PowerScribe.

This inherited nothing from Kurzweil or Clinical Reporter, it was a brand-new and totally different program. PowerScribe had a simple template system (much cruder than the Clinical Reporter templates), but  no predefined templates.  Later, they collected templates from existing users and started providing new users with a few basic templates, but nothing like what Clinical Reporter had. There was no way to tie a particular list of words to a fillin; each fillin was listening using the full vocabulary, and without a list of preferred words, and with the standard trigram model of continuous speech recognition, uttering a single word in a fillin results in frequent misrecognitions. However, Dictaphone, being part of Nuance, got to use the latest and best versions of the Dragon speech-recognition engine (recognizer). However, over the past few years, they’ve been slack in rolling out upgraded recognizers for Powerscribe and then its successor, Enterprise WorkStation (EWS).

I’d worked with one of the Kurzweil/L&H engineers testing different microphone designs, including custom designs with separate microphones on the back of the microphone, trying to get good recognition despite:

• one male nurse with a booming voice that could be heard throughout the ED even when he was speaking softly,
• trauma patients and trauma surgeons each trying to outshout the other,
• people with kidney stones loudly retching, and
• demented nursing home residents screaming “HelpMeHelpMeHelpMeHelpMe!”

We found one, a customized Philips Speechmike, that worked pretty well. We also traced some of the problems down to poor design of many sound cards, which introduced noise into the mike input.

Powerscribe had many disadvantages compared with Clinical Reporter, but one great advantage: the Dictaphone USB microphone. This microphone, combined with a good sound chip on the motherboard (almost all sound chips are good now, designs have improved) had truly superior noise rejection, and provided excellent recognition. We use this mike in the ED to this day.

As with VoiceEM and Clinical Reporter, Powerscribe saved voice profiles on the server. It also offered an interface to the registration system (so you could pick a patient from a list) and to the EMR system (so completed reports flowed seamlessly into the EMR).

However, Nuance abandoned Powerscribe for emergency medicine, though it’s still supported for radiology. Instead, they offered a program called Enterprise Workstation, or EWS. EWS is designed not just for the ED but for use throughout the hospital or clinic. As with its predecessors, it offers management of voice profiles of the server, and interfaces to registration and EMR. To the end-user (us) it looks, and acts, just about the same as Powerscribe.

Dictaphone Enterprise Workstation

EWS is a front end for all Nuance/Dictaphone speech-to-text. There are three primary modes for converting speech to text and correcting errors.

1. The speech may be self-corrected on the screen, which is what I’ve always done in the ED. Reports are then immediately available on the EMR, which is important for admitted patients and even those discharged from the ED who show up at an outside doctor’s office the next day, or return to the ED the next day. It also allows visible templates as reminders.
2. The speech may be created onscreen using templates, and then sent electronically to a correctionist who cleans up the dictated text. There are no “transcriptionists” any more; essentially all speech-to-text, whether you dictated into a microphone on a computer or into a telephone, is processed first by speech-recognition software.
3. Or, you may simply dictate a complete note without looking at the screen and rely on the correctionist to clean it up.

Options 2+3 entail more expense and delay. The shorter the delay, the higher the cost: transcription (correction) companies charge more for rapid turnaround.

In September 2010, Nuance introduced the Dragon Medical Enterprise Network Edition vSync (what a mouthful) which allows dictation directly into many common enterprise EMR systems, working over Citrix, as well as providing centralized updates and profile management. I have not seen this in action, and am not privy to much in the way of details, though there are rumors that a healthcare system where I work is investigating it as a replacement for EWS in the next year or two. As near as I can tell, this will offer profile management, but no chart management, as the underlying EMR provides that; it will also offer no templates, again depending on the underlying EMR for that. That means integration of templates with speech recognition is likely to be poor, unless the institution and the EMR vendor both work hard on this, with careful attention to user interaction design. Based on past experience, this seems unlikely. But I will keep hoping to be pleasantly surprised.

Quite a few vendors have “integrated” Dragon into their point-and-click EMR systems. But rather than a tight and user-focused integration, it usually has all the disadvantages of both point-and-click and of speech-recognition charting. It doesn’t leverage speech-recognition in an intelligent way, as pioneered by Ray Kurzweil in his original VoiceEM and subsequently Clinical Reporter.

Thus far, I have written only about the Kurzweil > L&H > Nuance/Dictaphone lineage of medical speech transcription. That’s because there is no real competition. IBM had something called ViaVoice, but sold it to Nuance in 2003. Philips used to have its own speech recognition engine but now their speech-recognition products use the Dragon engine. All those other products that we were looking at in the late 1990s? They’re long-gone.

Which is too bad, because Dictaphone could do with some competition. Competition makes product managers focus on the user experience and user interaction design improvements. They neglect these when there is little competition.

Why Speech Recognition is Inferior to Other Charting Methods

As with any charting system, there are disadvantages to speech-recognition. For some people, recognition is poor, though this tends to be with those for whom English is a second language. It’s not a matter of accents; the current Dragon engine compensates well for accents. The problem is with grammar. German-speakers seem to have the worst of it: if you reverse your sentence order from the standard English order (“She threw the ball”) to be like the German order (“She the ball threw.”) then the recognizer gets confused.

A bigger problem is proofreading. Professional correctionists are good at proofreading. Doctors, especially frequently-interrupted emergency physicians, are not nearly as good. And, the recognizer definitely has a dirty mind.

I remember one time that I was reviewing a note sent to me by one of our senior residents, who was a bit on the stoic and hard-bitten side; he’d worked as an big-city police officer before medical school. He had dictated a note on an obese woman who had a rash under her big, protuberant abdomen. He had dictated “The abdominal exam was notable for a large pannus.” Later, he came out of a room to see me in front of my PC, with three or four  residents looking over my shoulder, all of us laughing. He saw the misrecognition (I told you the recognizer has a dirty mind) and turned bright red. I think it’s the only time I saw him embarrassed during his residency.

I have seen many implementations where speech-recognition is grafted onto a point-and-click charting application. Some of these work, but none of them seem to me to work all that well. These seem to have many of the disadvantages of both point-and-click and speech recognition. We know that switching modes slows you down, both physically and mentally. There are opportunities here for entrepreneurs interested in smoothing this user interaction and making a successful blend of speech recognition and templates.

Why Speech Recognition is Superior to Other Charting Methods

Immediate Availability

Unlike with speaking into a telephone, where it takes hours or days for the chart to be available, speech-recognition/self-edit charts are available on the EMR system as soon as you close them. This is big. Think of:

• admitted patients,
• those returning quickly to the ED,
• those following up with their doctors the next day, and
• those calling back with a question right after you’ve left for the end of your shift.

Readability

The problem with most point-and-click templated charting is that it reads like point-and-click templated charting. You can tell. With DocuTAP charting, the support personnel in triage enter the chief complaint, past medical and social history, medications and allergies, and there is no need for me to do anything more than review this by clicking on it. Speeds things up quite a bit. But, it’s a template system. So I find, for example, that the chief complaint is

Patient complains of a Swelling.

With speech recognition, you can dictate a whole paragraph of HPI, or a whole paragraph of medical decision-making, easily. And if you’ve read many ED charts, you realize that these are the only parts that people really read. A good, succinct paragraph summarizing things makes a medical chart much better as a work product. The PCP, the admiting physician, or your partner who deals with the patient right after you leave, will appreciate such.

Yes, you need to use a little peer review and peer pressure to get people to really proofread their own charts, though with Version 11 and above of the Dragon engine, recognition is really quite good. And, yes, the vendor needs to do some user interface modification to promote proofreading. It’s hard to remember where you stopped proofreading when you’ve been interrupted, and that interruption was interrupted by something more urgent, and even that interruption was interrupted. If the vendor were to do something like highlighting all text we’ve dictated, and allow us to run a finger or mouse across the lines as we proofread, un-highlighting them, this might help.

Speed of “Clicking”

One particular fact I mentioned above – that speech recognition can easily distinguish between fifty or a hundred words – is a key advantage of speech recognition templated charting over point-and-click templated charting. That’s because point-and-click charting is limited by the number of words you can see on the screen. And you have to use your foveal vision to scan the screen to find the word you want. It’s slow and limited.

But with speech recognition, you probably already know all the likely words for the fill-in, which means that accessing one of those words is simply a matter of thinking of it and speaking it. This is much faster than having to visually scan a list of words and then use your hand-eye coordination to click on one of those words. And with speech recognition, the word list can be much longer than a list you can see on the screen.

This fact has been too long overlooked as a way to leverage speech-recognition.

If you could find a way to attach a list of words to a fillin of a template, to recognize that they are the most  likely words to recognize, you could improve recognition and usability greatly. Unfortunately, no current products do this: the template systems are quite crude, compared with what Ray Kurzweil pioneered.

Speed

I have found a very effective way to use Dictaphone EWS. I have a standard template – just a slight personal modification of the standard template we all use – shown here:

***************************************************************************
***************************************************************************

ATTENDING EMERGENCY MEDICINE NOTE:

Registration clerk chief complaint reviewed. [<Agree>]

Triage note reviewed. [<Agree>]

[<I performed a history and physical examination of the patient with the resident. I reviewed the resident's note and agree with the documented findings and plan of care (although I have not manually corrected all typographical/recognition errors) unless otherwise noted.

>]CHIEF COMPLAINT: [<>]

History of Present Illness: [<>]

REVIEW OF SYSTEMS: [<All systems listed below were reviewed and are negative unless otherwise noted in the report.
General
EYES
ENT
Cardiac
Respiratory
Gastrointestinal
Genitourinary
Musculoskeletal
Dermatologic
Neurological
Endocrine
Hematology/Lymph
Psychiatric
Allergic/Immunologic>]

PAST MEDICAL HISTORY: [<As above>]

MEDICATIONS: [<Reviewed and agree with Nursing Notes>]

ALLERGIES: [<Reviewed and agree with Nursing Notes>]

SOCIAL HISTORY: [<As above>]

PHYSICAL EXAM: Vital Signs: [<reviewed nurses' note>]

PATENT STATUS: [<alert, cooperative, no visible distress, not ill appearing, well-hydrated>] [<>]

[<>][<>][<>]

MEDICAL DECISION MAKING/DIFFERENTIAL DIAGNOSIS: [<Old records reviewed.>] [<>]

DIAGNOSIS: [<>]

DISPOSITION: [<Patient discharged in stable condition. Computer-generated discharge instructions provided.>]

Though the ideal for many is bedside charting, and I’ve done bedside charting with T-sheets, and have seen some hybrid systems that allow some part of the chart to be done via dictation at the bedside, this system is used at a sit-down PC. I’m still a fan of scribbling a few notes on a 6.5×5″ bit of card stock, folded in half, and stuck in my pocket. Even when we had what is arguably the best ED tracking system, Wellsoft, I still used the card in my pocket as a “peripheral brain.”

My usual charting strategy is to primarily dictate a long HPI, which includes a bit of social history, and pertinent positives from my review of systems (ROS). I can usually do this paragraph in one continuous utterance. It’s quick. Then, my template says “as above” for both social history and ROS, so I don’t usually need to modify them. I can then dictate a physical exam as follows, using the proword “Dictatphone” to tell the program that each of these is a “shortcut” (macro to programmers). Each of these is a standard “shortcut” that I have personalized to reflect my usual normal exams.

Dictaphone Normal Eyes
Dictaphone Normal Throat
Dictaphone Normal Neck
Dictaphone Normal Back
Dictaphone Normal Chest
Dictaphone Normal Lungs Heart Abdomen
Dictaphone Normal Skin
Dictaphone Normal Extremities
Dictaphone Limited Neurological

I can take a deep breath, and dictate this without stopping. It takes just a few seconds.

One problem with any templated charting system: it’s easy to chart things you really didn’t do. So I dictate a “normal” only for those things I actually examined. As these shortcuts (macros) are expanded, you see something like this on the screen:

THROAT: [<No injection. >] [<No exudate. >] [<No tonsillar hypertrophy. >] [<Airway widely patent. >] [<Uvula is midline. >] [<No tonsillar bulging, retropharyngeal soft tissues appear normal. >]

I then go back, use the mouse to highlight over anything that’s actually abnormal, and dictate the abnormal to replace it, thus:

ABDOMEN: Soft, nontender, normal bowel sounds, no guarding or rebound, no hepatosplenomegaly or mass, no bruit.

ABDOMEN: Soft, mild right upper quadrant tenderness, no Murphy sign, normal bowel sounds, no guarding or rebound, no hepatosplenomegaly or mass, no bruit.

Incremental Chart Completion

One of the great advantages of speech recognition charting, compared to talking into a telephone, is that you can break this process in half. You can start a chart, spend a few seconds dictating just the HPI, and save and close the chart. That way you’ve at least got the history down, and visible to you when you re-edit the chart. This is a great service to those of us who sometimes get back to our charts at the end of a shift and have a hard time remembering: “Was that the first old lady with abdominal pain? Or maybe the third?” Indeed, this ability to suspend charting in the middle is perhaps the most popular feature of speech-recognition charting with our residents. They rotate between our hospital, where we use speech recognition, and another hospital, where they dictate into a telephone. An informal survey reveals that 2/3-3/4 of the residents prefer the speech-recognition charting system, mostly for this reason.

* * *

Overall, in terms of efficiency, usability, functionality, and quality of work product, I know of nothing that works as well for ED provider charting as Enterprise WorkStation. It’s frustrating, though, as the company has done little to improve the product’s user interaction design, and is slow in upgrading the recognizer to the current shrink-wrap retail version. It could be so much better.

I look forward to reviewing the competition, and upgrades to Dictaphone’s charting software, when it appears.

***

Addendum, August 2012: I have hand a chance to work with Dragon’s new Medical Enterprise Medical Edition 10.1.  The Dragonbar loads my profile in just a few (less than five) seconds. This is dependent on network topology and speed, but it’s about 10 times faster than EWS loads my profile. The recognition, even with minimal training, is significantly better than the version 8 equivalent engine we were using with EWS. The templates, rather than using the [<EWS convention>] uses simple [square brackets.]This requires a bit of editing.

It’s easy to cut and paste templates (macros) from EWS to Dragon, but I’ve found I need to “launder” through Windows Notepad – cut from EWS, paste into Notepad, then copy from Notepad to Dragon – to strip out font attributes that I don’t want. (Pasting and copying from Notepad is easy if you simply hit control-V to paste, control-A to select all, then control-C to copy.)

We’ll be dictating directly into Cerner Millennium PowerChart 2G, and we’ve set up what is basically a blank template, cut way down on point-and-click to allow us the speed to dictate everything using a Dragon template (“Command”).  There are still a few issues to be dealt with, and I will post updates as I have them.