n this wee
k's refl
e
ctio
n
repo
r
t I will
di
s
cuss technology diffusion, S
-
Curves and innovation
decision p
roce
s
s. I will use t
he
health
care
i
ndustry as an example.
Ou
r
healthcare system is ever
e
v
ol
v
ing - ne
w
t
ec
hn
ologies, insurance mode
l
s
,
and information systems are shaping the s
y
stem
on a dail
y
b
as
i
s. Despites these changes and
the hu
g
e healthcare expenditu
r
e
s (
16
o
f
GDP
i
n
A
m
e
rica c
o
mp
are
d
to 8 in United Kingdom), A
mericans
a
re comparati
v
el
y
not an
y
healthier
than
ci
tiz
e
n
s
i
n most other developed nations (M
er
s
on
,
Blac
k,
&
Mill
s
,
2
01
2)
.
T
he disconnect
bet
w
een in
ves
t
me
nt
s in technology and he
alth outcomes is a concern of us all
.
It makes as
question
tec
hn
ology diffusion within the he
al
t
hcar
e sy
stem: are investments in health s
y
stem
bein
g s
pen
t efficie
n
t
l
y? Are consume
r
s really
resistant to changes that benefit their health
?
Or
are th
e
re i
ssues w
i
th technology dif
f
usion as a
prac
t
ice
.
Di
f
fusion
is the process b
y
which an innovatio
n is spread through a population. Ironicall
y,
people and i
ns
t
i
tut
ions, generall
y,
do not like
c
h
ange. Chan
g
e is
v
iewed as pa
i
nful
,
difficult and
time
s
creatin
g
u
ncer
t
ai
n
ties
.
Because of this, a
nd for the healthcare industr
y
,
hu
g
e amount
s
of
resources
are devote
d
e
i
ther to promoting innova
ti
o
ns
(f
or example
,
selling the
l
atest drug
,
imaging
system
,
me
d
ic
a
l device etc.) or to p
r
ev
en
t
in
g
inno
v
ations from disruptin
g
the status quo
.
Althou
g
h m
any s
u
ccessful healthcare in
n
ova
ti
o
ns
a
re aimed at making people healthier
,
at
relati
v
el
y sma
ll
er increases in costs
,
IT usage i
n healthcare ha
s
alwa
y
s lagged other industries
-
E
RH ar
e
a
goo
d
example. Adoption of E
R
H w
a
s s
lo
w. L
iterature on technolo
gy
diffusion states
that
s
ucce
ssf
u
l im
p
lementation is influenced by
the c
o
mpatibi
l
it
y
and comple
x
it
y
of the
inno
v
ation
,
o
r
ganizatio
n
al context
,
and t
h
e c
h
a
racte
r
istics
of
the implementation strateg
y (
Cain
M
,
&
Mittm
an
,
2002;
R
ogers, 1995
)
. People r
e
s
pond to th
e
se factors differentl
y
resulting in an
S-shaped cu
rve i
llu
s
t
ra
t
ion of the adoption p
roces
s
.
The S-cur
ve m
o
de
l
shows that any innovation
i
s f
i
rs
t
a
dopted b
y
a few people
/
or
g
anizations and
as more u
se
i
t
,
an
d
conf
i
dence is built around
the technolo
gy,
other will begin to use it
.
Because
of the inher
ent
u
ncer
t
ainty to new innovations, t
he decision to adopt an inno
v
ation takes time
.
Ho
wev
er
, "on
c
e the d
i
ffusion reaches a level of
critical ma
s
s
,
it proceeds rapidl
y
.
Ev
entuall
y
a
point i
s
r
eache
d
where the population is less lik
e
ly
to
a
dopt th
e
inno
v
ation
,
and spread slow
s
down.
T
h
e S
-
c
ur
ve implies a hierarchy of a
dop
t
er
s
,
st
a
rting with inno
v
ators
,
earl
y
adop.
n this weeks reflection report I will discuss t.docx
1. n this wee
k's refl
e
ctio
n
repo
r
t I will
di
s
cuss technology diffusion, S
-
Curves and innovation
decision p
roce
s
s. I will use t
he
health
care
i
ndustry as an example.
Ou
r
healthcare system is ever
e
v
ol
v
ing - ne
w
t
ec
hn
ologies, insurance mode
2. l
s
,
and information systems are shaping the s
y
stem
on a dail
y
b
as
i
s. Despites these changes and
the hu
g
e healthcare expenditu
r
e
s (
16
o
f
GDP
i
n
A
m
e
rica c
o
mp
are
d
to 8 in United Kingdom), A
mericans
a
re comparati
4. nt
s in technology and he
alth outcomes is a concern of us all
.
It makes as
question
tec
hn
ology diffusion within the he
al
t
hcar
e sy
stem: are investments in health s
y
stem
bein
g s
pen
t efficie
n
t
l
y? Are consume
r
s really
resistant to changes that benefit their health
?
Or
are th
e
re i
ssues w
i
th technology dif
f
5. usion as a
prac
t
ice
.
Di
f
fusion
is the process b
y
which an innovatio
n is spread through a population. Ironicall
y,
people and i
ns
t
i
tut
ions, generall
y,
do not like
c
h
ange. Chan
g
e is
v
iewed as pa
i
nful
,
difficult and
time
s
creatin
g
6. u
ncer
t
ai
n
ties
.
Because of this, a
nd for the healthcare industr
y
,
hu
g
e amount
s
of
resources
are devote
d
e
i
ther to promoting innova
ti
o
ns
(f
or example
,
selling the
l
atest drug
,
imaging
system
,
me
7. d
ic
a
l device etc.) or to p
r
ev
en
t
in
g
inno
v
ations from disruptin
g
the status quo
.
Althou
g
h m
any s
u
ccessful healthcare in
n
ova
ti
o
ns
a
re aimed at making people healthier
,
at
relati
v
el
y sma
ll
8. er increases in costs
,
IT usage i
n healthcare ha
s
alwa
y
s lagged other industries
-
E
RH ar
e
a
goo
d
example. Adoption of E
R
H w
a
s s
lo
w. L
iterature on technolo
gy
diffusion states
that
s
ucce
ssf
u
l im
p
lementation is influenced by
the c
o
mpatibi
10. 2002;
R
ogers, 1995
)
. People r
e
s
pond to th
e
se factors differentl
y
resulting in an
S-shaped cu
rve i
llu
s
t
ra
t
ion of the adoption p
roces
s
.
The S-cur
ve m
o
de
l
shows that any innovation
i
s f
i
rs
t
a
dopted b
11. y
a few people
/
or
g
anizations and
as more u
se
i
t
,
an
d
conf
i
dence is built around
the technolo
gy,
other will begin to use it
.
Because
of the inher
ent
u
ncer
t
ainty to new innovations, t
he decision to adopt an inno
v
ation takes time
.
Ho
wev
er
, "on
c
12. e the d
i
ffusion reaches a level of
critical ma
s
s
,
it proceeds rapidl
y
.
Ev
entuall
y
a
point i
s
r
eache
d
where the population is less lik
e
ly
to
a
dopt th
e
inno
v
ation
,
and spread slow
s
down.
T
h
e S
13. -
c
ur
ve implies a hierarchy of a
dop
t
er
s
,
st
a
rting with inno
v
ators
,
earl
y
adopters
,
earl
y
majorit
y,
l
ate
m
aj
o
rity and laggards
(
Rogers
,
1
995
).
In other
14. w
ords the S
-
curve explains the
inno
v
ation-d
ec
i
s
i
on p
r
ocess
:
the process throu
g
h
which an indi
v
idual
/
organization passes
throu
g
h
f
r
om w
h
e
n
they gain knowledge of an i
nno
v
ation
15. ,
to forming an attitude
,
t
o
the decision
to accept o
r re
j
ect the i
n
no
v
ation
,
to implem
en
t
ation
,
up to
t
he confirmation o
f
the decision.
Thu
s i
t i
s i
mpor
ta
n
t for innovators to understan
d the
f
ac
16. t
or
s
that influence this decision process
and design
i
n
fo
rmati
on and adoption messag
es
t
hat reduce the
l
e
v
el of uncertaint
y
about the
inno
v
ation.
Cain M
,
&
Mi
tt
m
a
n
,
R
.
(2002
)
.
17. Diffusion of Innovatio
n
i
n He
a
lthcare
.
California HealthCare
F
ound
a
ti
o
n
.
Mer
s
on
,
M
.
H.
;
Bl
ack,
R.E
.;
&
Mills
,
A.
1
.
(2012)
Glo
b
