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An English abstract of the following chapters in Ozcan (2nd ed.): 3, 9, 10, 12, 13, 14 and 15

Institution
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Institution
Study
Course

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Summarized whole book?
No
Which chapters are summarized?
Hoofdstukken 3, 9, 10, 12, 13, 14 en 15
Uploaded on
March 5, 2016
Number of pages
22
Written in
2015/2016
Type
Summary

Subjects

Content preview

Summary

Quantitive
methods
for
OM
in
healthcare

Ozcan
Chapter
3

Decision
making
in
health
care
facilities

Decision
making:
the
act
of
selecting
a
course
of
action
from
among
alternatives.



Making
and
implementing
decisions
is
a
central
function
of
management,
and
it
is
where

health
care
managers
concentrate
their
efforts.
Success
depends
on
whether
or
not
enough

right
decisions
are
both
made
and
implemented.
A
plan
of
action
that
improves
the
chances

of
a
successful
decision
will
include
the
following
steps:

1. Identify
the
problem
and
its
nature
(most
important
step)

2. Specify
objectives
and
decision
criteria
(costs,
profits,
return
on
investment,

increased
productivity,
risk,
company
image,
and
impact
on
demand)

3. Develop
alternatives

4. Analyze
and
compare
the
alternatives

5. Select
the
best
alternative
(this
may
be
to
do
nothing
at
all).

6. Implement
the
selected
alternative

7. Control
and
monitor
the
results



A
mathematical
model
is
an
abstract
representation
of
some
real-­‐world
health
care
process,

system,
or
subsystems,
which
can
help
the
manager
by
analysing
and
comparing

alternatives.
At
the
end,
the
astute
health
care
manager
should
ask
the
following
question:

which
alternative
best
fits
my
established
objectives
within
reasonable
time
and
cost

constraints
and
ill
benefit
the
health
care
organization
as
a
whole?



Poor
decision,
because:

-­‐ Managers
want
to
make
quick
decisions

o They
tend
to
assume
that
previous
successes
guarantee
success
in
the

current
situation

-­‐ Managers
have
trouble
making
decisions
and
wait
far
too
long
before
making
one



Managers
facing
a
decision
must
deal
with
(phenomenon
in
poor
decision
making):

-­‐ Bounded
rationality:
limits
imposed
on
decision
making
by
costs,
human
abilities

and
errors,
time
technology
and
the
tractability
of
data.

The
manager
must
contend

with
the
recognition
that
it
is
not
always
possible
to
come
up
with
a
decision
that

will
have
the
very
best
possible
outcome.


-­‐ Sub-­‐optimization:
in
a
highly
competitive
environment,
decisions
are
often

departmentalized
as
separate
organizational
units
compete
for
scarce
resources.

Individual
departments
often
seek
solutions
that
benefit
their
own
department
but

not
necessarily
the
health
care
organization
as
a
whole.




The
level
of
decisions
and
the
settings
in
which
managers
must
make
decisions
are
classified

according
to:

-­‐ The
strategic
level
of
the
decision,
which
can
vary
from
low
to
high
depending
on

the
situation.
The
management
level
making
the
decisions
rises
with
the
strategic

importance
of
these
decisions,
usually
top-­‐level
managers
make
strategic
decisions.


-­‐ The
level
of
certainty
surrounding
the
situation
or
states
of
nature.

o Uncertainty:
in
general,
strategic
in
nature
and
occur
at
top
levels.




1


, § Uncertainty
exists
in
any
scenario
when
insufficient
information

makes
it
impossible
to
assess
the
likelihood
of
possible
future

events.


o Risk:
can
occur
at
any
management
level

§ Risk
exists
when
you
do
not
know
which
events
will
occur
but
can

estimate
the
probability
that
any
one
state
will
occur.




Decision-­‐making
under
uncertainty:


-­‐ Maximin
(pessimistic
strategy):
this
strategy
identifies
the
worst
possible
scenario

for
each
alternative,
and
aims
to
select
the
alternative
that
will
give
the
largest

payoff
in
the
worst
circumstances.

-­‐ Maximax
(optimistic
strategy):
this
strategy
identifies
the
alternative
with
the
best

payoff
(highest
maximum
return).

-­‐ Laplace:
this
strategy
calculates
the
average
payoff
for
each
alternative
and
selects

the
one
with
the
highest
average.

-­‐ Minimax
regret:
this
strategy
calculates
the
worst
regret
(or
opportunity
loss)
for

each
alternative
and
chooses
the
one
that
yields
the
least
regret,
or
that
the
health

care
manager
can
“live
with”
best.

-­‐ Hurwitz
criterion:
this
strategy
allows
for
adjusted
weighting
between
maximin
and

maximax,
or
allows
the
health
care
manager
to
choose
a
platform
on
the
continuum

of
pessimist
versus
optimist.



Payoff
table:
a
tool
that
is
frequently
used
to
select
the
best
alternative
given
different

possible
outcomes
under
various
possible
conditions
(states
of
nature).
A
payoff
table
can

be
constructed
using
the
outcome
(profit,
revenue,
cost)
for
alternative
I
(Ai),
and
state
of

nature
j
(Sj)
as
Oij.






Hurwitz
case:
health
care
manager’s
behaviour
can
fluctuate
from
pessimism
to
optimism,

depending
upon
recent
experiences
with
similar
situations.
Hurwitz
optimism
weight
would

vary
0

α

1.
When
α
=
1,the
decision
becomes
optimistic
and
when
α
=
0,
the
decision
is

pessimistic.
The
manager
would
scan
through
each
row
of
the
payoff
table
and
find
the
best

outcome
and
the
worst
outcome
for
each
alternative.
Then
for
each
alternative
he
would

calculate
Hurwitz
Value
(HV)
as
follows:

𝐻𝑉 𝐴! =∝∗ 𝑅𝑜𝑤  𝑚𝑎𝑥𝑖𝑚𝑢𝑚 + 1−∝ ∗ (𝑅𝑜𝑤  𝑚𝑖𝑛𝑖𝑚𝑢𝑚)

Then,
the
alternative
with
the
highest
payoff
can
be
chosen.




Minimax
regret
case:


Regret:
refers
to
the
opportunity
loss
that
occurs
when
an
alternative
is
chosen
and
a

particular
state
of
nature
occurs
à
the
difference
between
the
best
possible
outcome
under

a
state
of
nature
and
the
actual
outcome
from
choosing
a
particular
alternative.


The
manager
must
develop
a
regret
table,
which
converts
the
payoff
table
to
opportunity

losses.


𝑅𝑒𝑔𝑟𝑒𝑡   𝑅!" = 𝑚𝑎𝑥𝑖𝑚𝑢𝑚  𝑝𝑎𝑦𝑜𝑓𝑓  𝑓𝑜𝑟  𝑐𝑜𝑙𝑢𝑚𝑛  𝑗 −   𝑝𝑎𝑦𝑜𝑓𝑓!"

If
this
table
is
completed,
the
minimax
rule
can
be
applied.
Collect
al
worst
scenarios
and

choose
the
best
(lowest
regret).




Laplace
case:
principal
of
“insufficient
reason”.
The
first
way
of
introducing
the
probability

concept
into
decision-­‐making.
Since
under
uncertainty
no
known
probabilities
exist,
the

health
care
manger
can
assume
equally
likely
probabilities
for
each
state
of
nature.
For
n

states
of
nature,
the
probability
for
each
state
under
the
Laplace
strategy
would
be
1/n.


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