Deleted Journal,
Год журнала:
2024,
Номер
3, С. 492 - 492
Опубликована: Дек. 31, 2024
Modern
healthcare
systems
now
strongly
rely
on
digital
health
communication
to
get
patients
more
engaged
in
their
treatment
and
assist
them
stay
with
prescriptions.
Healthcare
professionals
may
have
tailored
continuous
interactions
since
so
many
individuals
use
mobile
applications,
telemedicine
systems,
data.
With
an
eye
how
technology-based
solutions
can
enable
follow
regimens
for
chronic
illnesses
preventative
care,
this
paper
investigates
influences
patient
engagement
commitment.
This
examines
well
various
technologies
text
notes,
video
chats,
real-time
tracking
help
medical
interact
one
another.
The
research
also
successfully
treatments
as
behaviour,
drive,
overall
pleasure
regard
care.
uses
a
lot
of
current
research,
polls,
case
studies
find
the
main
things
that
make
work
healthcare.
These
are
ease
use,
accessibility,
perceived
value,
trust
technology.
results
show
makes
interested
by
giving
personalised
material,
letting
connect
at
right
time,
chances
learn.
Digital
platforms
been
shown
people
stick
reminding
them,
progress,
workers
offer
support
when
they
used
plans.
Even
though
there
benefits,
still
big
problems
need
be
fixed,
like
not
knowing
technology,
worries
about
privacy,
unequal
access
tools.
The
advancement
of
patient
scheduling
techniques
plays
a
crucial
role
in
cost
optimization
and
enhancing
the
flow
patients.
Efficient
ensures
timely
allocation
resources
treatment,
leading
to
improved
resource
utilization
minimized
waiting
times.
dynamic
unpredictable
nature
healthcare
system
introduces
uncertainty,
making
it
essential
address
this
factor
when
implementing
processes
for
real-world
problems.
In
recent
years,
there
have
been
many
new
ways
implement
advance
methods
hospitals
make
sure
are
used
with
optimum
utilization.
Various
isolated
because
they
solve
each
problem
independently.
Combining
two
or
more
can
be
beneficial
utilize
their
advantages
collectively.
This
chapter
provides
an
overview
latest
scheduling,
specifically
emphasizing
on
admission
nurse
operating
room
along
recovery
ICU
while
considering
both
scenarios
without
uncertainty.
purpose
is
assist
researchers
by
highlighting
developments
from
previous
literature
understanding
trends
future
directions.
Abstract
Background
In
April
2021,
the
province
of
Ontario,
Canada,
was
at
peak
its
third
wave
COVID-19
pandemic.
Intensive
Care
Unit
(ICU)
capacity
in
Toronto
metropolitan
area
insufficient
to
handle
local
COVID
patients.
As
a
result,
some
patients
from
were
transferred
other
regions.
Methods
A
spreadsheet-based
Monte
Carlo
simulation
tool
built
help
large
tertiary
hospital
plan
and
make
informed
decisions
about
number
transfer
it
could
accept
hospitals.
The
model
implemented
Microsoft
Excel
enable
be
widely
distributed
easily
used.
estimates
probability
that
each
ward
will
overcapacity
percentiles
utilization
daily
for
one-week
planning
horizon.
Results
used
May
2021
February
2022
support
ability
transfers
also
ensure
adequate
inpatient
bed
human
resources
response
various
COVID-related
scenarios,
such
as
changes
admission
rates,
managing
impact
intra-hospital
outbreaks
balancing
with
planned
activity.
Conclusions
Coordination
between
hospitals
necessary
due
high
stress
on
health
care
system.
simple
can
understand
patient
improve
confidence
leaders
when
making
decisions.
helpful
investigating
operational
scenarios
may
preparing
future
or
public
emergencies.
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Июнь 20, 2024
Abstract
The
Covid-19
pandemic
was
an
unforeseen
threat
to
human
survival,
and
the
efficiency
of
health
sector
faced
a
severe
challenge.
lack
hospital
beds
one
most
critical
concerns,
optimizing
capacity
considered
key
issues.
Due
ageing
population
occasional
occurrence
environmental
crises,
demand
for
services
need
improved
planning
administration
are
increasing
daily.
Therefore,
optimal
allocation
resources,
particularly
number
beds,
essential
criterion
medical
center’s
capacity,
can
substantially
reduce
patient
waiting
time
treatment
costs
improve
services.
An
ideal
multi-objective
integer
programming
problem
is
presented
in
this
study
reducing
length
stay
stay.
also
considers
constraints
relating
circumstances,
given
Corona's
prevalence.
Moreover,
answer
obtained
using
simulation
model,
mathematical
optimization,
simulation-based
optimization
approach.
For
purpose,
modelling
used
minimize
patients'
time,
hospitalizations,
maintenance
existing
purchasing
new
bed.
Following
that,
real-world
conditions
were
introduced
into
model
information
acquired
from
month
hospitalization
patients
during
Coronavirus
outbreak
at
Imam
Hussein
Hospital
Tehran.
After
comparing
simulated
models,
OptQuest
technique
revealed
beds.
