Ekonomika a managemen
100 2014, XVII, 3 DOI: 10.15240/ ul/001/2014-3-009
In oduc ion
Hospi als a e he weakes segmen o he
Slo ak heal h ca e sys em. Thei basic p oblems
a e e iden in ou da ed ma e ial- echnical base,
demo i a ion o physicians, lack o ca e o he
ch onically and se e ely ill pa ien s, egula ed
and non-compe ing sys em o heal h insu ance
companies, dys unc ional sys em o ainings
o physician and heal h p o essionals. Heal h
ca e p o ide s (HCP) assess he cu en heal h
ca e sys em as comple ely uns able. The long-
e m nega i e phenomena o he mos Slo ak
hospi als is hei loss making managemen ,
which a ec s he condi ion o he buildings,
equipmen , ewa d sys em, as well as he
wo king condi ions, he logis ics sys em o medicines,
medical ma e ials, e c. The e is a long e m
absence o he in es men esou ces, which
we e in he pas co e ed by he capi al
subsidies om he S a e budge . Hospi als
su e om he apid lack o in es men capi al
in o he buildings, echnologies and specialized
equipmen . This p oblem is closely ela ed o
he insu icien de elopmen o inno a ion and
de elopmen o highly specialized heal h ca e.
One o he possible sa ings o heal h insu ance
companies’ unds is in oducing day su ge y
op ion, espec i ely day su ge y, which would
be bene icial also o pa ien s. I is also
suppo ed by he go e nmen 's p og am o he
Minis y o Heal h o he Slo ak Republic (MH
SR) unde he educ ion o beds in hospi als and
decla ed highly e ec i e ea men consis ing
o cu ed pa ien s o he sho es possible ime,
wi hou unnecessa y pain and s ess, bu o he
highes quali y, wi hou unnecessa y hospi al
in ec ions appea ance and wi h as low as
possible expenses. Day su ge y has i s p oponen s,
bu also opponen s. Posi i e o nega i e
opinion on i s use in Slo akia depends on who
is assessing i : heal h insu ance companies a e
seeking o e icien use o a ailable inancial
esou ces in hospi als, bu hose a e pe ma-
nen ly in deb [13]. Heal h insu ance companies
con ibu e wi h signi ican ly educed paymen s
o se ices o day su ge y agains he paymen s
o comple ed hospi aliza ion. The eason is poo ly
cons uc ed and economically de-mo i a ing
sys em ha signi ican ly lags behind he
Eu opean a e age. Heal h sys ems need o be
assessed comp ehensi ely, since he adop ion
o measu es only in one a ea may subs an ially
a ec he o he a eas and cause many ad e se
e ec s, possibly wi h he wo se implica ions
han be o e he change i sel [14]. To sea ch o
al e na i es in he p ocess o inc easing he
e iciency o he heal h ca e sys em in Slo akia
i is necessa y o launch a b oad deba e abou
he whole sys em [2], [10] and i s unc ionali y,
o se up he goals, o p o ide all equi ed and
objec i e analyzes [19], o sea ch o all
possible a ian s o solu ions [39], o each an
ag eemen and pa icula ly o mee he ag eed
ules by all in ol ed s akeholde s in o de o
mee he a ge s [31], [20], [24], [38]. The e a e
e y ew s udies based on compa ison o adi-
ional hospi aliza ion wi h pe o mances p o ided
du ing day su ge y [5]. Those ha ha e been
ealized show no signi ican di e ences in he
esul s (e.g. [5], [6], [9], [11], [17]. Thei
conclusions ocus mainly on he sa e y
dimension o day su ge y pe o mance, also on
he subjec in compliance wi h all ecommended
THE FUNCTIONALITY COMPARISON OF THE
HEALTH CARE SYSTEMS BY THE
ANALYTICAL HIERARCHY PROCESS
METHOD
Vincen ·ol és, Beá a Ga u o á
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ins uc ions and o ganiza ional p inciples o he
day su ge y p og am.
1. Day Su ge y in Slo ak Republic
and Ab oad
A he p esen , in Slo akia is day su ge y mo e
inc easingly conside ed as a s anda d planned
p ocedu e, i can be ad an ageous no only o
he pa ien and his amily, bu also o heal h
ca e p o ide . „Day su ge y” is de ined as
asu ge y o p ocedu e, when he pa ien is
admi ed o eleased om su gical ca e on he
same day [1]. S ay in he hospi al du ing he
nigh up o 23 hou s is e med as „p olonged
eco e y” [1]. A e m „sho s ay“ is used o
su ge y, whe e equi ed hospi al s ay akes
mo e han 23 hou s, bu no longe han 72 hou s
[18]. Despi e o IAAS e o s o s anda dize
in e na ional e minology o acili a e compa isons
o su gical da a be ween he coun ies, he e
a e s ill he di e ences. The e is no s anda -
dized e minology o day su ge y p ocedu es,
as well as he places o hei ealiza ion, places
and leng h o eco e y a e p ocedu es and so
on. De elopmen o high quali y day su ge y
ca e se ices in Eu opean coun ies is also
ap io i y o hei go e nmen s in heal h ca e
ield. A ecen su ey conduc ed in 19 coun ies
poin ed o he signi ican di e ences in he
pe cen age o ealized p ocedu es o day
su ge y [34]. Thei ange a ies om less han
10% (e.g., Slo akia and Poland), o he a ound
80% (such as USA, Canada) [7], [29], [34].
These di e ences a e e iden be ween he
coun ies bu also wi hin he coun ies, be ween
he hospi als in he conc e e coun y, in i s
depa men s, as well as be ween he specialis s
in he equal hospi al. As he mos de e mining
ac o o s a ed di e ences could be indica ed
he exis ence o di e en ules and incen i es in
di e en coun ies, di e en inancial paymen s
o day su ge y, doc o s esis ance (including
anes hesiologis s) o he changes in he
implemen a ion o new p ocedu es and he like
(e.g. [21], [30]). IAAS (In e na ional Associa ion
o ambula o y su ge y) ecommends also
asubsequen benchma king o day su ge y
quali y assessmen based on selec ed ypes o
indica o s, such as cancella ion o planned
p ocedu es, unplanned admission o he
hospi al, e-admission o he su gical p ocedu e
(ambula o y o hospi al), pa ien sa is ac ion
wi h he su ge y pe o mance and he like.
1.1 C i ical Aspec s o Day Su ge y
in Slo ak Republic
P e ious esea ches o day su ge y use in
Slo akia [13], [14] decla e he ac ha al hough
day su ge y is a highly e ec i e ins umen o
p o iding heal h ca e, i is applied in uns able
condi ions o Slo ak heal hca e sys em. I is
asui able subjec o polemics o a ious
ep esen a i es o he heal h ca e sys em, as
well as he p o essional and gene al public, who
does no ha e adequa e in o ma ion. In o ma-
ion also absen on he web pages o indi idual
heal h insu ance companies. Day su ge y is
ca ied ou unde he p o essional guidance o
he Minis y o Heal h o he Slo ak Republic
issued in 2006. A ha ime, abou one hi d o
he pa ien s, especially in la ge public hospi als
we e hospi alized less han 72 hou s.
Fo eign s udies in he coun ies, whe e day
su ga y sys em is unc ioning o mo e han 30
yea ([23], [35], [8], [12], [16] e c.) decla e
nume ous esea ches in his ield, suppo ing
con inuous imp o emen o day su ge y
sys em. We can see a p oblema ic aspec o
day su ge y de elopmen in Slo akia in he lack
o inancial suppo om heal h insu ance
companies, which each yea expand he lis o
day su ge y pe o mances, bu wi hou
mapping he condi ions o i s app op ia eness.
In he i een yea s o day su ge y exis ence in
Slo akia, he e we e no done any esea ches
decla ing i s condi ion, as well as po en ial
de elopmen oppo uni ies. The e is no
esea ch mapping he iskiness o he selec ed
ypes o p ocedu es o di e en age g oups o
he pa ien s, he cos inc ease o ea men o
pa ien e-hospi aliza ion a e he p ocedu e,
he o e all bene i s o day su ge y use
compa ed o he s anda d hospi aliza ion wi h
he conc e e ype o diagnosis (cos sa ings o
heal h insu ance company), including he
pa ien 's ea ly e u n o he wo king p ocess.
P oblems can also be ound in he p ima y da a
collec ion, whe e in epo ing equencies o
day su ge y pe o mance based on he
guidelines o MH SR we ind many incon-
sis encies and incompa ibili ies. All c i ical
aspec s we e he impo an de e minan s in ou
expe e alua ion, which was he p epa a o y
phase o he applica ion o Analy ic Hie a chy
P ocess (AHP) in he p ocess o compa ison o
he wo heal h ca e sys ems. Applica ion o
AHP is u he elabo a ed in Chap e 2.
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1.2 Day Su ge y in he P ocess o
Beds Reduc ion in Heal h Ca e
Sys em
In connec ion wi h he day su ge y de elopmen
is necessa y o men ion he p ocess o he
hospi al beds educ ion. Reducing he numbe
o hospi al beds p e iously used o inpa ien
ca e can be conside ed om a inancial pe spec i e
as an impo an bene i o day su ge y. Slo akia
is among he OECD coun ies wi h he lowes
e iciency o heal h ca e, while in he numbe o
beds pe 1,000 inhabi an s is abo e he
a e age o he OECD [37]. Reduc ion o he
hospi al beds was epea edly planned by
p e ious go e nmen s in Slo akia, ouching
also he hospi als ha we e no in ended o be
cancelled. Al hough, he expec ed ou pu o
a ionaliza ion o hospi als in he long un in
conjunc ion wi h o he measu es, which should
inc ease he pe o mance managemen o
public esou ces in he heal h sec o , s i es o
he inc easmen o he quali y and accessibili y
o heal h ca e o ci izens, i can also cause
a ansi o y exace ba ion o he access o he
heal h ca e. As epo ed by he Na ional Heal h
In o ma ion Cen e (NHIC) s a is ics, since
2000 is epo ed a decline end o he numbe
o hospi al beds in all segmen s (acu e,
psychia ic as well as beds o long- e m
pa ien s). Be ween he yea s 2000–2007 he e
was a educ ion o beds by 37.3% (in 2000 was
hei numbe 42,332 and in 2007 a o al o
26,546 beds). Dec ease in he numbe o beds
was also e lec ed in he decline o he numbe
o employed physicians by 13.2% ( om 6,143
o 5,334), as well as he educ ion o o he
medical pe sonnel [36], [37]. In 2011, he
Gene al Heal h Insu ance Company educed
abou 3,000 unnecessa y beds and has no
con ac ed abou 150 hospi al depa men s,
which we e o en duplica ed o ine ec i e.
Despi e o he e e ed a ionaliza ion ac ions,
Slo akia emains in anking among he OECD
coun ies wi h he lowes e iciency o heal h
ca e, while in he o al numbe o hospi al beds
pe 1,000 inhabi an s is abo e he a e age o
OECD coun ies (e en in acu e beds) [36]. I is
appa en om he abo e ha he scope o
u he hospi al a ionaliza ion exis s, al hough
he p ocess o educ ion o beds causes
ac i ical con o e sy among he expe s in he
sense, ha s a ed sys em o sa ing inances is
liquida ing o hospi als. A e he educ ion o
beds was expec ed a lowe supply o unds
om heal h insu ance companies, which would
jeopa dize he abili y o hospi als o pay hei
liabili ies. Finally, he hospi al would ge mo e
in o he deb , because e en a he lowe in low
o he inances, hey will ha e o cu e he
pa ien s.
2. Compa ison o Heal h Ca e
Sys ems in Hospi als
Day su ge y in Slo akia and ab oad bene i s
om he posi i e esul s o se e al s udies and
medical p ac ice decla ing he ac , ha he
bes ongoing ea men and eco e y o
pa ien s a e su ge y is a home en i onmen .
Mode n medicine, as well as ongoing de elopmen
o ope a ional echniques and ela ed me hods
o he pos -ope a i e ca e, enables o sho en
hospi al s ay o a minimum and i p omp s o
e u n o he no mal li e [32]. Cu en educa-
ional modali ies limi he nega i e in luence o
in e indi idual a iabili y o su gical skills, hus
inc easing he po en ial o uncomplica ed
pos ope a i e cou se [4]. Howe e , he mos
s anda d, uncomplica ed su ge ies in Slo akia
a e accompanied by unnecessa ily long
hospi al s ay. When e alua ing he day su ge y
e iciency i is necessa y o bea in mind ha
he inancial sa ings occu when he hospi a-
liza ion su ge ies subs i u e he execu ion o
day su ge y pe o mances and bed a e
educed. Day su ge y e iciency depends on
many ac o s: p icing s a egies o heal h
insu ance companies, place o day su ge y
pe o mance, he pa ien age, como bidi ies
[33], deg ee o echnical ailu e o he su geon,
social aspec s and so on [3], [8] [15], [16], [35].
The he e ogenei y o hese ac o s on he one
hand makes he p ocess o day su ge y
pe o mances signi ican ly di icul o compa e
wi h he sys em o inpa ien ca e. Bu in he
indi idual componen s o he unc ioning o
bo h sys ems a e clea unambiguous c i e ia
ha a e necessa y o ensu e he unc ionali y o
he p ocess o heal h ca e p o iding. To
compa e hose wo sys ems, we ha e choosen
al eady men ioned AHP me hod.
2.1 AHP in he P ocess o
Compa ing Heal h Ca e Sys ems
AHP is a s uc u ed echnique designed o sol e
acomplex decision. I is based on ma hema ical
p ocedu es and human psychology. Since i s
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i s publica ion in he 70s o he 20 h cen u y, i
has unde gone se e al imp o emen s and i
p o ides complex and cohe en app oach o
he s uc u ing o he p oblem, o quan i y he
elemen s ela ed o he o e all objec i es and
e alua es an al e na i e solu ions. AHP can be
used in a ious decision-making si ua ions
sphe es (go e nmen , business, indus y,
heal h, educa ion).
AHP me hod is based on he c ea ion and
analysis o hie a chical s uc u e o he sol ing
ask. By he hie a chical s uc u e o he e m
we unde s and o he s uc u e, con aining
anumbe o le els, whe e each o hem con ains
se e al elemen s. The a angemen o he
di e en le els o hie a chical s uc u e co es-
ponds wi h he way o he a angemen om he
gene al o he speci ic. The mo e gene al
elemen s a e in ela ion o ha decision-making
p oblem, he highe le el o hie a chy hey ge .
The ypical simple ask o mul ic i e ia op ion
analysis includes he ollowing le els:
 i s le el – objec i e e alua ion, which
could be he a angemen o a ian s,
second le el – e alua ion c i e ia,
 hi d le el – assessed a ian s.
When quan i ying ela ions in he hie a chy,
i usually p og esses om he op o he bo om.
The me hod o quan i a i e pai compa ison by
Saa y is used; i is based on he impo ance o
compa ing all pai s o elemen s e alua ion [25],
[26], [28]. The ou pu o AHP is impo an o
he e alua ion o c i e ia, he e o e i is e y
impo an o pay a en ion o he p ocedu es
which helps o de e mine weigh s o he c i e ia
esponsibly and exac ly. Fo decision making
a e also impo an expe iences, i helps o so
ou e alua ion c i e ia o moni o ing so-called
in o ma i e signs, which p o ide la ges olume
o eal in o ma ion o deciding. Decisions
made on he base o he bes decision-making
me hod may no be co ec ; i he inpu da a in
p epa a ion phase a e no pe ec ly managed
and su icien quali y in o ma ion a e missin . In
he i s phase, be o e applying he me hod o
e alua ing, he e alua ing en i y has o de ine
all c i e ia and sub-c i e ia unde which he e a-
lua ion will ake place. Selec ion o indi idual
c i e ia and sub-c i e ia is ca ied ou on he
basis o cu en knowledge and expe iences o
each e alua ing en i y. I i is a e y i s
e alua ion o some en i y, he c i e ia mus be
so ed ou mo e o less acco ding o i s own
in ui ion, espec i ely acco ding o some
e alua ing subjec empla e, o acco ding o he
asks ha is he subjec o decision making.
2.1.1 The S uc u e o he AHP Me hod
Me hod o AHP is a lexible model o decision
making, cla i ying issues ha ha e se e al
possible solu ions. AHP is ca ied ou by an
expe me hod and hen by a ma hema ical
me hod, which di ides main p oblem in o he
smalle and mo e de ailed elemen s. Decision
making by he me hod o AHP can be di ided
Fig. 1: Fou -le el hie a chy o AHP
Sou ce: [25]
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104 2014, XVII, 3
in o h ee di e en le els [25]: 1) hie a chy, 2)
p io i ies, 3) consis ency.
Hie a chy – decomposi ion o he
p ope ies in o homogeneous clus e s and hen
u he di iding in o smalle uni s, we can
g adually in eg a e a la ge amoun o
in o ma ion in o hie a chical s uc u e, c ea ing
amo e comple e pic u e o he sys em.
Hie a chy on Figu e 1 ep esen s a p oblem o
mul ic i e ia decision making.
Se ing p io i ies – o de e mine he in en-
si ies o he impac e ec o a ious componen s
on he sys em as a whole, we need o ans e
ace ain ypes o measu emen . AHP allows
compa ing and measu ing he in angible
quali a i e ac o s (e.g. social, poli ical, e c.). In
absolu e compa isons a e compa ed he
al e na i es wi h he es ablished s anda d, which
was de eloped on he basis o pas expe iences.
In ela i e compa isons a e al e na i es compa ed
in pai s usually h ough he commonly used
e alua ion e ms (e.g. wo se, be e , e c.). AHP
uses o bo h ypes o compa isons, ca dinal
scales a e s a ed in Table 1.
Tab. 1: Basic scales o pai compa ison
E alua ion
deg ee Compa ison o elemen s x and y Explana ion
1xis as impo an as y Bo h elemen s con ibu e equally o he esul
2xis less impo an as y The i s elemen is sligh ly mo e impo an han he o he
3xis sligh ly impo an han y Expe iences and assuming sligh ly p e e he i s elemen
be o e he second
4xis sligh ly mo e impo an han y Sligh ly s onge p e e ence han he p e ious
5xis s ongly mo e impo an han y S ong p e e ence o he i s elemen be o e he second
6xis much mo e s ongly impo an han y Sligh ly s onge p e e ence han he p e ious
7xis e y s ongly impo an han y Ve y s ong p e e ence o he i s elemen be o e
he second
8xis e y, e y s ongly mo e impo an han y Sligh ly s onge p e e ence han he p e ious one
9xis ex emely mo e impo an han y The ac s ha p e e he i s elemen o e he second
one ha e he highes e iden ial le el.
Sou ce: [25]
In o ma ion abou he signi icance o he
c i e ia ob ained on he base o he pai ed
compa ison can be de e mined as he alues
sij, which indica es he a io o he signi icance
o he e alua ion c i e ia ki o c i e ion kj, whe e
i,j = 1,2,...,n. I is equi ed ha sij mee s o all i,
j= 1,2,...n, whe e n is he numbe o e alua ion
c i e ia, unde he ollowing condi ions [25]:
sij > 0, sij = sji-1, sii = 1 (1)
Va iables sij, ela i e signi icance o c i e ia
ha e o be a anged in a squa e ma ix o
ela i e signi icance S.
Consis ency – in de e mining he ela ions
be ween he objec s, he cohe ence ha e o be
achie ed, i.e. consis ency o mu ual ela ions.
This cohe ence is achie ed by homogenei y
( ele ancy) mani es ed in homogeneous clus e ing
o he objec s acco ding o gi en c i e ia, as well
as consis ency o in ensi y o ela ions be ween
he objec s acco ding o di e en c i e ia. The
al e na i es o decision a e so ed ou in o de
o e alua ion [27].
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As epo ed by Saa y and Joyce [26], when
using AHP me hod o decision making, ou
axioms ha e o be me :
In e se axiom: i an al e na i e A is n- imes
p e e ed o B, hen B al e na i e is 1/n-
imes p e e ed o A. I is a ule o
ecip oci y exp essed by he o mula:
(3)
Homogeneous axiom: compa ison using
pai ing is signi ican only i he elemen s a e
compa able.
Dependen axiom: compa ison a a lowes
le el (sub-c i e ion) depends on he
elemen a a highe le el ( he highe
c i e ion), he ule o ansi i i y.
Consequen ial axiom: i any c i e ion in he
hie a chy will be changed, new e- alua ion
o he new hie a chy is expec ed.
In p ac ical applica ion o me hod AHP, he
elemen s o decision ma ix, a e e y o en no
consis en . So he e is needed o calcula e
inconsis ency index, exp essed by he o mula
[25]:
(4)
whe e λmax is he bigges eigen alue o ma ix
Sand nis i s dimension. I Is= 0, han he
ma ix is consis en .
The highe he alues o inconsis ency
index (Is) acqui es, he mo e inconsis en a e
he pai wise compa isons in he ma ix o pai ed
compa isons. In case o highe inconsis ency
Saa y ecommends, ha expe should
econside i s assessmen o c i e ia and
modi y he ma ix o ela i e signi icances S, o
inc ease i s consis ency [27]. On he con a y,
he close o ze o is he alue Is, he g ea e is
he consis ency o he pai wise compa isons in
ma ix. In p ac ical applica ion Saa y ecom-
mends o accep he alue o inconsis ency
index lowe han 0.1, as i was applied in ou
calcula ions.
2.2 P ac ical Applica ion o AHP –
De e mina ion o C i e ia and
Sub-C i e ia
The subjec s o ou analysis a e heal hca e
sys ems, namely day su ge y and inpa ien
( adi ional) heal h ca e. He e ogenei y o hose
heal h ca e sys ems makes i signi ican ly
di icul o compa e hem in he hospi als.
De e mina ion o c i e ia and sub-c i e ia o
bo h heal h ca e sys ems was ca ied ou by he
expe e alua ion, 16 expe s pa icipa ed (3
we e he membe s o he Slo ak Associa ion o
Day Su ge y, 4 heal h insu ance companies
ep esen a i es, 4 ep esen a i e o he
Associa ion o Hospi als in Slo akia (AHP), 4
heal h ca e we e p o ide s wi h eal expe ience
wi h day su ge y pe o mance and 1 ep esen-
a i e was om he uni e si y sphe e). A he
beginning o his p ocess, expe s ha e
iden i ied a se o c i e ia; he e was no exac
e alua ion o indi idual elemen s be ween
hem. We ob ained a lis o he componen s o
heal h ca e sys ems, which a e no mu ually
alued be ween hem, so in his ime hey had
he same weigh . Based on he expe e alua ion,
he ollowing basic c i e ia we e speci ied:
s a egic ocus, sys em s abili y, measu abili y,
causali y, cohe ence wi h unding sou ces,
sys em sus ainabili y and eedback, and sel -
e alua ion o he heal h ca e sys em (Table 2).
These c i e ia we e also he basic p inciples o
heal h ca e (day su ge y and in-pa ien ca e)
and a pla o m o subsequen expe e alua ion
o he AHP. Adhe ence wi h hose p inciples in
he analyzed sys ems is condi ional o achie ing
he expec ed bene i s om hem. These p inciples
a e based on he undamen al p inciples o he
bo h, heal h ca e sys ems unc ioning, om
hei compa a i e aspec s, as well as om he
esul s o he own esea ch ac i i ies [13], [14],
The abo e s a ed p inciples ep esen he
e alua ion c i e ia, o which he g oup o expe s
om ou esea ch subsequen ly es ablished
ase o so-called sub-c i e ia (Table 2).
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Ekonomika a managemen
106 2014, XVII, 3
Lis ed c i e ia a e ela i ely widely unde s ood.
Fo his eason, i is necessa y ha in he p ocess
o de ining he c i e ia, he expe s should b eak
down hose c i e ia in o sub-c i e ia o he le el
whe e i is necessa y. The le el o he segmen-
a ion is unlimi ed. In his case, we ha e chosen
o b eak down he c i e ia only o one lowe le el,
o he sub-c i e ia. In p ac ice i is possible ha
hese sub-c i e ia will be subdi ided o o he
sub-sub-c i e ia. Fo he second le el o sub-
c i e ia we e based on expe es ima ion o he
expe g oup se he i ems shown in Table 3
F om he able is also clea he compe ence o
he a ious sub-c i e ia o he main c i e ia.
Tab. 2: Se o heal h ca e sys ems unc ionali y c i e ia based on expe e alua ion
C i e ion C i e ion i le
K1 S a egic objec i e o heal h ca e sys em
K2 S abili y o heal h ca e sys em
K3 Measu abili y
K4 Causali y
K5 Cohe ence wi h unding sou ces
K6 Con inui y, sus ainabili y and eedback
K7 Sel -e alua ion o heal h ca e
Sou ce: own
Se o heal h ca e sys ems unc ionali y sub-c i e ia based o expe
Tab. 3: e alua ion (pa 1)
Sub-c i e ion Sub-c i e ion i le
S1.1 Implemen a ion o he consis en s a egic analysis and assessmen o he app op ia eness o he heal h
ca e sys em o cu en condi ions in he Slo ak heal hca e
S1.2 Consensus on a ision and/o mission and/o c i ical success ac o s
S1.3 Regula analysis and assessmen o he o e all s a egic pe o mance o he hospi al
S1.4 Re ising he exis ing s a egic a eas and he possibili y o accep ing o he po en ial s a egic a eas
S1.5 Suppo o he majo decision-making o ganiza ion managemen s (MZ SR, heal h insu ance companies,
The Heal hca e Su eillance Au ho i y, AHS) when using heal h ca e sys em and hei pa icipa ion on he
ele an esul s o he heal h ca e sys em
S2.1 Regula ede ini ion o he objec i es and ac ions wi hin he heal h ca e sys em
S2.2 De ined objec i es e lec he equilib ium iew on he s a egy o hospi al
S2.3 De ined s a egic ac ions e lec he equilib ium iew on he s a egy o he hospi al
S2.4 Regula analysis and e alua ion o he balance be ween exis ing s a egic measu es
S3.1 To he s a egic objec i e a e assigned app op ia ely chosen s a egic measu e me hods o he alues
measu ing
S3.2 To he s a egic measu es a e assigned hei a ge alues and c i ical alues
S3.3 Speci ied condi ions and e ms o egula quan i ica ion o he measu es
S3.4 Regula analysis and e alua ion o exis ing measu es, a ge and c i ical alues, measu es and choice o
o he po en ial a ge and c i ical alue o measu es
S4.1 Causal ela ionships a e de ined be ween he s a egic pe spec i es
S4.2 Causal ela ionships a e de ined be ween he s a egic objec i es
S4.3 Causal ela ionships a e de ined be ween he measu es
S4.4 Causal ela ions a e de ined be ween he a ge ed and c i ical alues o s a egic measu es
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Se o heal h ca e sys ems unc ionali y sub-c i e ia based o expe
Tab. 3: e alua ion (pa 2)
Sub-c i e ion Sub-c i e ion i le
S5.1 De ined s a egy and subsequen planes a e linked o he s a e budge o SR
S5.2 Hospi al sou ces a e wi hin he sys em o day su ge y aligned wi h s a egic ac ions, espec i ely s a egic
ini ia i es
S5.3 Non-s a egic in es men s, espec i ely non-s a egic ac i i ies we e selec ed and elimina ed by in oduc ion
o new o ms o heal hca e
S5.4 Resul s o analyzes a ec he e iew o he s a egy, i.e. s a egic objec i es and esou ces
S5.5 Regula ly a e analyzed and e alua ed links o he sou ces o hospi als o he s a egic ac i i ies iden i ied in
he heal h ca e sys em
S5.6 Based on he esul s o analysis and e isions o he s a egic assump ions, i necessa y, we e ise exis ing
links o budge and s a egy o day su ge y sys em
S6.1 P ojec o es ablish heal h ca e sys em was planned in de ail om he me hodological, echnical and
o ganiza ional pe spec i e
S6.2 The in oduc ion o he heal h ca e sys em had he ull suppo and pa icipa ion om he side o supe io
uni s and ele an o ganiza ions s
S6.3 Fo day su ge y unc ioning was chosen and implemen ed an app op ia e in o ma ion sys em
S6.4 Ex ending heal h ca e sys em wi hin he hospi al was managed and con olled p ocess
S6.5 Leade ship o o ganiza ions suppo s he use o he heal h ca e sys em and pa icipa es in he ele an
esul s
S6.6 Con inuous ope a ion o he heal h ca e sys em and egula epo ing is ensu ed
S7.1 Fo he in oduc ion o he heal h ca e sys em was elabo a ed cos analysis and/o analysis o isk and
bene i s
S7.2 Condi ions and ules o he egula e alua ion o he heal h ca e sys em in e ms o bene i s, isks, and
cos -e ec i eness we e speci ied
S7.3 The heal h ca e sys em is egula ly analyzed and e alua ed - i s bene i s, cos s, gaps, isks and so on.
S7.4 In case o e ising condi ions and ules o unc ionali y and hei use o heal h ca e sys em, an e o o
con inuous imp o emen is egis e ed
Sou ce: own
In he i s ound o he expe e alua ion
we e de ined c i e ia and sub-c i e ia.
Subsequen ly, he expe s we e p o ided wi h
he lis s o c i e ia and sub-c i e ia in o de o
assess hei impo ance. The expe s could
assign a deg ee o impo ance o c i e ia and
sub-c i e ia om 1 (absolu ely impo an ) o he
le el 9 ( o ally unimpo an ). Expe s we e gi en
a able o c i e ia and sub-c i e ia and hen
using he modal c i e ion, he impo ance o
each c i e ion was e alua ed. Resul s a e
s a ed in he ollowing Table 4.
Consequen ly, using hese links be ween
hose c i e ia and sub-c i e ia we de e mined
he elemen s o ma ix. Value ma ix Sis de ined
p ecisely on he basis o mu ual compa ison o
he c i e ion impo ance, espec i ely associa ed
sub-c i e ia. E.g. when c i e ion K1 is as
impo an as c i e ion K2, he alue o mu ual
e alua ion o hese c i e ions in ma ix S is 1.
C i e ion K1 is one le el uppe han c i e ion
K4. So in a ow K1 and a column K4 is numbe
2. In a ow K4 and a column K1 is e e se alue
o 2, so 0.5, as K4 is one le el lowe han K1.
Analogically we can e alua e pai s o c i e ions.
Thus, we can de ine he alues as ela i e
di e ences o impo ance. When c ea ing a ma ix,
i is impo an o p ese e he ule o ansi i i y.
In ou case, a ibu e K1 is one deg ee mo e
impo an han a ibu e K4 (s14 = 2) and a ibu e
K4 which is one deg ee mo e impo an han K7
(s47 = 2). Based on he ansi i i y ule i mus
apply, ha an a ibu e K1 is 2 deg ees mo e
impo an han a ibu e K7 (s17 = 3).
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Ekonomika a managemen
108 2014, XVII, 3
I can also be exac ly w i en. Le ki ep esen s
an e alua ion o he impo ance o i- h c i e ion/
/sub-c i e ia. Mu ual e alua ion o he impo ance
o he wo c i e ia/sub-c i e ia hen can be
de ined as sij, as c i e ion i is mo e impo an
han c i e ion j which is s a ed by he o mula:
sij = kj– ki+ 1 i ki< kj,(5)
sij = 1 / (ki – kj+ 1 ) when ki> kj.(6)
Weigh s a e s a ed as:
whe e mis an index o a supe io main
c i e ion.
Resul s a e w i en in able 5 and able 6.
Tab. 4: Ranking o c i e ia and sub-c i e ia speci ied by expe e alua ion
Table o anking c i e ia and sub-c i e ia in o de o impo ance
C i e ia and sub-c i e ia Sub- Sub- Sub- Sub- Sub- Sub- Sub-
c i e ia c i e ia c i e ia c i e ia c i e ia c i e ia c i e ia
S1.X S2.X S3.X S4.X S5.X S6.X S7.X
S5.1, S6.1,
C i e ia S1.1, S5.2, S6.2,
S1.2, S2.1, S3.1, S4.1, S5.3, S6.3, S7.1,
K1, K2, S1.3, S2.2, S3.2, S4.2, S5.4, S6.4, S7.2,
K3, K4, S1.4, S2.3, S3.3, S4.3, S5.5, S6.5, S7.3,
K5, K6, K7 S1.5 S2.4 S3.4 S4.4 S5.6 S6.6 S7.4
Deg ee o impo ance Assigned
c i e ia Assigned sub-c i e ia
1. Absolu ely
impo an
S5.1,
S4.1, S5.2, S6.3,
2. Ve y s ongly S1.1, S4.2, S5.4, S6.4,
impo an K1, K2, K3 S1.2. S2.4. S4.4. S5.5. S6.6. S7.1
3. S ongly impo an S2.2, S5.3, S6.2, S7.2,
K4, K5, K6 S1.5 S2.3 S4.3. S5.6. S6.5. S7.4.
4. Impo an K7 S1.3, S2.1 S3.4. S6.1. S7.3.
S1.4.
5. Weakly impo an S3.1,
S3.3.
6. No impo an S3.2.
7. S ongly unimpo an
8. Ve y s ongly
unimpo an
9. Absolu ely
unimpo an
Sou ce: own
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Abs ac
THE FUNCTIONALITY COMPARISON OF THE HEALTH CARE SYSTEMS BY
THE ANALYTICAL HIERARCHY PROCESS METHOD
Vincen ·ol és, Beá a Ga u o á
Day su ge y is one o he a eas ha a e s ill no implemen ed in Slo akia in he in en ions o inding
signi ican economic sa ings in he heal h ca e sys em. The p ima y objec i e o use day su ge y
was o sepa a e he pa ien s wi h ligh e chi u gical p ocedu e, o less auma ize he pa ien s wi h
hospi aliza ion, o p o ec he pa ien om nosocomial in ec ions and o make eco e y easie in
g ea e com o o he own home. The p ima y impulse o dealing wi h he e ec i eness o heal h
ca e sys ems, wi h an emphasis on day su ge y, we e con lic ing esponses ega ding he
e iciency and e ec i eness o deploymen and use o day su ge y pe o mance. On he one hand,
we ind he di ec and indi ec e idence o unc ional applica ion o day su ge y pe o mance in
heal h acili ies in Slo akia and i s po en ial bene i s in achie ing he aims o heal h policy o he
SR. On he o he hand he e a e c i ical esponses on lack o he e ec s o he day su ge y use,
which a e associa ed wi h low alua ion o s a ed p ocedu es which a e inadequa e o he eal
cos s. I hinde s i s de elopmen in compa ison wi h he de elopmen ab oad. The main aim o his
a icle is o compa e he unc ionali y o day su ge y ca e in compa ison wi h he sys em o ien a ed
on adi ional hospi aliza ion, using he opinion o he expe s who ep esen he sys em o heal h
ca e in Slo akia. Fo o ien a ion in c i e ia cha ac e izing he unc ionali y o heal h ca e sys ems in
Slo akia, we s a ed om he p emise ha he unc ionali y o heal h ca e sys em is a basis o i s
e ec i eness. Gi en he conside able he e ogenei y o compa ed c i e ia o heal h ca e sys ems
we ha e chosen he me hod o Analy ical Hie a chy P ocess as he op imal me hod, suppo ed by
he expe g oup me hod.
Key Wo ds: Heal h ca e sys em, in-hospi al ca e, day su ge y, Analy ical Hie a chy P ocess,
unc ionali y o day su ge y.
JEL Classi ica ion: I11, I12, I14, I18, I19.
DOI: 10.15240/ ul/001/2014-3-009
EM_03_14_zlom 28.8.2014 9:45 S ánka 117