Instant Text Comparative Reviews

Comparing Instant Text to Other Abbreviation Programs

by Burt Danet

Posted March 14, 1996 on sci.med.transcription

The following was accomplished today:

1. I was able to translate a Flash Forward file I have been developing for about a year with nearly 8850 entries into a text file. This text file was imported into Word Perfect, briefly edited, and saved again, from within WordPerfect, as a text file (size: 717,313KB).
2. I then entered Instant Text and used the Glossary commands to create a new glossary based on this text file from Flash Forward. The new IT glossary was then merged with a previously constructed glossary compiled from text files of reports I had in the computer from previous work.
3. The newly revised combined glossary was then used in a trial, creating text from within Instant Text. The following took place:

a. I typed, Tp (2 strokes)
b. In the phrase window there appeared a phrase, The patient which I then entered with a ; (1 stroke)
c. Immediately, without doing anything else, there appeared in the phrase window several phrases, including one at the bottom of the list, is being admitted to the hospital because of which I entered by going cursor-up once and then typing another ; (2 strokes)
d.I then typed a and pressed the space bar. (2 strokes)
e. I then typed mi (2 strokes) and myocardial infarction appeared in the top of the phrase window which I entered with another ; (1 stroke)
f. Then I typed . to end the sentence (1 stroke).
g. So I typed, Tp;;a Space mi;. for a total of 11 strokes.
h. The resulting expansion was: The patient is being admitted to the hospital because of a myocardial infarction. — 81 strokes total.

Results:

In this example, with minimal experience with Instant Text, but using the powerful features of the program to create a glossary (based on work that has taken a year!) I found that IT could actually anticipate what I might be about to type! It gave me options BEFORE I entered any further keys to signify what I was about to do — just by typing in tp to enter the patient.

Conclusion:

It is obvious that this phenomenon is one that many people would want to replicate. Without having enough experience to see how often this can occur, it certainly was mind boggling to see the computer (IT program) actually anticipating what I was going to type — not just a word, but a good portion of an entire sentence. The only response to this is, Let's do this some more!

Technical Comparison:

There follows a more detailed comparison of the identical sentence being typed with the combined PRD+/Flash Forward abbreviation expander programs in use at the present time versus the Instant Text results.

I obtained the IT results with no training other than simply familiarizing myself with the basic aspects of the program and then learning how to create glossaries. I obtained the computer shorthand/abbreviation expander experience after seven years of programming into PRD+ and one year of programming with Flash Forward and PRD+ in combination.

So, after the above experience with Instant Text, for comparison purposes, I went back and took this same sentence, The patient is being admitted to the hospital because of a myocardial infarction. and typed it using the PRD+/Flash Forward combined computerized shorthand programs. The results are as follows:

Typed Saved Total Savings Gain






PRD+ 20 34 54 63% 170%
Flash Forward 8 27 55 49% 300%
PRD/FF 28 61 89 76% 218%
Instant Text 13 70 83 85% 538%






These results would appear to be self-explanatory and the conclusion is obvious. One would rather have a 538% productivity gain rather than a 218% productivity gain. One would rather save 70 out of 82 keystrokes rather than 61 out of 89 keystrokes. One would rather have an 85 percent savings rather than a 76 percent savings.

In this one instance, without trying anything but an experiment, I stumbled across the powerful capability of Instant Text to use previously created text files in a person's computer to compile a glossary and then combine that glossary with another made from a previously developed abbreviation expander list (with short and long forms in another text file), to compile a resulting glossary (322,316Kb) which then made the above example possible.

Burt Danet