Interoperability and Data Entry - There are Solutions

This piece on the Syleum blog analyzing data and effective communication on "The Data Model that Nearly Killed me" makes for interesting reading

During the last week of January 2009 a faulty electronic, networked, health information data model nearly killed me despite its vaunted status as a component of two state-of-the-art, health information systems at two of the world’s most advanced medical facilities.

It does not come as a surprise given the complexity of medical information and the exponential growth in that data that keeping all this information correct, connected and up to date. In fact there was a veritable uproar created with the this posting by ePatinetDave - Imagine someone had been managing your data, and then you looked" (also this post). Not surprising to those of us who have looked at our own data for the last several years, myself included but quite shocking to most folks who for that period of time have been entrusting their data to others expecting it to contain accurate and appropriate content.

The sharing of information across systems just doesn't exist and I've talked about his before (here, here and here) and it's frustrating as hell to everyone involved. The patient ends up repeating information multiple times

The nurse who escorts me into urgent care asks me for my doctor’s name. I tell her my allergist’s name. The nurse argues that she wants to know the name of my primary care physician. Of course, that information is in my electronic medical record that she can readily access. The nurse next requests me to relate my medical history - which information is available in the electronic record. Next, an attending physician asks for my doctor’s name, no, not my allergist, my internist, and please relate my medical history. Never mind that (a) I provided this information to the nurse only moments ago, (b) I can barely breath, (c) I have horrible pain in my lungs, (d) I have a high fever, and (e) the requested data already is in my electronic health record.

In fact this is all in one office let alone sharing between offices....! This goes on with multiple interactions being documented next in the Allergists offices, then in the ambulance and then in the ER

I was in ER for 20 hours before being admitted to the intensive care unit (ICU) where I spent another 28 hours. Throughout my stay, I was hooked to network attached monitors that incessantly sounded alarms to which no one responded. I was asked 11 times to repeat my medical history, medication, and allergies to as many different medical professionals. I was seen by seven doctors each of whom asked me similar questions. Five doctors were never to be seen again. All doctors mumbled something about putting their findings into the hospital’s electronic records system - most did not according to ICU nurses. No one read my allergist’s detailed report about my condition and health history.

Then some heroic efforts to enter and capture this in electronic form

One heroic medical professional, the first nurse I met in ICU, worked to create a consistent record of my condition, allergies, and medications in the hospital’s electronic health information system. She spent over one hour searching for previously entered data, correcting errors, and moving or reentering data.

The review is a damning indictment of "the system" and it matters not which one it is

Medical personnel at urgent care and the hospital who interacted with me all used a version of the same electronic health information system (the “system”). It became clear that everyone was fighting that system. Indeed, they wasted between 40% and 60% of their time making the system do something useful for them. The system kept everyone from fulfilling their duties - the health information system did not help medical professionals perform their duties.

Fixing the underlying data model and the systems that we use to interact with these systems must be on the critical path. Spending millions of stimulus dollars on systems that "wasted between 40 - 60% of clinician time" is not going to fix the problem. Unfortunately fixing the data model is a challenging problem as this is a moving target in medicine. But fixing the capture of this information is not - there are time related challenges but existing infrastructure - dictation and transcription used in conjunction with technology: speech understanding, CDA and the healthstory interchange format and most importantly knowledge based workers: medical editors can help facilitate this process and at least relieve the burden of data entry from the time pressured clinical staff who want to (and used to) focus on the patient and their care rather than on the system and data capture.

Speech Recognition and MT Compensation

Speech Recognition and its relationship to compensation took on a life of its own over at the MTChat message board in this thread titled MT Exchange: MTs and "Speech Wreck". There were strong words and a concerted attack on Julie Weight....Yikes! The confusion that ensued linking and even blaming a technology with poor business practices and in particular poor compensation models that appeared to be unfair missed the point.

But it was the posting by Jay Vance of XY Files in an MT World who posted a thoughtful response to some of the criticism being leveled at Speech Recognition in this posting "Is Speech Rec Wrecked" that even featured actual data (thanks for sharing this!) from a survey he conducted in 2006 of Speech Recognition editors. In fact the data presented was helpful in assessing the actual benefits (back in 2006 - a long time ago in technology terms!) that even then showed:

a total of 51% of respondents - saw an average increase in productivity of between 25% and 50%. This confirms the anecdotal information I had collected via informal conversations with MTs working as SR editors in a variety of situations on a variety of SRT platforms.

I don't think it is a stretch to assume that this must have gotten better and productivity has improved beyond this and for a greater proportion of editors. The survey included some review of compensation changes (there was a reduction in rate but hard to determine if this was a real reduction or represented a reduction in rate that was offset by increased productivity) and a final question on satisfaction with the technology:

31% said they were somewhat satisfied
26% said they were very satisfied. These two categories totaled 57%

Not great but better than average. Overall

there is a wide spectrum in terms of the impact of SRT on productivity, compensation, and overall satisfaction among MTs working as SR editors. Consequently, I don't believe there is enough objective evidence to conclude that speech recognition has proven to be a widespread disaster for the MT working class. As with any scenario involving people, technology, and money, mileage is going to vary widely. In my experience, there are simply too many factors that can influence productivity, compensation, and overall satisfaction with speech recognition technology to draw hard and fast conclusions about the impact SRT is having on working MTs on the whole.

And this was in part the point that Julie Weight was trying to make on the MTChat board - there are many factors and there is no use trying to stall the implementation of Speech technology - that trains has left, like outsourcing.

Both Jay and Julie make the point that this technology is in use and although I probably am a stronger advocate and believer in the Speech technology I think the overriding point here is that this can and should be a good thing for the industry. Reducing the labor intensive element of producing a report has to be a good thing....freeing up the medical editor to add value to the clinical information as part of the process of review, editing and validation.

Recognizing this is old data this gives us a good reason to update this information and there is a survey currently ongoing from MTIA that can be taken here and I would encourage you to participate. This is an extensive survey and needs input but if you don't have the time I put a 4 question survey here that. If you can spare the time please take the full survey, but if not I'd welcome hearing your responses.

Reinvestment is not Just About Technology

There is lots of excitement or even frenzy over the wave of investment coming down the pipe towards healthcare technology but in this piece on the Huffington Post: Workforce Development Essential to Obama's Health Care IT Initiative Julian Alssid and Jonathan Leviss are quick to point out that there is an essential element that must be included - that of Human Capital. Healthcare is unique and transplanting technology from other industries is not a straightforward process

Hospitals are not banks, or insurance agencies, or hotels. Healthcare's unique workflows -- including many physicians and nurses sharing computers in a busy emergency room, the challenges of maintaining working hardware in an intensive care unit, and the vast realm of data accessed to care for a sick human being -- require novel technologies and processes that cannot be easily translated from other industries.

While I agree that some technologies have stalled many are being implemented and are delivering success today. Speech Recognition did suffer problems in noisy environments (that's why the early adopters of this technology are Radiologists who mostly work in quiet reading rooms). But newer Speech Understanding which is modelled on nature's success in speech understanding by not only using audio inputs but also getting information from the patent's previous history, demographics, prior reports and any other elements that will help in understanding what was said.

But that's not enough

Physicians, nurses, and other health care providers routinely learn new skills and adopt new technologies....What is missing, however, is a parallel training track for a sufficient workforce to develop, implement, manage, and support advanced information technologies in hospitals, doctors' offices, and other health care venues.

So providing the infrastructure is one thing but having the resources to support it is an essential part. This is especially true for the embattled medical transcription industry that has been fighting declining rates of pay as hospitals and healthcare providers continue to push for lower and lower line rates. All this is driven by the perception of the medical transcription is a cost, when in actual fact it is a value added service that frees up the clinical staff to focus on taking care of patients rather than the drudgery of data entry. There are lots of examples of systems trying to turn clinicians into data entry clerks and while there are instances where this methodology makes sense in many cases it does not. Technology will help (see above - Speech Understanding is moving speech into the 21st Century) but even with this technology there is still the requirement to provide support and expertise to facilitate the process of capturing information that is essential to the new age of data driven medicine. The Medical Transcriptionist is the knowledge worker who delivers the value add of helping turn clinical information into structured clinical data that includes the fine detail in the free form narrative that clinicians need and want to include while adding tagged structured data to deliver the full Healthstory for the patent's episode of care.

Computers Don't Have to Depersonalizes Medicine

The NY Times article this week; The Computer Will See You Now written by a pediatric physician complains that the electronic medical record has depersonalized her interaction.

HISTalk commented on it in his morning update and highlighted the complaints:

• using the computer in front of patients is intrusive
• standard questions must be asked in order even when they clearly don’t apply
• the doctor might swear in front of patients when the computer does something wrong
• computers lose context because doctors can’t underline, write bigger, or otherwise highlight something important

And I would add that because it gets printed out and is held in a computer it appears to carry more weight/validity.

As the author says:

The benefits (of the EMR) may be real, but we should not sacrifice too much for them

And the end result for her is

In short, the computer depersonalizes medicine. It ignores nuances that we do not measure but clearly influence care

But the prescribed treatment of a hybrid using a tablet ignores most of the issues and concerns highlighted and forgets the relative difficulty of interacting with tablet or screen based technologies while facing and talking a patient. No doubt there are some circumstances where this does make sense but the key to success is the hybrid approach or blended model that does uses all the available methods and tools.

It is important to not turn our clinicians into data entry clerks and utilizing the finely honed and developed skills of the medical editor/transcriptionist to convert this audio into the data necessary to drive the EMR. Technology can assist and provide some efficiency to the process and specifically Speech Understanding can automate some of this process. But this method of capturing the voice is repeatedly dropped or forgotten in this discussion. There are circumstances where this technique may not apply (public forum in earshot of nosy eavesdroppers fro instance) but for circumstances where it does voice provides a ready and efficient method. Historically this created text that the EMR systems had difficulty using (they are essentially data driven repositories) but with the addition of tagged information that is linked to the narrative all held in the complete Healthstory we bridge the gap. Not only allowing for the inclusion of the fine detail that is essential and influences care but linked and part of this same material is tagged structured and encoded data that can feed the data hungry EMR.

From Dictation to Direct Computer Input

I hosted a panel at the recent TEPR conference on "From Dictation to Direct Computer Input" that included presentations from Laura Bryan (MedEDocs Transcription) and Louis Cornacchia, MD, of (Doctations). I already posted my presentation on LinkedIn and in Google Docs but with the consent of my co-presenters I post the other presentations here

Laura Bryan, MedEDocs Transcription:
"Narrative Data in the EMR: Have Your Cake and Eat it Too"


Louis Cornacchia, MD, Doctations, Inc.
Doctations

Documentation at the Point of Care


and for completeness
Nick van Terheyden, MD
Dictation to Clinical Data: Automating the Production of Structured and

Why Speech Recognition is no Longer Sufficient

Speech recognition has been around for over 30 years and part of our consciousness since the mid 1960’s but it is only in the last 3-4 years that we have see the technology really start to deliver some value to the much beleaguered and over worked clinician. There are innumerable studies that demonstrate the savings linked to the efficiencies possible with faster report turnaround. Unfortunately producing more reports faster is not always the best answer and oftentimes this is simply making the patient information haystack larger. This tsunami of data is overwhelming even the best organized clinicians and many are struggling to keep up with this alongside the explosion of diagnostic and treatment choices. Keeping up with the medical knowledge is a full time job if anyone had the time – but they don’t.

Clinicians want to give great care - that's a universal maxim for the profession and anything that enables or facilitates this will be successful. But that's not what has been going on with speech recognition which has not only required a change in behavior to enunciate in special ways, dictate commands, speak slowly and add punctuation and in the ultimate punishment requiring the highly skilled and time pressured expert to review and correct poorly drafted content. The output is a blob of text that cannot be read or interpreted by the electronic medical record (EMR) since it is not machine readable.

Innovation in speech recognition was last made in 1993 when continuous speech recognition was rolled out. Since then the technology has stagnated and while allowing clinicians to type with their tongue has provided some efficiencies and improvements, speech recognition has failed to address the underlying challenges facing clinicians today. So now we have reached this point what’s next?

It is the capture of structured clinical data that can automatically feed the EMR that is the real goal. Achieving this requires an alternative approach to speech recognition, not just recognizing the words but actually understanding the meaning and context. Comprehending normal human speech is not a word recognition process but speech understanding process that takes as input not just the phonemes or parts of words but the complete context of a conversation including the intonation, the subject matter and relevant prior information which is all applied to the complete conversation. It is this process that enables humans to exhibit the “cocktail effect” which allows us to listen in to more than one conversation at a time even though we are not fully participating in either. The added knowledge allows for inferring of missed words and understanding the content allows us to complete the picture producing a fully understood interpretation of the speech. Speech understanding is the next frontier of innovation in clinical documentation.

This content can be stored as part of the full story - the Healthstory that contains the computer interpretable data AND the fine detail in the narrative that is the essence of clinical insight, judgment and essential to the transmission and flow of useful clinical information between all the team members delivering care in our multi disciplinary model.

Plans to Computerize the US Healthcare Records

CNN Money features an article today on the President-elect Obama's Digitizing the US Health Records System featuring the proposal to modernize the health care system by "making all health records standardized and electronic."

The plan calls for computerizing all records withing 5 years and is subject to much discussion in the various communities I participate in that is both positive (great investment and resources allocated to help fix a broken US healthcare system) to negative (are we just spending money on technology rather than spending money on
improving the outcomes and quality)

One observer put it this way:

this is a bit like watching a train wreck that is too late to stop

and more worryingly:

I don’t think that even a free EMR is attractive enough for most docs right now

One source cited came from information published by the AAFP (now restricted to members) that showed substantial variation in satisfaction with current implementations

....substantial variance in physician satisfaction with EMRs by product from “if I could get out I for zero cost I would” to “I’m not happy but my practice couldn’t live without it” to some actual satisfaction.....in large practices seldom rose above the “not happy, but …” level.

Current penetration and usage cited is at 8% of hospitals and 17% of physicians so there is a long way to go. Estimations for the price tag to achieve this range from $75 - 100 Billion. A Large percentage of any "bail out" that may or may not be approved but a small drop in the ocean of "$2 Trillion a year the industry spends" today.

But it is the usability that is required and ubiquitous access:

Doctors cannot spend hours and hours learning a new system," said Castillo. "It needs to be a ubiquitous, 'anytime, anywhere' solution that has easily accessible data in a simple-to-use Web-based application."

I agree but what is missing from this discussion is how to get this information into these systems. If we had a 100% adoption of EMR's today this would be an enormous mouth to feed with clinical data. It is no use implementing these systems if we don't have the data and the idea that clinicians will interact with the current technology, no matter how good it is with screens, feedback, menus and intuitive interfaces, is just not going to happen.

Providing the tools to capture the data naturally is going to be critical tot he success of these systems and there seems no better method that using voice. All our interactions are based on voice and capturing this as clinical data that can feed the data hungry EMR's. Speech recognition has gone some way to helping and automating this process but these older engines only output text which does not satiate the EMR's needs for structured and encoded clinically actionable data.

Ensuring that technology does not take over the practice of medicine and replace bedside skills is a major concern as detailed in this a New England Journal of Medicine article covered here where Dr Abraham Verghese says:

In short, bedside skills have plummeted in inverse proportion to the available technology. I truly believe that good bedside skills make residents more efficient," Verghese said. Doctors who rely on hands-on skills tend to order tests more judiciously, reducing the number of unnecessary and expensive trips to the radiology department.

To that point allowing for ready voice capture that generates the date required to make these clinical systems useful is essential and is precisely what speech Understanding does. Free form narrative that is converted into structured meaningful clinical documents that contain the full fine detail from the clinicians but also contains encoded structured data that is tagged against relevant controlled medical vocabularies including Snomed, RxNorm, RadLex, LOINC, ICD9 to name a few. All this can be output in CDA format for Common Document Types that has been defined and approved through the HL7 balloting process through the tremendous work being done by the Healthstory Project that creates one document that delivers multiple outputs for different purposes and retains complete and detailed clinical information. Due to the open nature and flexibility of the standard this format allows for ready adoption by multiple stake holders quickly creating immediate value to the participants by generating a flexible rich clinical document that provides useful output.

The conversation on Digital Health Records is going in the right direction and i think it is exciting but must include the capture of information and while speech understanding is not a panacea it is an essential contributor to the equation of making digital records work

Why Doctors Don't Like EMR's

Mr HISTalk is on the money in his latest blog

Doctors, like 99% of people, want to be consumers of information, not creators of it

Doctors want to give great care - that's a universal maxim for the profession and anything that enables or facilitates this will be successful and will get used. But that's not what has been going on:

The model of forcing doctors to share their thoughts through manual electronic documentation is fatally flawed. There is no industry … none … where someone with the education and time value of a physician is expected to peck on a computer, especially in front of a client who’s only going to get seven minutes of time (I’ve never seen a CIO typing meeting minutes into a PC, yet they’re often the ones beefing about computer-avoiding doctors).

and my personal favorite part of this piece - philosophic johad:

....trying to force those small business owners to use computers based on some kind of naive philosophic jihad against the inefficiency of paper-based recordkeeping

He is right "speech recognition" (or better yet the newer and more relevant speech understanding) is ready for prime time.....

Gathering the data should not be the focus - it should be a natural by product of the interaction and speech can help in achieving this. The real value comes with driving clinical information to support to decision making allowing clinicians to focus on the healthcare process

Medical Transcription the EMR and Speech Understanding

The Medical Records institute e-Newsletter from September contained an article by Claudia Tessier from the Medical records institute titled: "Medical Transcription and EMRs: Opportunity Lost?" that discussed the relationship between medical transcription and the electronic medical record (EMR). As the Claudia says:

...medical transcription offers a bridge to EMR adoption

But the idea that

the EMR offers the best opportunity yet to get rid of transcription and its concomitant headaches

Misses the opportunity for medical transcription and valuable data that is lost with the push towards the structured form based hunt and click style documentation. In a recent discussion with a clinician he lamented the loss of "the beauty and descriptive nature of medical language that has been used to describe medical conditions and image findings". Instead as he put it "we have turned detail rich clinical information into dumbed down fill in the blank cookie cutter reports" which do not reflect the richness of the information he wants to provide to his colleagues.

To date medical transcription is estimated to constitute 60% of the input into current EMR systems but that input is in the form of text blobs and not clinical data. The article goes on to suggest that:

...EMR vendors should ramp up their cooperation to create uniform integration. Let every one of the 300+ EMR systems allow dictation and let the market determine whether the related turnaround time, quality, costs, etc. (see below) are acceptable. Let users dictate on cell phones and dictation devices, or through laptops and tablets—whatever their preference.

Is spot on - the systems work and with better integration and more choices for input we open the doors to capturing input from our clinicians caring for patients and struggling to document for the benefit of communication with others members of the team as well as capturing sufficient information to be paid for the services they are delivering to their patients.

But this input is still not resolving the necessity to feed EMR's with clinical data which is essential for computer based systems to understand the information and be able to act on it. There are existing standards to hold and transmit this information including the Continuity of Care Record (CCR) which is "....working in collaboration with HL7 on the expression of ASTM's Continuity of Care Record content within HL7's CDA XML syntax and the seamless transformation of clinical and administrative data between the two standards.” - Rick Peters, MD

Transcription companies are already offering xml-based solutions that support structured output and the significant value this brings to EMR's is that this structured data has been checked and reviewed by medical transcriptionist/editor with expertise and knowledge to validate that content relative to the original dictation input of the clinician. More value from the validated data output from Medical transcription will make the transcription industry more of a partner and even more important in their contribution and ongoing role in the delivery of high quality healthcare.

So where does Speech Understanding come into all of this - unlike the traditional speech recognition technology which Hollywood conditioned us to expect far more comprehension on the part of the engine as captured in this classic clip from Star Trek IV - the voyage home where Montgomery Scott (Scotty) of the original series of Star Trek fame is trying to interact with a computer circa 1980.....

But his experience is typical of traditional speech recognition systems and a typical response either visually or verbally would be "Directions unclear - please repeat request"

Speech Understanding is the next generation of the technology, crossing the chasm between the need and desire of physician to dictate using all the richness and expressivity of language but that is recognized and understood and not only creates an accurate representation of the free form text but also produces a structured and encoded document. Structure is captured and stored in native CDA format and encoding is achieved using clinically relevant encoding systems such as RadLex for radiology, RxNorm for drugs, Universal Medical Language Systems (UMLS) and SnoMed for clinical terminology etc

You can have the best of both worlds and Medical Transcription will be around for years to come - albeit in a updated MTv2.0 form where the transcriptionist is a knowledge based worker proofing, editing and validating clinical data......so in the words of Spock: "Live Long and Prosper"

Medical Transcription Knowledge Based Workers - Increasing Demand

A working from Home blog "Undress4Success - Work From Home" posted an interesting article on the Medical Transcription industry and the increased demand for Medical Transcriptionists

.... (Overseas) rates are going up too, particularly in India, because they’ve realized that they can demand higher prices thanks to growing need and scarce availability of experienced MTs

The author is right on target - Medical Editors are going to be in high demand. They are and will become key knowledge workers in healthcare. As Tom Harnish says in the blog

...qualified medical transcriptionists (MTs) are in short supply

Good news for those who fear the flatening of the world and the application of technology. Speech recogntion will improve the productivity by automating the rote task of converting the spoken word into text:

The (speech recognition) technology may increase costs by 15% to 20%, but it can increase output 100% to 200% according to one MTSO owner

But to add even more value to this process knowledge based workers will need to do more than just listen to the audio and convert this into text (either by pure typing or editing/proofing a draft output from a speech recognition engine). Adding clinical data that is machine readable and semantically interoperable between all the clinical systems being implemented in our healthcare system will become a must. That process is mostly manual and much information is lost in the avalanche of text based documents that contain the information but only in human readable form. Knowledge based workers will need to provide data elements and structure to these documents turning them into data that can be fed into clinical systems.

CDA4CDT provides an ideal common environment that is designed to flexibly cope with the varied levels of data encoding but still provide the healthcare system with the text based document that can be printed and used as it is currently. But the additional information incorporated into this file allows for semantic interoperability and data exchange at a level that EMRs want and need turning the huge volume of clinical text documents into clinical data inputs to the medical record that can be shared and exchanged between systems

Medical Editors can provide this manually by tagging documents and encoding using the CDA4CDT standard or by using speech understanding technology. Speech understadning outputs a document that is tagged and structured with clinical data. This merges the role of medical editor with a true knoweldge based fuctnion of reviewing and correcting clincal data embedded in the file and clinical document.

Medical Editors are knowledge based workers and are in short supply......

CMS Physician Quality Reporting Initiative - Breaking down the Resistance

CMS continues to push the Physician Quality Reporting Initiative (PQRI)
which represents the move towards quality measurement and comparison healthcare shopping for consumers. While there are many concerns related to the comparability of data and the different case loads and risks adversity fo different phsycians and thier patient load. But it is the burdensome overhead of collecting data

Participating in the program, established by a 2006 tax bill, will require time, resources and staff-something not all physician practices are willing or able to provide, industry experts say. As a result, the physicians that decline to participate in the CMS' Physician Quality Reporting Initiative will lose out on the 1.5% bonus payment the initiative pays.

That makes for interesting reading given the increasing number of factors to collect

2008 PQRI consists of 119 quality measures, including 2 structural measures. One structural measure conveys whether a professional has and uses electronic health records and the other electronic prescribing.

The measures include:

In Diabetics:

• Hemoglobin A1c Poor Control in Type 1 or 2 Diabetes Mellitus
• Low Density Lipoprotein Control in Type 1 or 2 Diabetes Mellitus
• High Blood Pressure Control in Type 1 or 2 Diabetes Mellitus

In Cardiac Disease:

• Left Ventricular Systolic Dysfunction (LVSD) - placed on ACE
• Oral Antiplatelet Therapy Prescribed for Patients with Coronary Artery Disease
• Beta-blocker Therapy for Coronary Artery Disease Patients with Prior Myocardial Infarction (MI)
• Heart Failure: Beta-blocker Therapy for Left Ventricular Systolic Dysfunction

You can see the complete list here

Capturing this data can be a burden but imagine if you were able to extract this information using the standard clinical documentation practice of dictation. With the addition of speech understanding and extracting this information to a CDA4CDT document that contains the detailed human readable narrative but is linked to the extracted machine readable semantically interoperable clinically actionable data this point of resistance should diminish and capturing this data should become part of the normal clinical documentation process.

Speech Understanding will Bring More Information to the Doctor

Came across an interesting post by Steven F. Palter, MD from the docinthemachine blog. Specifically the blog he wrote on EMR=Clonewars

He notes that there is a hidden danger in EMRs of the inadvertant cloning of patients.

I don't think it is so much hidden or inadvertent - it's human nature and doctors are like everyone else - we always look for the path of least resistance. Copying from a previous note especially one using templates with a series of choices can be helpful.

But what he gets in his practice

..... is EMR records from other practices .... and the patients look identical.....Instead of all the details of a past treatment cycle it will list drug dose and failure with no detail of WHY it did not work. The diseases all look the same. There is never any detail on the nuances and subtle aspects of that individual’s condition. So when a group uses these records and they review a treatment every single person with the same disease (the “patient clones”) end up looking identical and treated identically. Cookie cutter assembly line medicine.

There's hope - Speech Understanding and in particular the use of CDA4CDT documents which make narrative notes interoperable with electronic medical records - bridging the divide between where we are today:

• More than 60% of clinical content produced, stored and locked in narrative documents

and where we want to get to

• Structured encoded information that is semantically interoperable and can be automatically processed and used by computer systems to help apply the best knowledge of healthcare diagnosis and treatments available today
  

What this means is a at the most basic level virtually any clinician can produce a minimal CDA document utilizing the simplest form of the structure which includes all important uniform metadata for all documents that allows them to be indexed, searched and the content integrated in a meaningful way into the EMR.

And at the high end, lab systems, pharmacy systems and EMR's can produce richly-structured, fully machine-processable CDA documents that remain human-readable as well as machine readable which will satisfy Steven's needs of :

the nuances and subtle aspects of that individual’s condition

So as Steve rightly points out quoting from AHIMA 2006 study:

....65 percent of chief information officers planned to get it (Speech Recognition) by 2008. It’s being touted as a natural add-on to the electronic medical record, since doctors are used to recording their notes, says Harry Rhodes, director of practice leadership for the American Health Information Management Association.

Voice can help solve the cloning of patients and the technology and the standard is available today.

Healthcare driving speech recognition technology growth

No big surprise here - healthcare is deriving huge benefits from speech recognition and a new report from DataMonitor just reaffirms this. You can see the press release here

Healthcare currently represents 85% of the market for PC- and server-based speech recognition technologies.

Good news for the providers of speech recognition and speech understanding:

Datamonitor estimates in its report, Automating and Enhancing Processes through Voice in Desktop and Back Office Environments, that the global market for speech recognition in healthcare is currently worth an estimated $170 million. It projects that between 2008 and 2013 the market will more than double in size.

Which seems very conservative when you consider the current size of transcription market estimated anywhere from 6 - 12 Billion dollars. And that industry and content is currently pouring documents into the Electronic Medicals Records (EMR) filling some 60% or more of the content in these systems today. The problem with documents is they are only really human readable (it is possible to apply some level of Natural Language Processing (NLP) to them but that process remains difficult and is not happening with any significant amount of market penetration today). What these systems need and are crying out for is data that is machine readable and therein lies the real opportunity for speech and in particular speech understanding to deliver clinical data directly into the EMR from the dictation process....

Consumerism and Clinical Knowledge

Providing the population with the right information at the right time to help them navigate the murky waters of health care delivery, insurance, hospitals, payors, denials, quality indicators and pay for performance statistics is going to be a key facet to the success or failure of any consumer driven revolution in health care.

The recent study by McKinsey “What Consumers Want in Health Care“ - summary here

Faced with health care decisions, consumers are concerned, confused, and unprepared. They rely heavily on personal recommendations and brand recognition, according to a recent McKinsey study

No big surprise here but if this is to change and the consumer is really to become informed and help drive change in health care delivery they need to have access to the right information

...48 percent report being prepared for common medical problems but only 15 percent for more disruptive medical scenarios...

To help satisfy this need consumers are already turning to the web in increasing numbers and estimates range from 50% to as high as 75/80% of patients use the web before and after visiting their physician. But much of the information available comes from a range of sources some less qualified than others. By providing structured data output as part of the clinical documentation process and delivering documents in a standard form that can be read but also imported into computer systems it should be possible to support this burgeoning need for clinical data as a natural part of the process - this is exactly what Clinical Document Architecture for Clinical
Clinical Documentation Architecture for Common Document Types (CDA4CDT) is intended to provide directly from dictation.

You can read more about the process and the concept in these articles
Guidelines Will Standardize Dictated Documents
HL7's first ballot in expected series under way
HL7 CDA: The Missing Link in Healthcare IT

As the McKinsey study revealed

Most people need additional guidance, education, and advice to make decisions
Innovative, cross-industry products that assist with the complex decision making will be highly valued by an influx of consumers eager for options but unsure where to turn

That's going to be difficult until we can standardize the clinical information coming out of clinicians offices and hospitals and make it available in machine readable form to consumers to aid their voyage of discovery in the new health care world of consumer driven choice