Tomorrows Transcription Tools: What New Technology Means for Healthcare
by Joe Weber, MS, MBA
What does the future hold for the transcription industry? In the third
installment of the Journals series on transcription, take a look
at the new technology aimed at boosting productivity, improving accuracy,
and, in some cases, asking physicians for direct information input.
The year is 2006, and there are just a few hundred medical transcriptionists
(MTs) still transcribing reports, serving only those older physicians
who havent changed with the timesand the times have definitely
changed. Physicians have finally recognized the power of electronic health
records (EHRs) as well as the fact that this power is realized only if
they input clinical data directly into the EHR.
The vast majority of physicians are using empirically refined templates,
pick lists, and other methods of structured, codifiedinput through the
evolved progeny of todays Palm PCs, pocket PCs, and Tablet PCs.
Input methods include touch-screen, speech recognition, handwriting recognition,
and perhaps other technology not yet invented. There are no longer any
delays or expenses resulting from transcription. Plus, healthcare organizations
enjoy numerous benefits derived from analyzing codified clinical data.
But this is only one vision.
Another vision of 2006 incorporates an unavoidable reality: many physicians
strongly resist directly inputting clinical data. They believe it slows them down, which outweighs the potential overall
healthcare benefits. Additionally, these physicians believe that structured
input of patient information limits the freedom of expression afforded
by free text. And frankly, these physicians dont put much stock
in the value of clinical practice analysis. So transcription continues.
In fact, it expands dramatically. Due to regulatory controls and other
pressures, more providers dictate more clinical notes than ever. The need
for MTs explodes. In 2006, there are half a million MTs required to convert
voice dictations into text, more than double todays number.
Which is the accurate vision? Neither. In three years, its likely
that the transcription industry will resemble a combination of these two
visions. More clinical notes will be needed in computer-ready formand
not through the scanning of handwritten paper charts. Both coded input
and electronic free text will have an important place in the future. But
technology continues to advance, and these advances will ultimately alter
both the state of clinical documentation and the face of medical transcription.
In this article, well take a look at the most intriguing documentation
technologies of today and tomorrow.
Direct Data Input Enables Analysis
Most EHRs already offer physicians the opportunity to fully construct
their clinical notes by selecting the appropriate data right on their
computers or personal digital assistants (PDAs). They can do this with
a mouse, touch-pen, or voice. Templates for common conditions facilitate
the input process, but it still generally takes longer to generate a note
in this manner than by dictation. Yet much of the documentation can be
done during the encounter, and the payoff from this method could be awesome.
One of the reasons healthcare costs continue to escalatenow consuming
15 percent of what American households spend every year, with double-digit
increases from year to yearis because we are not learning from experience.
The only way to turn the crisis around is to implement continuous quality
improvement. We must learn from analyzing the process and outcome of every
clinical encounter. Then this new knowledge will enable us to increase
the quality and decrease the cost of care. But we can only do this if
we have data to analyze.
Direct physician input of structured/codified data would provide the
data we need, particularly if the industry adopts a controlled clinical
vocabulary, such as SNOMED-CT. Then we will be able to understand which
findings are connected to which diagnoses, which treatments work best
under what conditions, and when diagnostic tests are worth performing.
We can convert this learning to point-of-care clinical guidance and decision
support to improve the cost-effectiveness of healthcare. But to make this
happen, physicians will have to stop dictating and, instead, enter clinical
data directly into a computer. This will not be an easy change to get
them to make.
Physicians Input Free Text
It is likely to be a while before most physicians agree to perform direct
entry of structured/codified data. Even when physicians agree to enter
some data this way, they will still need a free-text option
for information that doesnt fit into the coding structure.
Free text can be entered by typing, speaking, or handwriting. Most physicians
will prefer speaking. Front-end speech recognition enables
a physician to dictate into a computer or a portable (possibly wireless)
device for uploading to the computer. Recognized text appears immediately
on the screen. The recognition engine will make a few errors and the dictator
will correct those errors via keyboard or voice.
Less than 5 percent of practicing physicians are currently using speech
recognition to generate clinical reports. And even some of these early
adopters confess that they could see at least two to three additional
patients each day if they didnt have to take the time to correct
the errors made by the recognition engine, despite its impressive accuracy
rates of 95 to 99 percent. However, those physicians claiming a time savings
by having their reports transcribed by an MT instead may not be reviewing
their transcribed reports for errors either.
Handwriting recognition is finally coming of age. The new tablet PCs
provide incredible accuracy for reasonably legible handwriting. And this
technology, like speech recognition, will become more accurate over time.
Although speech is considerably faster than handwriting, it is often more
palatable to handwrite notes in the presence of the patient. So both will
have an important place in the future of free-text clinical documentation.
None of the free-text entry methods provide useful data for clinical
practice research. However, natural language processing (NLP) technology
can extract clinical facts from narrative reports and turn those facts
into codes. NLP is currently in its infancy, but it too will advance.
Clinical guidance is considerably easier to implement with structured,
codified input than with free text, but changing physician behavior is
not an easy challenge. Therefore, free text with NLP-aided analysis may
prove to be a reasonable option in many clinical settings.
Patients Can Contribute Data
Patients are an untapped information resource in the healthcare delivery
system. Why not let them contribute to the documentation of their own
ambulatory clinical episodes? They clearly shouldnt be documenting
the physical exam, assessment, or management plan. But with the right
tool, they can effectively enter the subjective data related to their
symptoms and relevant medical history, which, on average, represents about
half of the entire encounters documentation. In fact, they should
be able to provide much more comprehensive and useful data than a physician
could document in todays all-too-brief clinical encounters.
With a highly developed medical knowledge base driving the computer-based
patient questionnaire, the quality and relevance of patient history information
will be superior to the data from a physician interview. Employing a patient
questionnaire would provide several benefits, including:
- patients know that all their symptoms will be noted
- encounters will be more efficient
- dictation and data entry time will be decreased
- transcription costs will be decreased
- service (and billing levels) will increase
Patients can fill out these structured questionnaires either in the waiting
room or over the Web. If over the Web, the summarized and organized output
can be used for triage. For example, urgency and appropriate length of
appointment can be determined. Indicated lab and radiology tests can be
requisitioned, so that results are available at encounter time. And sometimes
self-care can be prescribed or the patient can be immediately directed
to a specialist. Patient-provided histories have the potential to significantly
improve the cost effectiveness of healthcare if physicians embrace this
powerful and innovative approach to streamlining healthcare encounters.
The organized output from these computerized questionnaires can also
be used to form a basis for Web visits. Many conditions do
not actually require a face-to-face encounter with a healthcare provider.
By using a comprehensive patient history provided over the Web, physicians
can sometimes treat patients via e-mail. Patients dont have to make
the trip to the doctor and the cost of care is substantially reduced.
Although patients might have to pay a modest fee out-of-pocket for this
service, some insurance companies are investigating the quality and cost
implications of including Web visits in their coverage. The implications
this approach holds for our nations overall cost of healthcare are
Speedtyping Saves Transcription Time
Theres no need for transcriptionists to type out every word in
a report anymore. Speedtyping software, sometimes called abbreviation
expanders or word expanders, can save a significant
number of keystrokes, thereby improving transcriptionist productivity.
There are two kinds of speedtyping software available.
Conventional speedtyping software works like an autocorrecting function
in a word processor: users create their own set of abbreviations. For
example, an MT could set up uga as the abbreviation for under
general anesthesia. Whenever the MT hits the spacebar or punctuation,
the software checks the abbreviation list. If theres something in
the list that matches the characters that the MT just typed, it replaces
the abbreviation with the associated full text. This software can save
about 30 percent of an MTs keystrokes, and is provided by multiple
A more advanced approach to speedtyping, offered by a smaller number
of vendors, can save about 70 percent of a transcriptionists keystrokes.
It comes with a built-in vocabulary of the words that are used in medical
reports. Users can then add words, phrases, and blocks of text to reflect
any uniqueness in the kinds of reports they transcribe. This software
shows the transcriptionist, character by character, which word or phrase
will be inserted if the spacebar (or punctuation) is pressed. It also
provides a list of other words and phrases that can be entered by striking
their associated keys. The primary word and the listed words may be ordered
by frequency of occurrence in medical reports. Thus, the words that occur
most frequently become the easiest to type.
Productivity increases with speedtyping software typically range from
20 to 80 percent, though some users actually double their productivity.
Some software ensures correct spelling and hyphenation of all words. Plus,
it automatically capitalizes appropriate words such as brand names. These
programs have a one-time cost around $200. Consider what a 50 percent
increase in transcription productivity is worth each year. There may be
no better return on investment anywhere in the domain of healthcare information
Back-end Speech Recognition Transparent to Doctors
Back-end speech recognition could also be called computer-assisted transcription.
Physicians dictate as usual, while their digital voice files are run through
a speech engine on a local or remote server. A draft report is then electronically
shipped to a medical editor, along with the synchronized voice file. The
editor listens, reads, and corrects any mistakes. The corrected text is
sent back to the dictator for review and authentication.
Even with the quality-degraded voice files resulting from telephone dictation,
this approach is expected to eventually average enough accuracy for most
dictators that editors will be far more productive than transcriptionists.
To achieve this improvement, its important to provide the editors
with software designed to streamline the correction process. With recognition
accuracy in the 90 to 95 percent range (which is one mistake on every
one or two lines), if physicians have to make the corrections, they will
be highly distressed. However, an editor armed with the appropriate editing
software should find the correction process much faster than transcribing
the entire report. Most of these editors will be former MTs.
Some of the implementations of this approach can, on average, double
productivity. However, the technology is expensive, and users will have
to pay to the providing vendor some of what is saved in labor cost. Nonetheless,
back-end recognition is gaining traction in the industry and likely will
play a major role in the future of clinical documentation.
The most appealing aspect of these back-end systems is that they dont
require physicians to change behavior. Physician resistance to change
is a reality that often has to be accepted if we want to move forward
at all. As Lawrence Weed, MD, father of the Problem-Oriented Medical
Record adopted in the 1970s and Problem-Knowledge Couplers, a software
tool that links patient problems to a medical knowledge base, once said,
If physicians were in charge of airports, there would be no radar.
Just intensive care units all around the periphery. Weed, an entrepeneur
and healthcare visionary, argues that the healthcare systems reliance
on doctors memories for effective care is dangerous and inefficient.
Physicians and patients would be better served, he says, if doctors instead
accessed medical literature at the point of care to assign diagnoses and
shape treatment plans.
Which Tool Meets Your Needs?
Weve taken a brief look at some existing and evolving technologies
that should alter the healthcare documentation landscape in the coming
years. The vision of 2006 is still a bit hazy. The solutions outlined
above will find their way into more healthcare settings as the years go
by. But one size does not fit all. The key will be in combining technologies
to meet site-specific needs.
The challenge facing HIM managers is to design and implement the documentation
process most compatible with their organizational goals, available resources,
and physician mindsets. This is by no means a small challenge, but it
is surely an exciting one. Clinical documentation methodologies may be
the most powerful tools available for improving the quality and cost effectiveness
of healthcare. By 2006, the technologies will be further enhanced. Some
of these tools can bring impressive efficiency and cost reduction to the
transcription process. But others can actually advance the science of
medicine, ultimately providing the kind of point-of-care clinical guidance
that will make healthcare be all that it can be.
Dayna Pierzchala, MBA, RHIA
Joe Weber (firstname.lastname@example.org)
is CEO of Narratek, provider of clinical documentation solutions.
Weber, Joe. "Tomorrow's Transcription Tools: What New Technology Means for Healthcare." Journal of AHIMA 74, no.3 (2003): 39-43.