Researchers
at
the
University
of
Waterloo
have
found
that
sentiments
in
the
nursing
notes
of
health
care
providers
are
good
indicators
of
whether
intensive
care
unit
(ICU)
patients
will
survive.
Hospitals
typically
use
severity
of
illness
scores
to
predict
the
30-day
survival
of
ICU
patients.
These
scores
include
lab
results,
vital
signs,
and
physiological
and
demographic
characteristics
gathered
within
24
hours
of
admission.
“The
physiological
information
collected
in
those
first
24
hours
of
a
patient’s
ICU
stay
is
really
good
at
predicting
30-day
mortality,”
said
Joel
Dubin,
an
associate
professor
in
the
Department
of
Statistics
and
Actuarial
Science
and
the
School
of
Public
Health
and
Health
Systems.
“But
maybe
we
shouldn’t
just
focus
on
the
objective
components
of
a
patient’s
health
status.
It
turns
out
that
there
is
some
added
predictive
value
to
including
nursing
notes
as
opposed
to
excluding
them.”
The
researchers
used
the
large
publicly
available
intensive
care
unit
(ICU)
database,
Medical
Information
Mart
for
Intensive
Care
III,
containing
patient
data
between
2001
and
2012.
After
some
inclusion
and
exclusion
criteria
were
considered,
such
as
the
need
for
at
least
one
nursing
note
for
a
given
patient,
the
dataset
used
in
the
analysis
included
details
about
more
than
27,000
patients,
as
well
as
the
nursing
notes.
The
researchers
applied
an
open-source
sentiment
analysis
algorithm
to
extract
adjectives
in
the
text
to
establish
whether
it
is
a
positive,
neutral
or
negative
statement.
A
multiple
logistic
regression
model
was
then
fit
to
the
data
to
show
a
relationship
between
the
measured
sentiment
and
30-day
mortality
while
controlling
for
gender,
type
of
ICU,
and
simplified
acute
physiology
score.
The
sentiment
analysis
provided
a
noticeable
improvement
for
predicting
30-day
mortality
in
the
multiple
logistic
regression
model
for
this
group
of
patients.
There
was
also
a
clear
difference
between
the
patients
with
the
most
positive
messages
who
experienced
the
highest
survival
rates
and
the
patients
with
the
most
negative
messages
who
experienced
the
lowest
survival
rates.
“Mortality
is
not
the
only
outcome
that
nursing
notes
could
potentially
predict,”
said
Dubin.
“They
might
also
be
used
to
predict
readmission,
or
recovery
from
infection
while
in
the
ICU.”
The
study,
Sentiment
in
nursing
notes
as
an
indicator
of
out-of-hospital
mortality
in
intensive
care
patients,
co-authored
by
Dubin
and
his
collaborators,
Ian
Waudby-Smith,
Nam
Tran,
and
Joon
Lee,
all
of
the
University
of
Waterloo,
was
published
recently
in
the
journal PLoS
ONE.
Monday, July 16, 2018