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A cognitive model of medical record coding : implications for understanding inter-rater agreement.
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A cognitive model of medical record coding : implications for understanding inter-rater agreement.
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http://www.ohsu.edu/xd/education/library/services/theses-dissertations/rights-statement.cfm
Title
A
cognitive
model
of
medical
record
coding
:
implications
for
understanding
inter-rater
agreement
.
Creator.PersonalName
Campbell
,
Emily
M
.
Thesis.Degree
Ph.D.
Thesis.Major
Biomedical Informatics
Thesis.DateDegreeAwarded
July
2009
Institution
Oregon Health & Science University
School
School of Medicine
Department
Dept. of Medical Informatics and Clinical Epidemiology
Thesis.Advisor/Mentor
Cohen, Aaron M.
Thesis.Committee
Chapman, Wendy Webber
Hazlehurst, Brian L.
Sittig, Dean F.
Stibolt, Thomas B.
Subject.MeSH
Cognition
Information Systems
Call Number
Q171 C187 2009
Description.Abstract
Objective
This
study
evaluated
the
level
of
agreement
between
clinicians
(experts)
and
nonclinicians
(lay
persons)
when
answering
questions
and
selecting
supporting
text
from
ambulatory
care
encounter
notes
. The
study
hypothesized
that
1)
clinicians
would
agree
more
often
than
non-clinicians
across
all
documents
and
2)
agreement
would be
higher
for
both
groups
when
subjects
were
asked
to
find
explicit
text
in
documents
than
when
the
subjects
were
asked
to
draw
inferences
from the
text
. The
study
was
designed
to
shed
light
on the
causes
of
disagreement
among
coders
of
clinical
documents
.
Methods
Eight
clinical
experts
and
eight
non-clinicians
reviewed
58
clinical
encounter
notes
,
answered
questions
about
the
notes
,
highlighted
text
in
support
of
answers
, and
provided
comments
about
the
reasoning
behind
the
answers
and/or
text
selections
.
Study
subjects
interacted
with a
web-based
data
collection
tool
that
displayed
the
documents
and
collected
user
input
. The
data
were
analyzed
using
quantitative
measures
of
agreement
for
question
answers
and
selected
text
as
well
as
qualitative
methods
for
content
analysis
of the
comments
data
.
Results
The
quantitative
analysis
revealed
support
for
Hypothesis
#1
though
not for
Hypothesis
#2
,
likely
due
to
confounders
in
study
design
.
However
, the
qualitative
analysis
provided
important
information
about
how
subjects
search
for
information
within
clinical
records
and
attempt
to
resolve
ambiguity
,
when
present
.
Five
general
approaches
emerged
from the
content
analysis
:
1)
Explicit
statements
are
best
, if
found
, and
lead
to the
highest
agreement
among
subjects
2)
all
subjects
utilize
ad
hoc
heuristics
based
on the
available
data
to
reach
conclusions
,
3)
poor
temporal
specificity
creates
ambiguity
,
4)
exceptions
to
common
clinical
presentations
cause
confusion
among
all
codes
, and
5)
some
ambiguity
is
irresolvable
post
hoc
.
Additionally
all
subjects
in this
study
were
able
to
identify
relevant
information
in
response
to
questions
,
regardless
of
clinical
training
.
Finally
,
subjects
appeared
to
disagree
for
predominantly
non-clinical
reasons
.
Conclusions
The
results
suggest
that there
is
significant
work
to
do
to
mitigate
or
eliminate
some
of the
causes
of
data
ambiguity
in
clinical
information
systems
(CIS)
. This
work
involves
improving
general
cognition
support
(e.g.
,
rendering
collected
data
properly
contextualized
with
other
,
available
information)
,
eliminating
the
use
of
secondary
information
(such
as
ICD-9
codes
as
proxies
for
problem
lists)
in the
clinical
record
, and
building
heuristics
to
identify
points
of
ambiguity
for the
clinician
to
resolve
during
a
clinical
encounter
.
Computational
support
to
reduce
ambiguity
may
help
reduce
the
introduction
and
proliferation
of
ambiguity
in the
medical
record
,
increasing
the
likelihood
of
higher
inter-rater
agreement
among
coders
.
Language
eng
Type
Text
Format.Use
Needs Adobe Acrobat to view
Format.FileSize
2268397 Bytes
OCLC number
436774277
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