OR Manager November December 2022 - 20
Technology
BY CYNTHIA SAVER
State of natural language processing in surgery: Part 1
I
magine this: As a nurse in the OR
talks with a patient, a computer listens
in, recording the nurse's notes
so that data are added automatically to
be retrieved later. The surgeon and anesthesiologist
also interact with the patient
without the burden of manual data
entry, and the insurance company has
preauthorized the procedure using a
computer-generated algorithm. Later, an
algorithm ensures the facility receives
maximum reimbursement, and another
algorithm automatically extracts data
for submission to the American College
of Surgeons National Surgical Quality
Improvement Program (ACS NSQIP) so it
can be used to improve patient quality.
Natural language processing (NLP)
may make this scenario commonplace
in the future. It is already being used
to reduce manual data entry, improve
coding, and enhance research efforts.
NLP is becoming a global phenomenon,
with a predicted compound annual
growth rate of 20.3% from 2026 to
2028 (sidebar, NLP trending upwards).
" It's exciting, " says Yaa Kumah-Crystal,
MD, MPH, a pediatric endocrinologist
who works on improving the usability
NLP trending upwards
Natural language processing (NLP) is gaining
traction worldwide.
Predicted global market size of NLP in
healthcare and life sciences
of electronic health records
(EHR) through NLP
and is clinical director
for health IT in the biomedical
informatics department
at Vanderbilt
University Medical Center
in Nashville, Tennessee.
" It's an opportunity
for people to leverage
technology, where we can interact more
seamlessly with our computers, rather
than just use a keyboard. "
This two-part series looks at the
role of NLP in surgery. Part 1 describes
NLP and how it is being used in several
areas, including speech recognition
and preauthorization. Part 2 explores
NLP's role in outcomes and research,
the challenges associated with its wider
use, and considerations for purchasing
NLP-related products.
Yaa KumahCrystal,
MD,
MPH
What is NLP?
A McKinsey & Company report on NLP
defines it as " a specialized branch of
artificial intelligence [AI] focused on the
interpretation and manipulation of human-generated
spoken or written data. "
Maxim Topaz, PhD,
MA, RN, the Elizabeth
Standish Gill associate
professor of Nursing
at Columbia University
Medical Center and Columbia
University Data
Science Institute in New
York, says it refers to " a
Maxim Topaz,
PhD, MA, RN
set of computer algorithms that allow
computers to read human-generated
text " (sidebar, How NLP works).
NLP has several applications related
$4.3
billion
2026
$6.8
billion
2028
This is a compound annual growth rate
of 20.3%. The growth rate continues an
upward trend-the market size was predicted
to grow from $1.8 billion in 2021 to
20
OR Manager | Nov/Dec 2022
$4.3 billion in 2026, a compound annual
growth rate of 19%. In 2018, the market
was $1.4 billion.
Electronic health records (EHR) had a
market share of about 48% in 2018, the
highest among application type, which included
computer-assisted coding, clinician
document, and other. The computer-assisted
coding market was valued at $3.45
billion in 2019 and is forecasted to reach
$8.18 billion by 2027.
Key players in the market include 3M
Company, IBM Corporation, Microsoft Corporation,
Google LLC, Amazon Web Services
Inc., Cerner Corporation, Corti ApS,
Lexalytics Inc., Health Fidelity Inc., and
Linguamatics.
References included at the end.
to surgery including speech recognition,
which allows clinicians to dictate notes
in real time. But NLP's true power lies
in its ability to extract data that, through
AI techniques such as machine learning
(ML), computers can use to develop
tools such as algorithms. These algorithms
can support functions ranging
from helping clinicians make better patient
care decisions to ensuring accurate
coding of surgical procedures.
NLP extracts structured
data from sources
such as EHR, and it
also extracts and converts
unstructured data
to structured data, so
that a computer can
" read " it. Structured
data have a set format
(eg, diagnoses, billing codes, and laboratory
results), while unstructured data
do not (eg, radiographs and MRI scans).
" Structured data are things like vital
signs on a flow sheet, and unstructured
data are items that are in nurses' notes
and physicians' progress notes, " says
Davera Gabriel, RN, senior research
terminologist in biomedical informatics
and data science at Johns Hopkins
University in Baltimore. Most data in an
EHR are unstructured, so the ability to
harness this information is significant.
" NLP will parse the individual words
in a sentence, the order of those words,
and how close those words are to other
important things, " Gabriel says in describing
how unstructured data are proDavera
Gabriel,
RN
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