204 Eu opean Jou nal o Ope a ional Resea ch 61 (1992) 204-214
No h-Holland
A managemen ool o indica o -suppo ed
sys ems: A public heal h se ice applica ion
E. Ca izosa, E. Conde, F.R.
Fe n indez and
J.
Pue o
Depa amen o de Es ad[s ica e In es igaci6n Ope a i a, Uni e sidad de Se illa, Se illa, Spain
Recei ed Ma ch 1991; e ised Sep embe 1991
Abs ac : We de elop a decision-making me hodology o hie a chical s uc u es. I p o ides di e en
decision make s wi h decision-o ien ed in o ma ion based on ob ained sa is ac ion le els. This is specially
con enien o public se ices, whe e he main goal is use 's sa is ac ion. Ou me hodology and i s
associa ed so wa e (INDI) ha e been implemen ed in he Andalusian Heal h Se ice (SAS), suppo ing
esou ce alloca ion decisions in o de o educe he complain s p esen ed agains such an ins i u ion.
Keywo ds: Decision Suppo Sys ems; decision heo y; mul ic i e ia decision making
1. In oduc ion
Any o ganiza ion in a compe i i e ma ke
needs some ools o eac agains unexpec edly
inc easing cos s o dec easing quali y.
This has gi en an impo an ole o he in o -
ma ion depa men : moni o ing he p oduc ion
p ocess h ough in o ma ion sys ems gi es he
manage he ools o compa e he ou pu s wi h
p ese a ge s and check he quali y o hem.
Un il he beginning o he 80s, all ha was
equi ed we e Managemen In o ma ion Sys ems
(MIS), he decisions being ese ed o he man-
age s, wi h he only aid o he epo s gi en by
he MIS. Howe e , he e has been in he las
yea s an inc easing in e es in he de elopmen o
no ma i e decision models, suppo ing he mak-
ing o non-s uc u ed o semi-s uc u ed deci-
sions in o de o sys ema ize he p ocess o con-
inuous imp o emen .
Mos o he e o s ha e been de o ed o he
de elopmen o me hodologies o speci ic deci-
sion si ua ions (Valada es e al., 1986; Boldy,
1987; And eu and Co ominas, 1989; Vla6i6, 1989).
The de elopmen o ou me hodology HIDS
(Hie a chical In o ma ion and Decision Sys em)
and i s associa ed so wa e had as a s a ing poin
a con ac wi h he Se icio Andaluz de Salud
(Andalusian Heal h Se ice), known as SAS.
The e, we had o de elop an in e ac i e sys em
suppo ing decisions abou he alloca ion o e-
sou ces in o de o educe he numbe o com-
plain s in public heal h cen e s.
We ha e de eloped a uni ied decision-making
en i onmen o suppo ing decisions a di e en
le els in any hie a chical s uc u e. This en i on-
men can be seen as a
shell
ha he decision
make s (DMs) use in o de o de elop hei own
DSS p o ile inside he s uc u e.
Ou aim is o gi e all he DMs ex emely
manageable and meaning ul decision-o ien ed in-
o ma ion. The me hodology is based on he anal-
ysis o he sa is ac ion le el ob ained h ough he
ou pu s o he sys em. This sa is ac ion is mea-
su ed by means o obse ed ajec o ies, no mal-
ized using
sa is ac ion unc ions.
This p ocedu e is especially con enien o
public se ices, whe e he main goal is o ob ain a
high le el o use 's sa is ac ion.
This pape is di ided in o ou sec ions. In
Sec ion 2, we desc ibe he model and i s unde ly-
ing hypo heses, he In o ma ion and Decision
P ocesses. In Sec ion 3 we p esen a eal applica-
ion o ou me hodology applied o public heal h
0377-2217/92/$05.00 © 1992 - Else ie Science Publishe s B.V. All igh s ese ed
E. Ca izosa e al. / Managemen ool o indica o -suppo ed sys ems
205
se ices. Sec ion 4 is de o ed o he desc ip ion o
he so wa e a chi ec u e ha has been de el-
oped o he model. The pape ends wi h wo
ma hema ical appendices dealing wi h some as-
pec s o he In o ma ion and Decision P ocesses.
2. The Hie a chical In o ma ion and Decision
Sys em (HIDS)
2.1. The model
The model we p opose is based on a se o
hypo heses we desc ibe below. They do no co e-
spond o heo e ical condi ions, bu appea in
almos any eal la ge-scale in o ma ion-decision
sys em. Due o hei na u e, hese hypo heses a e
classi ied in o h ee g oups:
- S uc u e hypo heses (S).
- Sys em Pa ame e hypo heses (P).
- P ese Ta ge s hypo heses (T).
S1. The sys em can be ep esen ed h ough a
hie a chical s uc u e.
$2. Any elemen in he sys em (DM) occupies
only one place in he s uc u e.
$3. No elemen ac s isola ed om he es .
$4. The e a e wo p eo de s on he s uc u e,
called he Decision ela ion and In o ma ion e-
la ion. Each one is he in e se o he o he .
$5. The e exis s only one maximal elemen o
he Decision ela ion: The Supe Decision Make
(SDM). Fo any DM, he Decision ela ion in-
duces exac ly one chain om he SDM o him.
PI. Any DM a he lowes le el in he hie a -
chy ( e minal DM) is esponsible o a unique
se eice cen e . The pe o mance o such a se ice
is con olled by a s ochas ic p ocess ha depends
on a se o pa ame e s.
T1. The pe o mance quali y o a se ice cen-
e i a ime is a unc ion o a se V~( ) o
nume ical ea u es (which a e pe iodically mea-
su ed), and a se o p ese a ge s.
T2. The sa is ac ion o a e minal DM is he
pe o mance quali y o his associa ed se ice cen-
e . The sa is ac ion o any non- e minal DM a
ime is a unc ion o he sa is ac ion o hose
DMs subo dina ed o him ollowing he Decision
ela ion.
In a na u al way, he hypo heses desc ibed
abo e lead us o a ep esen a ion o he sys em by
means o a ma hema ical s uc u e H =
(N, F, B), whe e:
1) N is he se o all he DMs in he hie a chy
2) F is he Decision ela ion. I (n, m)~F,
we say ha m is subo dina ed o n.
3) B is he In o ma ion ela ion. I (n, m) ~ B,
we say ha n in o ms m.
4) (N, F) is an acyclic connec ed dig aph, wi h
only one DM wi h ze o ank: he Supe Decision
Make (SDM).
5) (N, B) is an acyclic connec ed dig aph, wi h
only one elemen wi h maximal ank: he SDM.
6) (n, m) ~ F i (m, n) ~ B.
No e ha he hypo heses we imposed a e ex-
plici ly used in his o mula ion. In ac , $1 and
$2 jus i y he acyclic g aph s uc u e, $3 he con-
nec edness, and $4 he exis ence o wo g aphs,
one o each di ec ion o low: whe eas he a cs
in (N, F) ep esen in di ec ion in which he
decisions a e ansmi ed, he ones in (N, B)-s a e
he di ec ion o in o ma ion low.
Hypo hesis $5 is aken in o accoun in (4) and
(5); hypo hesis P1 is needed o explain he non-
de e minis ic na u e o he sys ems we a e model-
ing. Finally, he T1 and T2 hypo heses allow he
e alua ion o sys em pe o mance, and cons i u e
he co ne s one o he In o ma ion P ocess we
desc ibe below.
2.2. The In o ma ion P ocess (IP)
E icien managemen needs e y sha p and
belie able knowledge abou sys em pe o mance.
Due o he sys em's na u e, only he DMs in
he lowes le el in he hie a chy ha e di ec ac-
cess o in o ma ion, bu such in o ma ion gi es
only e y pa ial knowledge abou he eal pe o -
mance o he whole sys em.
Howe e , he DMs in he highes le els ( hose
wi h a b oade ac ion ield) no only lack di ec
access o in o ma ion, bu also need mo e gene al
knowledge abou he sys em: as gene al as he
kind o he decisions hey ha e o ake.
Hence, we ha e o ace wo p oblems:
• How should he DMs collec in o ma ion?
• How should such in o ma ion be p ocessed
and sen o DMs in highe le els in he hie a -
chy?
The aim o e e imp o ing he quali y o a
se ice ad ises agains collec ing in o ma ion
abou he se ice h ough me ely desc ip i e a i-
206
E. Ca izosa e al. / Managemen ool o indica o -suppo ed sys ems
Figu e 1. Some sa is ac ion unc ions
ables. A decision-o ien ed p ocess is mo e sui -
able, e alua ing he e icacy o e iciency o pe -
o mance agains some p ese and pe iodically
ixed a ge s. A powe ul ool o his pu pose is
p o ided by Pe o mance Indica o s (PI) (Wes on
and B o he s, 1984; Fo uin, 1988). Hence, in-
s ead o conside ing ea u es in isola ion, we will
use pe o mance indica o s, which a e de ined by
a ea u e and i s associa ed a ge . To ge his
goal, such PIs mus be easy o unde s and, clea ly
de ined and ep esen a i e o he sys em's pe o -
mance, which is e lec ed in hypo hesis T1 im-
posed o ou model.
Fo mally, in o de o measu e a ime he
quali y o he se ice associa ed o e minal DM i,
a se V/( ) o quan i a i e a iables a e aken. Fo
any a iable ~ V/( ), we need a couple
(O,,( ), G ( )), whe e
Q( )
is he obse ed alue
o , and
Q( )
is he goal o i . This couple is
added o p e ious obse a ions and goals, gi ing
us he s ochas ic p ocess {(O~.(s),
GL,(s):s ~ T,,},
whe e T~, is he se o ins an s when he a iable
has been obse ed. Mo e p ecisely, he quali y
should be measu ed h ough he s ochas ic p o-
cess
{O,,(s):s ~ T,,},
whe e
D,~(s) = ~,(O,,(s)-
G (s), G~(s)), and is a [0, 1]- alued unc ion,
indica ing he le el o ag eemen be ween he
obse ed alue and he goal. Hence, De(s)= 1 i
a ime s, he p ese goal is eached, and
Dc(s) = 0
i he goal is no eached a all.
The DMs should ha e a hand a se o unc-
ions ~ o i hei eal pe cep ion o ag eemen ;
some pa icula ins ances, aken om P ome hEe
me hodology (B ans e al, 1984; B ans and
Vincke, 1985) a e shown in Figu e 1.
Wi h his, we ha e p ocessed he wo-dimen-
sional s ochas ic p ocess {(O (s), G~,(s): s ~ T~}
in o a one-dimensional p ocess
{D~,(s):s ~ T~.}
ep esen ing he le el o achie emen h ough
ime (S ep 1 in Figu e 2).
We a e aced now wi h he p oblem o e alua -
ing he e olu ion o such an achie emen (S ep 2
in Figu e 2).
This e alua ion should no be done using only
he mos ecen obse ed alue
(DL( )),
because
ends o imp o emen o wo sening would no
be app ecia ed: he same e alua ion would be
ob ained o e y di e en beha io s (Figu e 3).
This is he eason why we dis inguish wo
di e en pe iods o ime o a a iable : we
S ochas ic P ocess
O ( ),G ( )
Bidimensionll S ochas ic
P o¢Isl
-4 '4
By( )
D= i= lon$
P oc=ss
N
umbe in
(0,1)
Figu e 2. E alua ing a a iable by a numbe
E. Ca izosa e al. / Managemen ool o indica o -suppo ed sys ems
207
Io
DMn,, hen DMn ecei es he m- uple
(an, ....
,
anm).
This m- uple has also o be p o-
cessed in o a scala alue; a p ocedu e ha i s
hese needs e y well is he Analy ic Hie a chy
P ocess (AHP) (Saa y, 1980; Va gas, 1990).
This globalizing p ocess is ecu si ely execu ed
and ends eaching he SDM.
2.3. The Decision P ocess (DP)
Figu e 3. Di e en ends wi h he same las obse ed alue
de ine a
sho pe iod
as he ime uni y o he
obse a ions (week, mon h, qua e .... ), and a
long pe iod
as he g oup o he sho pe iods o be
conside ed in o de o explain he e olu ion o
he quali y o (mon h, yea .... ).
Wi h he de ini ions abo e, jus he la es long
pe iod should be conside ed.
The decisi e ole played by he DM should be
aken in o accoun in he e alua ing (globalizing)
p ocess h ough his a i ude owa ds isk. As has
been widely s udied in decision heo y, a neu al
a i ude owa ds isk is exp essed by means o he
a e age alue, a pessimis ic a i ude by he mini-
mum, and an op imis ic a i ude by he maximum
(Milno , 1954).
Hence, he sui able and simple choice o he
globalizing unc ion could ha e he o m
qb(a(1), a, a(n)), wi h a(1 ) = min{al,...,
an} , a =
(l/n) E
a i, a n ) = max {a ..... an}, n
is he num-
be o sho pe iods included in a long pe iod,
and a i is he le el o achie emen in he i- h
sho pe iod in he long pe iod.
A i ing p ocedu e when qb is assumed o be
addi i e is desc ibed in Appendix 1. Wi h ha
p ocedu e we ha e a scala e alua ion o any
a iable o he se ice cen e associa ed o he
e minal DMi.
The in o ma ion ha has been p ocessed by
he e minal DMs has o low owa ds he SDM
h ough he dig aph (N, B) (see Figu e 4). The
DMs in he hie a chy ecei e meaning ul bu
simpli ied in o ma ion. O cou se, i i does no
su ice, a d illing p ocess should be a ailable in
o de o ob ain mo e echnical da a.
Hence, i {DMn¢..., DMn, .} is he se o non-
e minal DMs subo dina ed o DM n and an, ep-
esen s he le el o achie emen ob ained by
The pe o mance measu e we y o op imize
is he global sys em sa is ac ion, ob ained using
he IP desc ibed abo e.
We assume ha he s ochas ic mechanism con-
olling he sys em can be modi ied by means o
esou ces, and i an unlimi ed amoun o e-
sou ces we e a ailable, he o al sa is ac ion would
be ob ained. Howe e , his is an u opic si ua ion,
so a p ocedu e suppo ing decisions conce ning
esou ce alloca ion is needed.
In eal sys ems, op imal esou ce alloca ion
does no su ice, so an op imal managemen o
exis ing esou ces is also necessa y.
As a consequence o he IP in he hie a chy,
he DMs can de ec and co ec w ong esou ce
managemen ; hence, he p ocedu e we p opose
deals wi h he o he aspec o he p oblem: he
alloca ion o new esou ces.
The DP is de eloped h ough he dig aph
(N, F). An amoun o a ailable esou ces o he
DM can be seen as a low emana ing om him,
and ha ing as sinks his subo dina es in (N, F).
The p ocess is ecu si ely execu ed, un il
eaching he lowes le el in he hie a chy, whose
DMs a e he only ones wi h he capabili y o
using esou ces in modi ying he sys em pe o -
mance.
Figu e 4. Agg ega ing sa is ac ions
208
E. Ca izosa e al. / Managemen ool o indica o -suppo ed sys ems
The p ocess can be done in di e en ways,
depending on he le el o knowledge ha DMs
ha e abou he sa is ac ion unc ion.
I he e exis s a unc ional dependence be-
ween esou ces and ou pu s in he sys em (Vla6i~,
1989), he esou ce alloca ion p oblem is sol ed
h ough he ollowing ma hema ical p og amming
p oblem:
P(F)
max (Sij(Oj, Uj, Xj)){,i,j)~F:FF, j,=¢}
s. .
xj=
E Xij
Vj/(i,j)~F:FF(j)=#,
jEFF 1
R >1 ~
Xlj ,
j~FF(I)
E xik <~ E Xkj
i~FTl(k) j~FF(k)
Vk~N,
k :g 1, FF(k) 4: ~,
O <xij < cij
'q(i,j)~F
whe e
si~(Oj, Bj, x j)
is he unc ion measu ing he
sa is ac ion o DM/~ N, whose pe o mance de-
pends on pa ame e s
Oj,
has p ese goals
Bj
and
ecei es
xj
uni s o esou ce.
The o al amoun o a ailable esou ces a e R,
we suppose ha he e exis s some capaci y
Cij
in
he a cs, and he decisions a iables a e 0 and
Xj.
P(F) is a mul iobjec i e p oblem, and i he
knowledge o a globalizing unc ion is assumed
(which is a sensible assump ion due o he AHP
ollowed in he IP), p oblem P(F) becomes a
scala p oblem, whose op imal solu ion gi es he
alues o esou ce alloca ing a iable pa ame e s
and global sa is ac ion ob ained o such an
amoun o esou ces.
When he explici o ms o he sa is ac ion
unc ions a e no known, he p ocedu e abo e is
in easible. Fo such cases, an in e ac i e me hod-
ology is mo e sui able.
The i e a i e p ocess we p opose consis s o
wo phases (Backwa d and Fo wa d), desc ibed
below. In he backwa d phase, he e minal DMs
demand an amoun o esou ces hey would like
o ecei e, and associa e o such demand he le el
o sa is ac ion o be ob ained. This in o ma ion
lows un il i eaches he SDM. In he o wa d
phase, an o e o esou ces lows om he SDm
un il eaching he e minal DMs. These wo
phases a e epea ed un il a ce ain equilib ium is
ob ained. Compa a i ely, whe eas he backwa d
phase looks o
op imali y
in sa is ac ion, he
o wa d phase looks o
easibili y.
The backwa d phase
This phase consis s o h ee s eps:
S ep 1.
Fixing uppe bounds o any e minal
DM and esou ce. In he i s backwa d phase,
hese bounds a e de e mined in a ealis ic way,
maybe upda ing pas alloca ions. In he ollowing
backwa d phases, he bounds a e de e mined
based on he o e s done in he p eceding o -
wa d phase.
S ep
2. Demands and sa is ac ion. Any DM,
DMj, gi es a pai
( j, sj),
whe e j is a esou ce
ec o demand, easible wi h espec o he p e-
sen uppe bounds
u j,
and
sj
is he le el o
sa is ac ion ha would be ob ained wi h such an
amoun o esou ces.
The p ocess is di e en depending on he kind
o DM. A e minal DMj's demand mus be he
consequence o a desi ed change in his ec o
pa ame e . Such a change may be suppo ed by
means o he p ocedu e desc ibed in Appendix 2.
A non- e minal DMj's demand o esou ces
j
equals Y'-i i, and i s associa ed sa is ac ion
sj
is
he agg ega ion o he sa is ac ions o his subo di-
na es, ollowing he IP:
s= Y~i wisi.
Ob iously, his agg ega ion should be supe -
ised by DMj in o de o co ec possible e o s
in i , due o he ac ha we ha e admi ed a
linea globalizing unc ion and he a ibu es may
no be mu ually independen (Fishbu n, 1970).
S ep 3.
Feasibili y es . The p ocess o agg e-
ga ion o esou ces and sa is ac ion ends eaching
he SDM; he ecei es a pai ( , s), whe e is he
amoun o esou ces he sys em desi es, and s is
he sa is ac ion ha such esou ces would induce.
The SDM has an amoun o o esou ces. I
o >/ , he sys em eaches equilib ium, and he
DP s ops; i his we e no he case, a o wa d
phase s a s, wi h he aim o eaching easibili y.
The numbe o i e a ions needed o each
equilib ium s ongly depends on how ealis ic he
demands made by he e minal DMs a e. Such
ealism can be con olled by he SDM h ough
a ionally ixing he bounds in S ep 1.
The o wa d phase
The amoun o esou ces i ha DM i has
mus be dis ibu ed among his subo dina e DMs.

E. Ca izosa e al. / Managemen ool o indica o -suppo ed sys ems
209
PROPERTIES El MENT5 REOURSIYITY
GLOBAL
UNDIREDT
ELABORATED
WEIGHTING
BY A.H.P.
PARTIAL
DIREOT
EA iY TO
EY/¢UATE
WEIGHTIN6
BY A.H.P.
lObs' oO "ue¢ O ( l I °(}'1~' =(hi
Figu e 5. In o ma ion and Decision P ocesses
Such a dis ibu ion should be a unc ion o he
couples
( i, sj), Vj ~ F(i),
ob ained in he p eced-
ing backwa d phase, and should be done in ol -
ing DMi.
A easible choice o his pu pose could be
ob ained by sol ing he ollowing linea ma he-
ma ical p og am:
max ~ ~sjwi6kj
j k
s. . Y'~ 6~j <~ 1 Vk = 1 ..... ,
J
O<~6~j
Vk=l,..., ,
j~F(i)
whe e 8kj is he ac ion o k- ype esou ce as-
signed o DMj and w J is he weigh ha DMi
gi es o his subo dina e DMj.
The op imal alues o he decision a iables
Ski gi e he ac ion o esou ces assignable o
e e y DMj.
This p ocess is done ecu si ely, and s ops
when he lowes le el is eached. Then, a new
backwa d phase s a s.
In o de o as en he con e gence o equilib-
ium, a p uning p ocess could be used, emo ing
hose DMs whose demands in a s age we e easi-
ble.
These wo sec ions ha e been de o ed o de-
sc ibe he HIDS. A summa izing diag am is shown
in Figu e 5. Fo p ac ical applica ions, all ha is
needed i so iden i y he eal s uc u e wi h he
elemen s in ou model. This is wha we do in he
nex sec ion.
3. A case s udy
When his de elopmen was con ac ed, he
public heal h se ices in Andalusia (Spain) de-
pended on a public ins i u ion called SAS
(Se icio Andaluz de Salud).
[
EA .
DIRECTOR 1
H.I LM. P-k 6. •
Figu e 6. SAS s uc u e
210
E. Ca izosa e al. / Managemen ool o indica o -suppo ed sys ems
The SAS o ganiza ion Table 1
A simpli ied o ganig am o he adminis a i e
s uc u e o his ins i u ion is shown in Figu e 6.
The op manage is he SAS di ec o . A he
second le el he e a e wo gene al di ec o s: The
Hospi al Assis ance Gene al Mange (HAGM)
and he P ima y Assis ance Gene al Manage
(PAGM).
Andalusia is adminis a i ely di ided in o eigh
p o inces, each one wi h i s own P o incial Man-
age (PM), subo dina e o he wo gene al di ec-
o s. E e y cen e has i s own manage (Hospi al
o P ima y Assis ance Cen e Manage ). All he
cen e s in a p o ince a e unde he esponsibili y
o hei P o incial Manage .
The complain sys em
Ins ead o being ocused on p oduc i i y, pub-
lic sys ems a e mainly in e es ed in o e ing high
quali y in hei se ices. This is why one o he
goals o SAS manage s has always been he
con inuous imp o emen o he le el o ob ained
sa is ac ion, he la e being measu ed by means
o he complain s he use s make.
Such complain s a e classi ied acco ding o he
ype o pe sonnel, he a ea o ac i i y, he eason
o he complain and he answe ob ained o he
complain (Table 1).
HIDS modeling
The hie a chical and adminis a i e SAS s uc-
u es coincide, excep o he P o incial Man-
age s. Since hese DMs join wo clea ly sepa able
asks ( he managemen o he hospi als and he
p ima y assis ance cen e s), hey ha e been spli
up acco ding o he o ganig am shown in Figu e
7. The main pa ame e s (gi en by he manage s)
ha con ol he pe o mance o he di e en
elemen s in he sys em a e shown in Table 2.
The se o obse ed a iables (ou pu s)
h oughou ime shows di e en ypes o p e-
sen ed complain s, classi ied ollowing Table 1.
The manage s ha e sugges ed ha da a should
be collec ed in he cen e s e e y mon h (a sho
pe iod). In o de o p ocess such in o ma ion, all
ha is needed is (i) he sa is ac ion unc ions
associa ed o he di e en a iables and (ii) he
Reason:
CA. Assis en quali y
TP. Poli eness
EM. Pe o mance o ins umen s
TA. Bu eauc acy
PP. Tes s los
LI. Cleaning
PU. Punc uali y
IN. In o ma ion
SA. Medical examina ion cancelled
LE. Wai ing lis
AL. Food
IA. Assis en in o ma ion
OT. O he s
A ea:
PL. Floo
UR. U gency
CE. Ex e nal examina ions
QU. Su gical a ea
PT. In e nal examina ion
LA. Labo a o y and analysis
SG. Gene al Se ices
S a :
ME. Doc o s
EM. Nu ses
AA. O ice wo ke s
CE. A endan s
MA. Main enance
DI. Di ec o s
CL. Res au an , cleaning employees
IN. O he s.
Resul :
a.
b.
C.
d.
e.
.
The use is igh and his p oblem is sol ed.
The use is igh and his p oblem emains unsol ed.
The use is w ong.
The complain is no clea enough.
The use needs addi ional in o ma ion.
The cen e is no esponsible o he eason o he
complain .
I ;*s' °zRsc °R 1
N.k E. kl. P.A.E.M.
Figu e 7. HIDS modeling
E. Ca izosa e al. / Managemen ool o indica o -suppo ed sys ems
211
Table 2
Hospi als P ima y
Assis ance
Cen e s
Numbe o beds X
Numbe o examina ion ooms X X
Special examina ions X X
Assis en ial s a X X
Adminis a i e s a X X
Gene al se ice s a X X
Numbe o ope a ing ooms X
Numbe o ambulances X X
Numbe o u gency boo hs X Figu e 8. A menu display
globalizing unc ions o ajec o ies; we ha e
gi en he manage s a small lib a y o sa is ac ion
unc ions, aken om decision heo y manuals.
The globaliza ion o ajec o ies, done acco ding
o Appendix 1, is now being alida ed.
Following also manage 's sugges ions, he goals
o he a iables a e o be ixed a he beginning
o e e y na u al (a long pe iod). Due o he
na u e o his sys em, wha manage s ha e o
de e mine is he highes numbe o complain s o
e e y ype ha is going o be seen as accep able.
In he DP, he main esou ces used in o de o
imp o e he sa is ac ion le el a e essen ially o
economical na u e, al hough in some cases he
use s assigned o e e y cen e we e also used as
esou ces. Fo his pu pose, he e minal DMs
(Hospi al o P ima y Assis ance Cen e Man-
age s) could change he pa ame e s associa ed o
hei managed cen e (see Table 2). Such a change
should be execu ed ollowing he manage 's own
expe ience, and, i needed, suppo ed by he p o-
cedu e p oposed in Appendix 2: gi en a Heal h
Se ice cen e , hose se ices wi h simila pa am-
e e s a e de ec ed; by means o a decision p o-
cess, which akes in o accoun echnical con-
s ain s (uppe bounds o he numbe o beds,
dependence be ween he numbe o ope a ing
ooms and assis en s a , e c.), a change in he
ec o o pa ame e s is p oposed.
4. So wa e a chi ec u e
HIDS has been implemen ed in a so wa e
a chi ec u e called INDI. INDI is an objec -o i-
en ed decision en i onmen ha allows he ep e-
sen a ion o decision si ua ions in a e y gene al
con ex , and allows he analysis o in o ma ion.
One he main ea u es o INDI is i s e olu i e
na u e: i pe mi s he addi ion o new ele an
elemen s and disca ding o useless ones. The
sys em is based on a se o ela ional da a bases,
managed by a knowledge base ha de e mines
he ela ions among di e en elemen s in he
hie a chy. This se o ules desc ibes he p o-
cesses o in o ma ion and decision.
INDI is a mul i-use sys em, ha uns in a
local a ea ne wo k wi h DOS compa ible compu -
e s. Some displays a e shown in Figu es 8 and 9.
INDI has wo di e en modules:
1) Use in e ace.
• Main enance. Allows he ep esen a ion o
any hie a chical sys em. The use can c ea e
new elemen s and i s associa ed ea u es, and
de ine he ela ions among hese elemen s and
he es o he hie a chy. These da a a e loca ed
in he knowledge-base.
• In o ma ion p ocess gene a o . Gene a es
he epo s o any DM in he hie a chy, and
p ocesses he in o ma ion h ough he IP o
ob ain he le el o sa is ac ion o he DMs.
!
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SERVICIOS SCCIALES U.I'IEDIOA: DIAS P lEDICCIQNES.
PERI ENERO FEBRERO VAqZO ABRIL
P gAS 5 5 5 5
E
R ~ 67 0 0 0
I
0 DES -62,00 5.00 5.00 5.00
T BAS 5.00 5.OO S.O0 S.OO
A RF~ 67.00 67.00 67.00 67.00
e i~s -~.oo *E,?.oo -62.oo -~.oo
PERIO EX~E~O N(~4AL NOW~L NORNAL
T.A.H EXTEF6qO EXTE~40 EXTE~6NO EXTEF~O
PULSE CL~L~J[ER TECLA PARA CONT[NUAR
Figu e 9. A p edic ions display
212
E. Ca izosa e al. / Managemen ool o indica o -suppo ed sys ems
"FORWARD PHASE
-,Ho,__ I I.OEOISIOH SU,,ORT/ / FREE-TExT NE'NTS
"UTIL "HIERARCHY MANAGEME "FORECASTING
INOI ATORS RELA ON A ONG
DM8
• oN--INE "~1 I'.AIN~ENAHCE~ I ""J'.AIN;~NANC~
' [ORR[I~RRATI ON I 'MS[TI gRF[[T ION
l
" SPECIAL FUNCTIONS
l
• INTRODUCTION
OF
DATA
Figu e 10
G aphical and sc een-edi o epo s a e a ail-
able.
• Analyze . This is he co ne s one o he
DP. I allows in e ac i e analysis (abou he
esou ces), p edic i e analysis abou he beha -
io o he obse ed a iables and s a is ical anal-
ysis (homogenei y in e minal elemen s, clus e
analysis).
• In e ac i e aid.
2) Sys em in e ace. Allows he con igu a ion
o ha dwa e pa ame e s, and he c ea ion o
use s and le els o esponsibili y and accessibil-
i y o he di e en modules o INDI.
An a chi ec u e diag am is shown in Figu e 10.
Appendix 1
Ou aim is he i ing o an addi i e globalizing
unc ion q~ in o de o agg ega e he achie emen
ajec o y ob ained h ough a long pe iod by
means o a eal alue q~(a(1), ~,
a(n ))
ep esen ing
he sa is ac ion associa ed o he a iable.
By addi i i y we mean ha @ is o he o m
q~(a(l ), ~, a(,)) = o a(1 ) +/3~ + 3"a(n )
o some a,/3, 3' >~ 0, a +/3 + 3' = 1, o be es i-
ma ed.
We assume ha , i he achie emen ajec o y
is displayed, he DM is able o sco e he global
achie emen (sa is ac ion) in an long pe iod wi h
a alue in [0, 1].
E en unde his assump ion, he p ocedu e we
p opose is e y use ul, because i a oids ime-con-
suming ou inely e alua ions o e e y a iable.
The pa ame e s a e i ed in a p elimina y
i ing p ocess.
Fo any sho pe iod i, le a(1)(i) , ~(i) and
a(m(i)
be he lowes , a e age and highes achie e-
men , espec i ely, ob ained in he long pe iod
ending in i. Le also
(i)
be he sco e in [0, 1]
ha he DM p oposes o such a long pe iod.
When his p ocess is epea ed du ing k con-
secu i e sho pe iods, we ob ain a sample
{(a(1)(i),
-d(i), a(m(i) , (i)), i= 1 .... , k}.
We p opose as pa ame e es ima o s,
(a*,/3", 3'*), he op imal solu ion o he p ob-
lem:
k
min E [om(1)(i) +/3~(i)
+3"a(m(i )
- (i)] 2
i=1
s. .
a+/3+3"=1,
a,/3, 3' >/0.
Once he DM's sco es ag ee wi h he global-
ized alues, he i ing s age ends. F om hen on,
he globaliza ion will be au oma ically done as
a*ao) +/3"~ + 3"*a(m.
O cou se, i a any ime he DM s ops ag ee-
ing wi h his globaliza ion, a new i ing s age
should s a .
Appendix 2
The backwa d s age in he DP s a s a he
lowes le el, whe e he sa is ac ion associa ed o
esou ce demand mus be de e mined.
Le DM n be a e minal DM wi h demand
n.
In o de o ob ain he associa ed sa is ac ion s n,
we p opose a p ocedu e ha shows a heu is ic
use o esou ces by modi ying he d-dimensional
pa ame e
O n
associa ed o DM,.
The in o ma ion ha DM, has abou sys em
pe o mance is summa ized in he de ia ion ec-