Mastering healthcare data governance with data lineage

The
healthcare
industry
faces
arguably
the
highest
stakes
when
it
comes
to
data
governance.
For
starters,
healthcare
organizations
constantly
encounter
vast
(and
ever-increasing)
amounts
of
highly
regulated
personal
data.

The
impact
of
healthcare
data
usage
on
people’s
lives
lies
at
the
heart
of
why
data
governance
in
healthcare
is
so
crucial.In
healthcare,
managing
the
accuracy,
quality
and
integrity
of
data
is
the
focus
of
data
governance.
When
healthcare
organizations
excel
at
this,
it
can
lead
to
better
clinical
decision-making,
improved
patient
outcomes
and
prevention
of
medical
errors. 

Despite
this,
many
healthcare
organizations
face
challenges.
Healthcare
organizations
need
a
strong
data
governance
framework
to
help
ensure
compliance
with
regulations
like
the Health
Insurance
Portability
and
Accountability
Act
of
1996
(HIPAA)
in
the
US
and
the
General
Data
Protection
Regulation
(GDPR)
in
the
EU.

How
can
a
healthcare
provider
improve
its
data
governance
strategy,
especially
considering
the
ripple
effect
of
small
changes? 
Data
lineage
can
help.With
data
lineage,
your
team
establishes
a
strong
data
governance
strategy,
enabling
them
to
gain
full
control
of
your healthcare
data pipeline.

Understanding
data
governance
in
healthcare

The
need
for
a
strong
data
governance
framework
is
undeniable
in
any
highly-regulated
industry,
but
the
healthcare
industry
is
unique
because
it
collects
and
processes
massive
amounts
of
personal
data
to
make
informed
decisions
about
patient
care.
One
broken
or
incomplete
piece
of
data
can
trigger
not
only
noncompliance
and
audit
issues
but
also
harm
real
people.
For
example:

• Healthcare
  providers
  regularly
  rely
  on
  medical
  records
  to
  diagnose
  and
  establish
  treatment
  plans
  for
  patients.
  Inaccuracies
  in
  these
  medical
  records
  leading
  to
  misdiagnoses,
  medication
  errors
  or
  delayed
  care
  can
  have
  serious
  consequences.
• Inaccuracies
  might
  also
  lead
  to
  more
  delays
  or
  complications
  with
  insurance
  coverage. 
• Healthcare
  organizations
  must
  adhere
  to
  data
  privacy
  regulations
  like
  HIPAA
  and
  GDPR.
  Noncompliance
  with
  these
  laws
  is
  costly
  and
  can
  damage
  your
  reputation,
  besides
  posing
  a
  danger
  to
  patients
  and
  practitioners
  when
  data
  breaches
  occur.

Conversely,
confidence
in
the
accuracy
and
consistency
of
your
data
can
minimize
the
risk
of
adverse
health
outcomes,
rather
than
merely
reacting
to
or
causing
them. Also,
using
predictive
analytics
can
help
identify
trends,
patterns
and
potential
future
health
risks
in
your
patients.

It’s
worth
noting
that
most electronic
health
records
(EHR)
systems offer
predictive
analytics
capabilities.
The
accuracy
of
these
analytics
is
limited
by
the
accuracy
of
the
data
used. 

Thus,
having
a
comprehensive
understanding
of
the
data
environment
and
a
clear
chain
of
custody
becomes
imperative.
Detecting
leaks
and
pressure
points
depends
on
implementing
a
strong
data
governance
strategy,
with
data
lineage
as
a
critical
component.

Challenges
in
data
governance
for
healthcare
and
how
data
lineage
can
help

Data
governance
can
help
healthcare
organizations
maximize
the
accuracy
and
security
of
their
data
assets.
At
the
same
time,
implementing
a
data
governance
framework
poses
some
challenges,
such
as data
quality issues,
data
silos
security
and
privacy
concerns. 

1.
Data
quality
issues

Positive
business
decisions
and
outcomes
rely
on
trustworthy,
high-quality
data.
However, healthcare
facilities
continue
to
face
data
quality issues
despite
the
best
efforts
of
business
leaders,
primarily
due
to
the
sheer
number
of
people
inputting
data
and
the
high-pressure
situations
in
which
data
entry
often
occurs.

A study
conducted
by
the
Journal
of
the
American
Medical
Association
(JAMA) revealed
that
errors
were
found
in
the
records
of
one-fifth
of
patients
with
access
to
ambulatory
care
notes.
Among
those
patients,
21%
identified
the
errors
as
critical,
with
common
issues
including
diagnostic
errors,
medication
data
errors
and
incomplete
or
inaccurate
EHR
data
conversions.
These
errors
are
crucial
and
can
occur
daily. To
prevent
these
errors,
it’s
critical
for
data
flows
to
be
mapped
out
and
for
issues
with
data
quality
to
be
flagged
by
using
root-cause
analysis,
thereby
reducing
the
impact
on
patients.

2.
Data
silos

In
the
healthcare
industry,
where
an
estimated 30%
of
the
world’s
total
data
is
generated,
patient
data
often
remains
unstructured
and
scattered
across
disparate
systems.
The
consequence?
An
incomplete
picture
of
patient
health
and
multiple
sources
of
truth
prevents
you
from
achieving the

benefits
of
data
visibility such
as
informed
patient
care.
Issues
with
compliance
and
audit
conduct
also
arise
due
to
these
scattered
data
sources.

The
solution
lies
in
the
ability
to
visualize
patient
data
from
different
sources
in
one
place.
That’s
exactly
what
enterprise-wide
data
lineage
does.
Data
lineage
extends
throughout
your
data
environment
to
create
a
comprehensive
map
of
all
your
data
flows
and
dependencies,
eliminating
data
silos
effectively.

However,
not
all
data
lineage
solutions
can
visualize
data
from
different
silos.
Some
platforms
only
allow
you
to
see
data
stored
within
their
specific
catalog.
Opting
for
a
catalog-agnostic
solution
helps
you
address
this
issue. 

 3.
Security
concerns
and
chain
of
custody

Healthcare
organizations
are
in
a
unique
position
because
both
depend
on
cross-departmental
information
sharing
to
facilitate
patient
care
and
are
bound
by
strict
regulations
to
help
ensure
secure
data
transmission.

As
part
of
both HIPAA
and
GDPR
compliance,
healthcare
organizations
need
to
provide
auditors
with
details
regarding
the
chain
of
custody
of
patient
records.
This
includes
information
on
who
accessed
the
records
and
the
time
and
location
of
access.
Establishing
a
chain
of
custody
for
data
stored
in
an
EHR
system
accessible
across
several
devices
within
a
medical
facility
can
be
laborious
and
time-intensive,
especially
when
dealing
with
so
many
records
that
exist
in
a
paper
format
or
have
been
manually
entered
or
scanned. 

Data
lineage
significantly
reduces
the
amount
of
effort
needed
to
establish
a
chain
of
custody
within healthcare
information
systems. By
mapping
data
flows,
you
can
trace
the
journey
of
your
data
backward
to
see
where
and
when
it
was
changed
in
your
systems.
Combined
with
your
governance
efforts
that
establish
the
meaning,
quality
and
stewardship
of
the
data
stores
in
this
chain
of
custody,
you
can
deliver
the
crucial
data
pipeline
information
required
by
your
auditors.

Better
patient
care
and
predictive
analytics

With
high-quality
data,
you
can
provide
well-informed,
cross-collaborative
and
personalized
patient
care.
You
also
place
deeper
trust
in
the
predictive
analytics
within
your
EHR
system
to
predict
patient
conditions,
disease
progression,
hospital
overstays,
readmissions,
and
more.
All
this
relies
on
reliable
data
and
requires
data
lineage
for
governance.

Enhanced
regulatory
compliance

If
you’re
struggling
with
data
silos,
data
quality
or
proving
chain
of
custody,
you
might
also
be
finding
it
difficult
to
establish
and
prove
compliance
with
healthcare-related
regulations
like
HIPAA
and
GDPR.
Data
lineage
can
help
you
establish
your
chain
of
information
flow
and
dependencies
to
auditors
clearly
and
quickly,
which
is
key
to
compliance. 

Increased
data
security
and
privacy

In
the
healthcare
industry,
data
privacy
is
integral.
When
data
lineage
creates
a
map
of
your
data
environment,
it
does
so
without
sharing
or
processing
any
private
information.
Instead,
it
uses active
metadata.
That
means
that
you
can
create
a
strong
data
governance
framework
without
sacrificing
patient
privacy.

Improved
operational
efficiency
and
cost
savings 

Mapping
out
data
flows
manually
is
a
time
and
resource-intensive
process,
especially
in
the
highly-complex
healthcare
industry.
Among
the
top
advantages
of
automated
data
lineage
for
data
governance
are
its
operational
efficiency
and
cost-effectiveness.
You
can
save
money
and
time
on
labor
costs
and
focus
your
efforts
on
what
matters
most
to
your
organization.

We’re
90%
faster

“Our
ETL
teams
can
identify
the
impacts
of
planned
ETL
process
changes
90%
faster
than
before.”
Robert
D,
BI
Team
Leader
at
GEMU

90%
increase
in
analyzing
source
system
changes

“Effort
for
analyzing
the
impact
of
a
source
system
change
has
decreased
by
at
least
90%,
from
hours
to
minutes
(or
seconds).”
Michael
L.,
BI
Manager
at
Schumacher
Clinical

Data
governance
and
compliance 

In
the
healthcare
industry,
ensuring
compliance
with
regulations
like
HIPAA
and
GDPR
is
another
important
piece
of
data
governance,
crucial
for
both
protecting
patient
privacy
and
facilitating
secure
information-sharing
critical
for
the
highest
level
of
patient
care.

Some
healthcare
organizations
today
still
struggle
to maintain
compliance
with
HIPAA
and
GDPR.
Meanwhile,
the
world’s
regulatory
landscape
is
becoming
increasingly
complex.
In
fact,
Gartner®
predicts
that
by
the
end
of
2024, 75%
of
the
world
will
have
its
data
protected under
modern
privacy
regulations.
Given
that
the
healthcare
industry
is
generating
new
regulated
patient
data
by
the
second,
now
is
the
time
to
kickstart
an
effective
data
governance
strategy. 

It’s
worth
noting
that
these
regulations
don’t
just
apply
to
patient
care-focused
organizations.
Nearly
every
area
of
healthcare
processed
large
quantities
of
protected
data,
including:

• Biotechnology
  companies
• Health
  insurance
  providers
• Medical
  device
  manufacturers
• Pharmaceutical
  companies

With
data
lineage,
you
get
a
detailed
map
of
your
data
flows
that
help
ensure
that
you
are
processing
and
securing
data
within
the
strict
requirements
of
regulatory
frameworks
like
HIPAA
and
GDPR. You
can
also
more
easily
prove
the
chain
of
custody
to
auditors,
who
will
need
to
see
who
has
had
access
to
your
regulated
data
assets
and
apply
stricter
controls
around
who
has
access.

Next
steps
to
increase
data
security
and
enhance
compliance

The
modern
healthcare
industry
is
undeniable
in
its
complexity, with
the
emergence
of
EHR
systems,
the
proliferation
of healthcare
data,
and
an
increasingly
complex
regulatory
landscape
contributing
to
this
complexity.

To
keep
up,
healthcare
companies
today
need
to
implement
data
governance.
A
strong
data
governance
framework
helps
ensure
that
you
can
verify
that
the
data
you’re
collecting,
processing
and
using
is
accurate,
consistent
and
dependable.
Without
it,
you
risk
making
poorly
informed
decisions
about
patient
care
based
on
erroneous
data
or
inaccurate
predictive
insights.
These
decisions
can
have
serious
or
even
fatal
outcomes
for
patients.

Data
governance
is
also
integral
when
complying
with
healthcare
data
privacy
regulations
like
HIPAA
and
GDPR.
Any
healthcare
organization
processing
protected
data
needs
to
have
a
data
governance
strategy
in
place
to
remain
compliant
with
these
regulations
and
be
prepared
for
any
new
regulations
that
might
arise. 

Despite
challenges
like
data
quality
issues,
data
silos,
security
concerns
and
proving
chain
of
custody,
there
is
a
solution:
automated
data
lineage. By
using
automated
data
lineage,
your
organization
can
overcome
common
data
governance
barriers,
improve
patient
care,
enhance
regulatory
compliance,
increase
data
security
and
privacy
and
enhance
operational
efficiency
while
reducing
costs. 

Explore
our
automated
data
lineage
solution
for
data
governance
in
healthcare