U.S. patent application number 11/766780 was filed with the patent office on 2007-12-27 for automatic decision support.
Invention is credited to Michael Finke, Detlef Koll.
Application Number | 20070299665 11/766780 |
Document ID | / |
Family ID | 38834406 |
Filed Date | 2007-12-27 |
United States Patent
Application |
20070299665 |
Kind Code |
A1 |
Koll; Detlef ; et
al. |
December 27, 2007 |
Automatic Decision Support
Abstract
Speech is transcribed to produce a transcript. At least some of
the text in the transcript is encoded as data. These codings may be
verified for accuracy and corrected if inaccurate. The resulting
transcript is provided to a decision support system to perform
functions such as checking for drug-drug, drug-allergy, and
drug-procedure interactions, and checking against clinical
performance measures (such as recommended treatments). Alerts and
other information output by the decision support system are
associated with the transcript. The transcript and associated
decision support output are provided to a physician to assist the
physician in reviewing the transcript and in taking any appropriate
action in response to the transcript.
Inventors: |
Koll; Detlef; (Pittsburgh,
PA) ; Finke; Michael; (Pittsburgh, PA) |
Correspondence
Address: |
ROBERT PLOTKIN, PC
45 BUTTERNUT CIRCLE
CONCORD
MA
01742-1937
US
|
Family ID: |
38834406 |
Appl. No.: |
11/766780 |
Filed: |
June 21, 2007 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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60815689 |
Jun 22, 2006 |
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60815688 |
Jun 22, 2006 |
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60815687 |
Jun 22, 2006 |
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Current U.S.
Class: |
704/235 |
Current CPC
Class: |
G16H 10/60 20180101;
G10L 15/26 20130101; G06F 40/30 20200101; G10L 15/02 20130101; G16H
10/20 20180101; G06F 40/103 20200101; G10L 19/00 20130101; G16H
15/00 20180101 |
Class at
Publication: |
704/235 |
International
Class: |
G10L 15/26 20060101
G10L015/26 |
Claims
1. A computer-implemented method comprising: (A) applying an
automatic speech recognizer to a spoken audio stream to produce a
first document including first codings associated with text in the
first document; (B) providing the first document to an automatic
decision support system; (C) receiving, from the automatic decision
support system, decision support output derived from the first
document; and (D) transmitting to a recipient a second document,
derived from the first document and the decision support output,
wherein the second document does not include the first codings.
2. The method of claim 1, wherein transcribing the spoken audio
stream and providing the first document to the automatic decision
support system are performed contemporaneously.
3. The method of claim 1, wherein the first codings encode concepts
represented by the text.
4. The method of claim 1, wherein (A) comprises: (A)(1) identifying
a second document including second codings associated with the
text; (A)(2) determining whether any of the second codings is
inaccurate; and (A)(2) correcting any of the second codings
determined to be inaccurate to produce the first document.
5. The method of claim 1, further comprising: (A) storing a record
associating the output with the first document.
6-8. (canceled)
9. The method of claim 1, further comprising: (D) rendering the
first document based on the output to produce a rendering of the
first document.
10. An apparatus comprising: speech recognition means for applying
an automatic speech recognizer to a spoken audio stream to produce
a first document including first codings associated with text in
the first document; document provision means for providing the
first document to an automatic decision support system; output
receiving means for receiving, from the automatic decision support
system, decision support output derived from the first document;
and document transmission means for transmitting to a recipient a
second document, derived from the first document and the decision
support output, wherein the second document does not include the
first codings.
11. The apparatus of claim 10, wherein the document provision means
comprises means for providing the first document to the automatic
decision support system contemporaneously with operation of the
speech recognition means.
12. The apparatus of claim 10, wherein the speech recognition means
comprises: means for identifying a second document including second
codings associated with the text; means for determining whether any
of the second codings is inaccurate; and means for correcting any
of the second codings determined to be inaccurate to produce the
first document.
13. The apparatus of claim 10, further comprising: means for
storing a record associating the output with the first
document.
14. The apparatus of claim 10, further comprising: means for
rendering the first document based on the output to produce a
rendering of the first document.
15. A computer-implemented method comprising: (A) applying an
automatic speech recognizer to a spoken audio stream to produce a
first document including first codings associated with text in the
first document; (B) applying a decision support method to the first
document to produce decision support output; (C) storing a record
associating the decision support output with the first document;
and (D) transmitting to a recipient a second document, derived from
the first document and the decision support output, wherein the
second document does not include the first codings.
16. The method of claim 15, wherein (B) comprises determining
whether the first document indicates at least one of a drug-drug,
drug-allergy, and drug-procedure interaction.
17. The method of claim 15, wherein (B) comprises determining
whether the first document indicates satisfaction of a clinical
performance measure.
18. The method of claim 15, wherein the first codings encode
concepts represented by the text.
19. The method of claim 15, wherein (A) comprises: (A)(1)
identifying a third document including third codings associated
with the text; (A)(2) determining whether any of the third codings
is inaccurate; and (A)(2) correcting any of the third codings
determined to be inaccurate to produce the first document.
20-22. (canceled)
23. The method of claim 15, further comprising: (A) rendering the
first document based on the output to produce a rendering of the
first document.
24. An apparatus comprising: speech recognition means for applying
an automatic speech recognizer to a spoken audio stream to produce
a first document including first codings associated with text in
the first document; decision support means for applying a decision
support method to the first document to produce decision support
output; record storage means for storing a record associating the
decision support output with the first document; and document
transmission means for transmitting to a recipient a second
document, derived from the first document and the decision support
output, wherein the second document does not include the first
codings.
25. The apparatus of claim 24, wherein the decision support means
comprises means for determining whether the first document
indicates at least one of a drug-drug, drug-allergy, and
drug-procedure interaction.
26. The apparatus of claim 24, wherein the decision support means
comprises determining whether the first document indicates
satisfaction of a clinical performance measure.
27. The apparatus of claim 24, wherein the speech recognition means
comprises: means for identifying a third document including third
codings associated with the text; means for determining whether any
of the third codings is inaccurate; and means for correcting any of
the third codings determined to be inaccurate to produce the first
document.
28. The apparatus of claim 24, wherein the record storage means
comprises means for modifying the first document based on the
output.
29. The apparatus of claim 24, further comprising: means for
rendering the first document based on the output to produce a
rendering of the first document.
30-33. (canceled)
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Prov. Pat. App.
Ser. No. 60/815,689, filed on Jun. 22, 2006, entitled,
"Verification of Extracted Facts"; U.S. Prov. Pat. App. Ser. No.
60/815,688, filed on Jun. 22, 2006, entitled, "Automatic Clinical
Decision Support"; and U.S. Prov. Pat. App. Ser. No. 60/815/687,
filed on Jun. 22, 2006, entitled, "Data Extraction Using Service
Levels," all of which are hereby incorporated by reference
herein.
[0002] This application is related to copending and commonly-owned
U.S. patent application Ser. No. 10/923,517, filed on Aug. 20,
2004, entitled "Automated Extraction of Semantic Content and
Generation of a Structured Document from Speech," which is hereby
incorporated by reference herein.
BACKGROUND
[0003] It is desirable in many contexts to generate a structured
textual document based on human speech. In the legal profession,
for example, transcriptionists transcribe testimony given in court
proceedings and in depositions to produce a written transcript of
the testimony. Similarly, in the medical profession, transcripts
are produced of diagnoses, prognoses, prescriptions, and other
information dictated by doctors and other medical
professionals.
[0004] Producing such transcripts can be time-consuming. For
example, the speed with which a human transcriptionist can produce
a transcript is limited by the transcriptionist's typing speed and
ability to understand the speech being transcribed. Although
software-based automatic speech recognizers are often used to
supplement or replace the role of the human transcriptionist in
producing an initial transcript, even a transcript produced by a
combination of human transcriptionist and automatic speech
recognizer will contain errors. Any transcript that is produced,
therefore, must be considered to be a draft, to which some form of
error correction is to be applied.
[0005] Producing a transcript is time-consuming for these and other
reasons. For example, it may be desirable or necessary for certain
kinds of transcripts (such as medical reports) to be stored and/or
displayed in a particular format. Providing a transcript in an
appropriate format typically requires some combination of human
editing and automatic processing, which introduces an additional
delay into the production of the final transcript.
[0006] Consumers of reports, such as doctors and radiologists in
the medical context, often stand to benefit from receiving reports
quickly. If a diagnosis depends on the availability of a certain
report, for example, then the diagnosis cannot be provided until
the required report is ready. For these and other reasons it is
desirable to increase the speed with which transcripts and other
kinds of reports derived from speech may be produced, without
sacrificing accuracy.
[0007] Furthermore, even when a report is provided quickly to its
consumer, the consumer typically must read and interpret the report
in order to decide on which action, if any, to take in response to
the report. Performing such interpretation and making such
decisions may be time-consuming and require significant training
and skill. In the medical context, for example, it would be
desirable to facilitate the process of acting on reports,
particularly in time-critical situations.
SUMMARY
[0008] Speech is transcribed to produce a transcript. At least some
of the text in the transcript is encoded as data. These codings may
be verified for accuracy and corrected if inaccurate. The resulting
transcript is provided to a decision support system to perform
functions such as checking for drug-drug, drug-allergy, and
drug-procedure interactions, and checking against clinical
performance measures (such as recommended treatments). Alerts and
other information output by the decision support system are
associated with the transcript. The transcript and associated
decision support output are provided to a physician to assist the
physician in reviewing the transcript and in taking any appropriate
action in response to the transcript.
[0009] For example, one embodiment of the present invention is a
computer-implemented method comprising: (A) applying an automatic
speech recognizer to a spoken audio stream to produce a first
document including first codings associated with text in the first
document; (B) providing the first document to an automatic decision
support system; (C) receiving, from the automatic decision support
system, decision support output derived from the first document;
and (D) transmitting to a recipient a second document, derived from
the first document and the decision support output, wherein the
second document does not include the first codings.
[0010] Another embodiment of the present invention is an apparatus
comprising: speech recognition means for applying an automatic
speech recognizer to a spoken audio stream to produce a first
document including first codings associated with text in the first
document; document provision means for providing the first document
to an automatic decision support system; output receiving means for
receiving, from the automatic decision support system, decision
support output derived from the first document; and document
transmission means for transmitting to a recipient a second
document, derived from the first document and the decision support
output, wherein the second document does not include the first
codings.
[0011] Another embodiment of the present invention is a
computer-implemented method comprising: (A) applying an automatic
speech recognizer to a spoken audio stream to produce a first
document including first codings associated with text in the first
document; (B) applying a decision support method to the first
document to produce decision support output; (C) storing a record
associating the decision support output with the first document;
and (D) transmitting to a recipient a second document, derived from
the first document and the decision support output, wherein the
second document does not include the first codings.
[0012] Another embodiment of the present invention is an apparatus
comprising: speech recognition means for applying an automatic
speech recognizer to a spoken audio stream to produce a first
document including first codings associated with text in the first
document; decision support means for applying a decision support
method to the first document to produce decision support output;
record storage means for storing a record associating the decision
support output with the first document; and document transmission
means for transmitting to a recipient a second document, derived
from the first document and the decision support output, wherein
the second document does not include the first codings.
[0013] Another embodiment of the present invention is a
computer-implemented method comprising: (A) receiving, from a
remote location, a spoken audio stream; (B) applying an automatic
speech recognizer to the spoken audio stream to produce a first
document including first codings associated with text in the first
document; (C) providing the first document to an automatic decision
support system; (D) receiving, from the automatic decision support
system, decision support output derived from the first document;
and (E) transmitting, to a recipient, at the remote location, a
second document, derived from the first document and the decision
support output.
[0014] Another embodiment of the present invention is an apparatus
comprising: means for receiving, from a remote location, a spoken
audio stream; means for applying an automatic speech recognizer to
the spoken audio stream to produce a first document including first
codings associated with text in the first document; means for
providing the first document to an automatic decision support
system; means for receiving, from the automatic decision support
system, decision support output derived from the first document;
and means for transmitting, to a recipient, at the remote location,
a second document, derived from the first document and the decision
support output.
[0015] Another embodiment of the present invention is a
computer-implemented method comprising: (A) receiving a first
portion of a streamed spoken audio stream from an audio stream
transmitter; (B) applying an automatic speech recognizer to the
stream spoken audio stream to produce a first partial document
including first codings associated with text in the first partial
document; (C) providing the first partial document to an automatic
decision support system; (D) receiving, from the automatic decision
support system, decision support output derived from the first
partial document; (E) determining whether the decision support
output satisfies a predetermined criterion triggering human review;
(F) if the decision support output is determined to satisfy the
predetermined criterion, then transmitting to the audio stream
transmitter, while receiving a second portion of the streamed
spoken audio stream, an indication that the decision support output
satisfies the predetermined criterion.
[0016] Another embodiment of the present invention is an apparatus
comprising: means for receiving a first portion of a streamed
spoken audio stream from an audio stream transmitter; means for
applying an automatic speech recognizer to the stream spoken audio
stream to produce a first partial document including first codings
associated with text in the first partial document; means for
providing the first partial document to an automatic decision
support system; means for receiving, from the automatic decision
support system, decision support output derived from the first
partial document; means for determining whether the decision
support output satisfies a predetermined criterion triggering human
review; and means for transmitting to the audio stream transmitter,
while receiving a second portion of the streamed spoken audio
stream, an indication that the decision support output satisfies
the predetermined criterion if the decision support output is
determined to satisfy the predetermined criterion.
[0017] Other features and advantages of various aspects and
embodiments of the present invention will become apparent from the
following description and from the claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0018] FIG. 1 is a dataflow diagram of a system for applying
automatic clinical decision support to a transcript of speech;
and
[0019] FIG. 2 is a flowchart of a method performed by the system of
FIG. 1 according to one embodiment of the present invention.
DETAILED DESCRIPTION
[0020] Embodiments of the invention are directed to techniques for
providing a transcript to a clinical decision support system for
the purpose of attaching critical alerts and other information to
the transcript for review by a physician. In general, speech is
transcribed to produce a report. At least some of the text in the
transcript is encoded as data. The codings may be verified for
accuracy and corrected if inaccurate. The resulting transcript is
provided to a decision support system to perform functions such as
checking for drug-drug, drug-allergy, and drug-procedure
interactions, and checking against clinical performance measures
(such as recommended treatments). Alerts and other information
provided by the decision support system are associated with the
transcript. The transcript and associated decision support output
are provided to a physician for review and any other appropriate
action in response to the decision support output.
[0021] More specifically, referring to FIG. 1, a dataflow diagram
is shown of a system 100 for applying automatic clinical decision
support to a transcript of speech. Referring to FIG. 2, a flowchart
is shown of a method 200 performed by the system 100 of FIG. 1
according to one embodiment of the present invention.
[0022] A transcription system 104 transcribes a spoken audio stream
102 to produce a draft transcript 106 (step 202). The spoken audio
stream 102 may, for example, be dictation by a doctor describing a
patient visit. The spoken audio stream 102 may take any form. For
example, it may be a live audio stream received directly or
indirectly (such as over a telephone or IP connection), or an audio
stream recorded on any medium and in any format.
[0023] The transcription system 104 may produce the draft
transcript 106 using, for example, an automated speech recognizer
or a combination of an automated speech recognizer and human
transcriptionist. The transcription system 104 may, for example,
produce the draft transcript 106 using any of the techniques
disclosed in the above-referenced patent application entitled
"Automated Extraction of Semantic Content and Generation of a
Structured Document from Speech." As described therein, the draft
transcript 106 may include text 116 that is either a literal
(verbatim) transcript or a non-literal transcript of the spoken
audio stream 102. As further described therein, although the draft
transcript 106 may be a plain text document, the draft transcript
106 may also, for example, in whole or in part be a structured
document, such as an XML document which delineates document
sections and other kinds of document structure. Various standards
exist for encoding structured documents, and for annotating parts
of the structured text with discrete facts (data) that are in some
way related to the structured text. Examples of existing techniques
for encoding medical documents include the HL7 CDA v2 XML standard
(ANSI-approved since May 2005), SNOMED CT, LOINC, CPT, ICD-9 and
ICD-10, and UMLS.
[0024] As shown in FIG. 1, the draft transcript 106 includes one or
more codings 108, each of which encodes a "concept" extracted from
the spoken audio stream 102. The term "concept" is used herein as
defined in the above-referenced patent application entitled
"Automated Extraction of Semantic content and Generation of a
Structured Document from Speech." Reference numeral 108 is used
herein to refer generally to all of the codings within the draft
transcript 106. Although in FIG. 1 only two codings, designated
108a and 108b, are shown, the draft transcript 106 may include any
number of codings.
[0025] In the context of a medical report, each of the codings 108
may, for example, encode an allergy, prescription, diagnosis, or
prognosis. In general, each of the codings 108 includes a code and
corresponding data, which are not shown in FIG. 1 for ease of
illustration. Each of the codings 108 may be linked to text in the
transcript 106. For example, coding 108a may be linked to text 118a
and coding 108b may be linked to text 118b. Further details of
embodiments of the codings 108 may be found in the above-referenced
patent application entitled, "Verification of Data Extracted from
Speech."
[0026] A coding verifier 120 may verify the codings 108 (step 204).
Any of a variety of techniques may be used to verify the codings,
examples of which may be found in the above-referenced patent
application entitled, "Verification of Data Extracted from Speech."
The verification process performed by the coding verifier 120 may
include correcting any codings that are found to be incorrect. The
coding verifier 120 therefore produces a modified draft transcript
122, which includes any corrections to the codings 108 or other
modifications made by the coding verifier 120 (step 206). Note,
however, that it is optional to verify the codings 108.
[0027] The modified draft transcript 122 is provided to a decision
support engine 124, which applies decision support methods 126 to
the modified draft transcript 122 to produce decision support
output 128 (step 208). If the codings 108 were not verified (e.g.,
if step 204 was not performed), then the original draft transcript
106, instead of the modified draft transcript 122, may be provided
to the decision support engine 124 in step 208 to produce the
decision support output 128. In other words, the draft transcript
106 may be unverified when decision support is applied to it.
[0028] An example of a decision support method is a method which
checks for drug-drug, drug-allergy, and/or drug-procedure
interactions. The decision support engine 124 may easily perform
such a method because concepts such as drugs, allergies, and
procedures have already been encoded in the modified draft
transcript 122 in a form that is computer-readable. Therefore, the
decision support engine 124 may use a database of drug-drug
interactions, for example, to determine whether the modified draft
transcript 122 describes any such interactions requiring attention
of a physician.
[0029] Another example of a decision support method is a method
which checks concepts encoded in the modified draft transcript 122
against clinical performance measures (such as recommended
treatments). For example, the American Heart Association (AHA)
recommends that patients who have had a heart attack, unstable
angina, or ischemic stroke take aspirin regularly. Therefore, one
of the decision support methods 126 may determine whether the draft
transcript 106 (or modified draft transcript 122) indicates that
the dictating physician stated that the patient has experienced a
heart attack, unstable angina, or ischemic stroke. If so, the
decision support method may further determine whether the draft
transcript 106 (or modified draft transcript 122) recommends (e.g.,
in the "recommended treatments" section) that the patient take
aspirin. If the decision support method determines that the patient
has had one of the three indicated conditions and that the doctor
did not recommend aspirin for the patient, then the decision
support method may alert the physician (through the decision
support output 128) to this fact and suggest that the physician
recommend aspirin to the patient. Again, the decision support
engine 124 may easily perform such a method because concepts such
as the patient's medical history and recommended treatments have
already been encoded in the transcripts 106 and 122 in a form that
is computer-readable.
[0030] As stated above, the decision support engine 124 produces
decision support output 128. An example of such output is a
critical alert indicating that the transcript 122 states that the
patient has been prescribed two drugs which are contraindicated
with each other. The decision support engine 124 may be configured
to label different components of the output 128 with different
priority levels. For example, the decision support engine 124 may
label certain components of the output 128 as requiring immediate
physician review, while labeling other components of the output 128
as requiring physician review, but not immediately. Alternatively,
for example, the decision support engine 124 may filter the results
it produces and include in the output 128 only those pieces of
information which exceed a certain priority level (e.g., only those
pieces of information requiring immediate physician review).
[0031] A decision support output processor 130 may attach the
decision support output 128 to the modified draft transcript 122 or
otherwise associate the decision support output 128 with the
modified draft transcript 122 (step 210). For example, in the
embodiment shown in FIG. 1, the decision support output processor
130 stores the decision support output 128 within the modified
draft transcript 122, thereby producing a processed draft
transcript 132 containing the contents of both the modified draft
transcript 122 and the decision support output 128.
[0032] As another example, decision support output processor 130
may use the decision support output 128 to modify the modified
draft transcript 122. For example, if the decision support output
128 indicates a drug-drug allergy, the decision support output
processor 130 may modify the code(s) for the contraindicated
drug(s) in the transcript 122 so that the text corresponding to the
drug(s) appears in boldface, in a conspicuous color (e.g., red), or
in some other manner that calls attention to the text. As another
example, the decision support output processor 130 may include in
the transcript 122 a textual comment describing the drug-drug
allergy such that the comment appears in the vicinity of the text
when it is rendered.
[0033] The processed draft transcript 132 (and the decision support
output 128, if it is not contained within the processed draft
transcript 132) may be provided to a physician or other reviewer
138 for review. Alternatively, for example, information derived
from the processed draft transcript 132 and/or decision support
output 128 may be provided to the reviewer 138 for review. The
reviewer 138 may be the same person as the dictator of the spoken
audio stream 102.
[0034] For example, a renderer 134 may render the processed
transcript 132 based on the decision support output 128 to produce
a rendering 136 (step 212). The rendering 136 may display both the
text of the transcript 132 and the output 128. As described above,
the rendering 136 may reflect the output 128 in a variety of ways,
such as by using the output 128 to modify the manner in which the
text of the transcript 132 is rendered.
[0035] For example, the rendering 136 may be a flat text document
or other document which does not include the codings 108a-b and
other data which typically require an EMR and/or decision support
system to process. For example, the rendering 136 may be a Rich
Text Format (RTF) or HTML document suitable for display by a
conventional word processor or web browser. The renderer 134 may,
for example, strip out the codings 108a-b from the processed draft
transcript 132 or otherwise process the draft transcript 132 to
produce the rendering 136 in a format suitable for processing
(e.g., displaying) without an on-site EMR and/or decision support
system. The rendering 136, therefore, need not be directly or
immediately displayed to the reviewer 138. For example, the
renderer 134 may transmit the rendering 136 to the reviewer 138
electronically (e.g., by email, FTP, or HTTP), for subsequent
viewing in any manner by the reviewer 138.
[0036] The reviewer 138 (e.g., physician) reviews the rendering
136. The system 100 may include an approval mechanism (not shown)
which enables the reviewer 138 to provide input indicating whether
the reviewer 138 approves of the transcript 132. In the medical
context, for example, if the reviewer 138 is a physician, the
physician may be required to sign off on the transcript 132, as
represented by the rendering 136. The use of the decision support
output 128 in the process of producing the rendering 136
facilitates the process of reviewing the transcript 132. For
example, if the output 128 indicates that the transcript 122
describes a particular drug-drug allergy, then the rendering 136
may display a conspicuous indication of such allergy, thereby
increasing the likelihood that the physician-reviewer 138 will
notice such an allergy and decreasing the time required for the
physician-reviewer 138 to do so.
[0037] Embodiments of the present invention have a variety of
advantages. For example, in conventional systems, a physician
typically dictates a report. The report is transcribed and the
transcript is presented to the physician for review and signature.
The physician must conclude that the report is accurate before
signing it. If the physician's facility does not have an onsite EMR
system and/or decision support system, then it may not be possible
or feasible for decision support to be applied to the report before
presenting it to the physician for signature. As a result, the
physician must review and sign the report, thereby attesting to its
accuracy, without the additional assurance of accuracy that a
decision support system may provide.
[0038] In contrast, the techniques disclosed herein facilitate the
process of applying decision support and other quality assurance
measures to a draft report before providing the report to the
physician for signature, i.e., while the report is still in its
unsigned state. As a result, the techniques disclosed herein may be
used both to increase the quality of signed reports and to reduce
the amount of time required by physicians to review reports before
signing.
[0039] In particular, the techniques disclosed herein may be used
to bring the benefits of automatic clinical decision support and
other automated quality assurance measures to care providers who do
not have an on-site Electronic Medical Record (EMR) system which is
capable of consuming coded document formats. Such EMR systems are
costly and therefore are not used by small clinics. Embodiments of
the present invention do not require an on-site EMR system because
all processing of encoded documents may be integrated into the
transcription workflow and therefore performed by, for example, an
outsourced transcription service at a remote location in relation
to the clinic or other source organization. The dictator of speech
102 may, for example, transmit the spoken audio stream 102 to such
a service at a remote location in any manner, such as by electronic
transmission.
[0040] The service may then perform method 200 (FIG. 2) at an
off-site location in relation to the dictator of speech 102. The
service may then transmit the processed draft transcript 132,
decision support output 128, and/or the rendering 136 to the
reviewer 138 in any manner, such as by any form of electronic
transmission. If the reviewer 138 does not have an on-site EMR
and/or decision support system, however, the service may provide
the transcript 132, decision support output 128, and/or rendering
136 to the reviewer 138 in a flat text format or other format that
does not require the reviewer 138 to have an on-site EMR or
decision support system to process. For example, the service may
provide only the rendering 136, and not the processed draft
transcript 132 or decision support output 128, to the reviewer 138.
Therefore, embodiments of the present invention may be used to
provide the benefits of automatic clinical decision support systems
to providers through medical transcription services without
requiring deployment of EMR systems on the provider side.
[0041] More generally, embodiments of the present invention use a
human transcription workflow to enable automatic clinical decision
support, disease management, and performance tracking. As described
above, conventional transcription systems typically produce
transcripts which are "flat" text documents, and which therefore
are not suitable for acting as input to decision support processes.
In contrast, embodiments of the present invention produce
transcripts including structured data which encode concepts such as
allergies and medications, and which therefore may be processed
easily by automatic decision support systems. Such embodiments may
therefore be integrated with clinical decision support systems and
provide the benefits of such systems quickly and easily.
[0042] It is difficult or impossible to use flat text transcripts
in this way because a decision support system would need first to
interpret such text to apply decision support methods to it. Any
attempt to use human intervention and/or natural language
processing to perform such interpretation will suffer from the slow
turnaround times and relatively high error rates associated with
such techniques. In contrast, and as described in more detail in
the above-referenced patent applications, transcripts may be
produced using embodiments of the present invention quickly and
with a high degree of accuracy, thereby making such transcripts
particularly suitable for use as input to automatic clinical
decision support systems.
[0043] Even in cases in which the system 100 of FIG. 1 is
implemented in conjunction with an outsourced transcription
service, the techniques disclosed herein do not require the entire
spoken audio stream 102 to be spoken before clinical decision
support may be applied to it. For example, consider a case in which
a physician dictates the spoken audio stream 102 into a handheld
recording device, which streams the spoken audio stream 102 to the
transcription system 104 while the physician is speaking the spoken
audio stream 102. The transcription system 104 may begin
transcribing the beginning of the spoken audio stream 104 while the
physician dictates subsequent portions of the spoken audio stream
102, which continue to be streamed to the transcription system 104.
As the draft transcript 104 is being produced, it may be processed
by the remainder of the system 100 as described above with respect
to FIGS. 1 and 2.
[0044] As a result, if the decision support system 124 identifies a
problem (such as a drug-drug allergy) requiring physician review,
the decision support output 128 (e.g., in the form of the processed
draft transcript 132 and/or the rendering 136) may be provided to
the physician-reviewer 138 while the physician is still dictating
the remainder of the spoken audio stream, i.e., before the entire
spoken audio stream 102 has been transmitted to the transcription
system 104 and before the entire draft transcript 106 has been
produced. One benefit of such real-time application of decision
support to the spoken audio stream 102 is that the decision support
output 128 may be provided to the dictating physician before the
physician has finished dictating, thereby presenting the physician
with an opportunity to correct any errors during a single dictation
session and while the correct content of the session is still fresh
in the physician's mind.
[0045] It is to be understood that although the invention has been
described above in terms of particular embodiments, the foregoing
embodiments are provided as illustrative only, and do not limit or
define the scope of the invention. Various other embodiments,
including but not limited to the following, are also within the
scope of the claims. For example, elements and components described
herein may be further divided into additional components or joined
together to form fewer components for performing the same
functions.
[0046] Although certain examples provided herein involve documents
generated by a speech recognizer, this is not a requirement of the
present invention. Rather, the techniques disclosed herein may be
applied to any kind of document, regardless of how it was
generated. Such techniques may, for example, be used in conjunction
with documents typed using conventional text editors.
[0047] The spoken audio stream 102 may be any audio stream, such as
a live audio stream received directly or indirectly (such as over a
telephone or IP connection), or an audio stream recorded on any
medium and in any format. In distributed speech recognition (DSR),
a client performs preprocessing on an audio stream to produce a
processed audio stream that is transmitted to a server, which
performs speech recognition on the processed audio stream. The
audio stream may, for example, be a processed audio stream produced
by a DSR client.
[0048] The invention is not limited to any of the described domains
(such as the medical and legal fields), but generally applies to
any kind of documents in any domain. For example, although the
reviewer 138 may be described herein as a physician, this is not a
limitation of the present invention. Rather, the reviewer 138 may
be any person. Furthermore, documents used in conjunction with
embodiments of the present invention may be represented in any
machine-readable form. Such forms include plain text documents and
structured documents represented in markup languages such as XML.
Such documents may be stored in any computer-readable medium and
transmitted using any kind of communications channel and
protocol.
[0049] Furthermore, although particular examples are described
herein in conjunction with clinical decision support, this is not a
limitation of the present invention. Rather, the techniques
disclosed herein may be applied to other forms of automated
decision support based on transcripts containing structured text
with encoded data. For example, the techniques disclosed herein may
be used to verify document completeness, such as whether the
dictator of the transcript 106 mistakenly omitted a required
section of the transcript 106.
[0050] The decision support engine 124 may include any mechanism,
such as a software- or hardware-based mechanism, for applying
automatic decision support to the modified draft transcript 122.
Although the decision support engine 124 may be described herein as
applying automated methods, this does not preclude some degree of
human interaction with the decision support engine 124 to perform
its functions.
[0051] Furthermore, the decision support engine 124 may receive
inputs in addition to the modified draft transcript 122 to assist
in providing decision support. For example, a transcription service
may produce multiple transcripts over time describing a single
patient. In the course of producing such transcripts, the
transcription service may build an archive of data about the
patient, derived from data in the transcripts. Then, when the
transcription service receives a new spoken audio stream for
transcription, the transcription service may identify that the new
spoken audio stream refers to a patient for whom a data archive
already exists. The transcription service may then provide not only
the current draft transcript, but also some or all of the patient's
data archive, to the decision support engine 124. The decision
support engine 124 may benefit from such additional data about the
patient, such as medications previously prescribed to the patient,
to detect drug-drug allergies or other problems which could not be
detected from the current transcript in isolation.
[0052] The techniques described above may be implemented, for
example, in hardware, software, firmware, or any combination
thereof. The techniques described above may be implemented in one
or more computer programs executing on a programmable computer
including a processor, a storage medium readable by the processor
(including, for example, volatile and non-volatile memory and/or
storage elements), at least one input device, and at least one
output device. Program code may be applied to input entered using
the input device to perform the functions described and to generate
output. The output may be provided to one or more output
devices.
[0053] Each computer program within the scope of the claims below
may be implemented in any programming language, such as assembly
language, machine language, a high-level procedural programming
language, or an object-oriented programming language. The
programming language may, for example, be a compiled or interpreted
programming language.
[0054] Each such computer program may be implemented in a computer
program product tangibly embodied in a machine-readable storage
device for execution by a computer processor. Method steps of the
invention may be performed by a computer processor executing a
program tangibly embodied on a computer-readable medium to perform
functions of the invention by operating on input and generating
output. Suitable processors include, by way of example, both
general and special purpose microprocessors. Generally, the
processor receives instructions and data from a read-only memory
and/or a random access memory. Storage devices suitable for
tangibly embodying computer program instructions include, for
example, all forms of non-volatile memory, such as semiconductor
memory devices, including EPROM, EEPROM, and flash memory devices;
magnetic disks such as internal hard disks and removable disks;
magneto-optical disks; and CD-ROMs. Any of the foregoing may be
supplemented by, or incorporated in, specially-designed ASICs
(application-specific integrated circuits) or FPGAs
(Field-Programmable Gate Arrays). A computer can generally also
receive programs and data from a storage medium such as an internal
disk (not shown) or a removable disk. These elements will also be
found in a conventional desktop or workstation computer as well as
other computers suitable for executing computer programs
implementing the methods described herein, which may be used in
conjunction with any digital print engine or marking engine,
display monitor, or other raster output device capable of producing
color or gray scale pixels on paper, film, display screen, or other
output medium.
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