57
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Business Adminis a ion and Managemen
DOI: 10.15240/ ul/001/2015-2-005
In oduc ion
Cu en ends in scien ifi c and echnological
ad ances a e b inging a signifi can
imp o emen s in heal h ca e as a esul o
c ea ion new ools ool o suppo decision
making p ocess o decision-make s (DM)
[8], [11], [12], [23], [27]. The expe s g oup
app oach is used in heal h sec o bo h clinical
[28], [31] and nonclinical [5], [24], [29], [30],
[32] decision-making. The goal o his pape
is o de elop, es and analyse a me hodology
o de e mining he quali a i e and quan i a i e
composi ion o an expe g oup and i s
applica ion on example o he heal h echnology
decision making in he Czech Republic.
Heal h p o ide s ace he p oblem o ying o
make decisions in si ua ions whe e he e is
insu fi cien in o ma ion and also whe e he e is
an o e load o (o en con adic o y) in o ma ion
[13]. Regula o y and eimbu semen au ho i ies
ace unce ain choices when conside ing he
adop ion o heal h-ca e echnologies [4]. As he
la ges sha e o heal hca e expendi u e is paid
om public sou ces, he e fi cien decisions a e
no only pu ely echnical and fi nancial p oblem
bu may be seen as an issue o public in e es
in he b oade e ms. This ype o decision-
making me hodology may ha e a e y wide
po en ial also ou side he sec o o heal hca e
[14], [16]. Un o una ely he decision-making in
he heal hca e (and many o he pa o public
sec o s) in e ms o la ge in es men he Czech
Republic is ela i ely o en he objec o se ious
economics as well as legal conce ns. To seek
o e idence-based me hodology ha has
a po en ial o e idence-based decision-making
is e y i al as an opposi e o he decision-
making infl uenced by pa ial indi idual and
g oup in e es s.
Many o he mos e ec i e models
used o fi nd expe s a e mainly based on
he language models [17], [33]. One o he
p oblems wi h models based on language
model amewo ks is ha hey can ake in o
accoun ex ual simila i ies be ween he que y
opics and documen s [1], [20], [26]. The
pape [2] p o ides wo expe s fi nding sea ch
s a egies modelled o inco po a e di e en
ypes o e idence ex ac ed om he da a.
The ad an age o he mode n app oaches
is machine lea ning echniques [18], [34]
o disc imina i e p obabilis ic models [7]
a possibili y o agg ega ion o a la ge numbe o
he e ogeneous in o ma ion. In addi ion o ha ,
he e a e he ollowing p oblems and di fi cul ies:
i is di fi cul o exp ess quali a i e in o ma ion
on expe s in he quan i a i e o m because
in o ma ion abou he candida es a ies wi h
ime; he expe ience o a candida e is always
a ying h ough ime. [8]
In candida e-cen ic p obabili y es ima ion
app oaches o academic expe fi nding [1],
he assessmen o an expe is made using
gene a i e p obabilis ic models. In que y
independen me hods [25], knowledge o he
expe candida es is p esen ed as a mix u e
o language models. The pe son-cen ic [26]
app oach is inc easingly being used. This pape
[19] is based on ex ual simila i ies, he au ho ’s
p ofi le in o ma ion and he au ho ’s ci a ion
pa e ns o y o fi nd academic expe s. The
me hods o Condo ce Fuse [19], Ma ko chain
models [6] and mul i-c i e ia decision-making
me hods 10] a e ecognised as ep esen ing he
mos ele an wo ks [3]. The mul isenso y Da a
Fusion app oach using Demps e -Sha e heo y
o E idence oge he wi h Shannon’s En opy [20]
was used o academic expe s fi nding.
METHOD FOR SELECTING EXPERT GROUPS
AND DETERMINING THE IMPORTANCE OF
EXPERTS’ JUDGMENTS FOR THE PURPOSE
OF MANAGERIAL DECISION-MAKING TASKS
IN HEALTH SYSTEM
Ilya I le , Pe e Kneppo, Mi osla Ba ák
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58 2015, XVIII, 2
Ekonomika a managemen
Expe s fi nding is a di fi cul ask because
he expe s and hei skills and knowledge
a e a e, expensi e, cons an ly changing and
a ying in dep h. When add essing di fi cul
mul idisciplina y p oblems, a combina ion
o knowledge om se e al expe s is o en
equi ed, especially om expe s in a ious
fi elds. Ou me hod p oposal is based on
he esea ch o expe s’ weigh ing ac o
de e mining ha efl ec s he o e all compe ence
o he expe s when p oblem sol ing.
1. Examina ion o Expe s
An examina ion needs o be pe o med o
de e mine he weigh -coe fi cien s o impo ance
in oduced by each c i e ion o choice. Depending
on he scale o he p oblem, he examina ion is
o ganised ei he by a DM in pe son o by an
expe g oup appoin ed by he DM. Decisions
abou he numbe and compe ence o expe s
a e made wi h ega d o he scope o he
ask, he e aci y o he e alua ions o expe s’
cha ac e is ics and he a ailable esou ces.
The ollowing asks need o be sol ed while
c ea ing he expe eam: 1) unde s and he ask
o be sol ed by he expe s; 2) de e mine fi elds
o ac i i y linked o he ask; 3) decide wha
sha e in he eam shall be alloca ed o expe s
ep esen ing each fi eld o ac i i y; 4) de e mine
he numbe o expe s in he eam and d a a lis
he eo ; 5) analyse expe s’ qualifi ca ions and
edi he d a lis o expe s; 6) ob ain he expe s’
ag eemen o wo k on he eam; and 7) fi nalise
he lis o expe s. Depending on he chosen
o m o de e mining expe s’ p e e ences,
he main equi emen s o he expe s a e as
ollows: 1) compe ence ( eliabili y and alidi y
o decisions, awa eness and ep oducible
assessmen and a gumen a i eness eplies);
2) impa iali y; 3) c ea i i y; 4) con o mism; 5)
eam spi i (dependen on qua e na y ype);
6) ela ion o he examina ion; 7) deg ee o
pa icipa ion in he sol ing p oblem; and 8)
communica ion skills (dependen on qua e na y
ype) (Fig. 1).
The expe s’ cha ac e is ics, as lis ed
abo e, gi e a comp ehensi e pic u e o he
quali ies ha infl uence he examina ion esul s
mos s ongly [20] (p ope ies ha a e w i en
on a black backg ound a e aken in o accoun
in ou model).
2. Quan i y Lis o he Expe G oup
To de e mine he su i cien numbe o expe s, we
needed o i nd a numbe H, so ha he inequali y
W > H is ue, whe e W is he dispe si e
Kendall’s coe i cien o conco dance (coe i cien
o conco dance o expe s’ opinions. Cons an H
is selec ed om he ela ionship PW > H = α and
is ully de i ned by he le el o signi i cance α. I
is i a ional o selec a low le el o signi i cance
because i s dec ease esul s in an inc ease o H,
which, consequen ly, inc eases he con ingency
o he e o o he second ype [13].
The eby, we shall de e mine he necessa y
quan i y o expe s ha gua an ees, a a fi xed
le el o signifi cance, he gi en c i ical alue
o dispe si e coe fi cien o conco dance. Fo
easons o simplifi ca ion, we shall conside he
ollowing ela ionship ue:

2
1.
1
n
PW H P Hm
n




  





(1)
As
2
1
1
lim 1
n
n
n





(n = quan i y o pa ame e s),
he le el o signifi cance o a c i e ion is
de e mined by he p oduc H*m (m = numbe
o expe s), which, e en wi h a small numbe o
expe s, can make α su fi cien ly small.
The su ey o expe s included eco ding,
in an in o ma i e and quan i a i e o m, he
expe s’ opinions abou a gi en p oblem. The
main modes used o su ey expe s include
ques ionnai es and in e iews, discussions and
b ains o ming. The Delphi me hod could be
used o consensus-building by using a se ies
o ques ionnai es deli e ed using mul iple
i e a ions [19], [20].
3. P ocessing o Expe s’
E alua ions
P ocessing is needed o ob ain gene alised
da a and new in o ma ion ha is concealed in
he expe s’ e alua ions. I g oup e alua ions
o objec s p o e doub ul when compa ed wi h
calcula ed s a is ics, i is necessa y o de e mine
he easons o he ailed examina ion. The mos
ypical easons o ailed examina ions include
he ollowing:
1. D awbacks in he selec ion o he expe
g oup: expe s’ goals did no co espond
wi h he goal o he esea ch (confl ic o
in e es s), unsound examina ion.
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59
2, XVIII, 2015
Business Adminis a ion and Managemen
2. A confl ic o opinion exis s. In o de o
disco e di e en poin s o iew, he expe s
need o be g ouped acco ding o how close
hei e alua ions a e. I such g ouping p o es
success ul, s a is ical p ocessing has o be
pe o med o each g oup sepa a ely.
3. Mis akes in he ex o he ques ionnai e,
e.g., ambiguous in e p e a ion o ques ions
o use o specifi c wo ds.
4. In oduc ion in o he ques ionnai e byway
objec s. Insu fi cien con o mi y o expe s’
e alua ions does no allow o he g oup
e alua ions o all objec s o be conside ed
as eliable. I his si ua ion occu s, hose
e alua ions will need o be excluded and he
esul s ep ocessed.
Depending on he goals o he expe
e alua ion, he ollowing main asks a e equi ed
o p ocess he su ey esul s: 1) de e mine
expe s’ compe ences and gene alised
e alua ions o objec s, 2) ank he objec s, 3)
de e mine con o mi y in he expe s’ opinions,
Fig. 1: Expe p ope ies and me hods o assessmen
Sou ce: own
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60 2015, XVIII, 2
Ekonomika a managemen
and 4) de e mine he ela ionships among
he anged objec s. The ollowing sec ion will
desc ibe he indi idual poin s ele an o he
ask we a e sol ing.
3.1 E alua ion o Expe
Compe ence in he Gene alised
E alua ion o Objec s
The fi s p e equisi e o ensu e eliabili y o he
examina ion esul s is o in i e expe s who a e
in e es ed in he esul s o he examina ion.
Concu en ly, he goals o expe s ha e o
co espond wi h he goal o he examina ion, in
gene al.
I is clea ha in p esen -day condi ions,
o mal indica o s o expe s (job i le,
science deg ee, wo k expe ience, numbe o
publica ions, e c.) can be used only as seconda y
c i e ia in iden i ying expe s’ o al compe ence
ha efl ec s hei o e all p o essional skills
and quali ies. When using he sel -e alua ion
me hod, he expe p o ides in o ma ion abou
he fi elds he o she is mos compe en in [22]. I
ollows ha o e alua e expe s’ compe ences;
se e al main me hods could be used: sel -
e alua ion, e alua ion o a colleague’s
compe ence, es ing o he expe s, and he
e alua ion o hem by he o ganize s o he
examina ion based on p e ious examina ions.
The me hods lis ed abo e belong o so-called
ex e nal me hods wi h espec o he conduc ed
examina ion. Howe e , he me hod o sel -
e alua ion o compe ence a es he deg ee o
he expe ’s sel -confi dence a he han hei eal
compe ence. Simila ly, du ing he e alua ion
me hod, o he people’s compe ence and he
g oup’s awa eness abou each o he ’s abili ies
play a ole. As can be seen, each me hod has
i s d awbacks. O he me hods o e alua ion o
expe s’ compe ences use pos e io da a, o
he esul s om he e alua ion o objec s. He e,
expe s’ compe ences a e e alua ed by he
deg ee o con o mi y o hei e alua ions o he
g oup e alua ion o objec s [22]. The essence o
his app oach lies in he ac ha expe s who
ha e exp essed con adic o y opinions ecei e
low g ades o compe ence, and consequen ly,
hei e alua ions play a less impo an ole
when de e mining he g oup e alua ion. When
an expe ’s e alua ion is close o he g oup’s
e alua ion, he compe ence o his expe is
ea ed as highe [21] and his ac could be used
as a way o expe s’ compe ence de e mining. I
should be no ed, ha g ope opinion o expe s
wi h close o e all compe ence le el would ha e
highe con o mi y [27].
3.1.1 E alua ion Based on Objec i e and
Subjec i e Pa ame e Assessmen
To p e en he esul s o he sel -e alua ion
me hod om being a me e efl ec ion o an
expe ’s sel -confi dence, i is possible o use
app oaches [9] ha p o ide an objec i e
cons i uen o knowledge abou he expe ’s
compe ence (Tab. 1).
I is ad isable o de e mine an index o
ela i e sel -e alua ion by an expe based on
he deg ee o hei pa icipa ion in elabo a ing
he p oblem as a complex coe fi cien , which
exp esses he ela ionship be ween he expe
and he examina ion, hei pa icipa ion and
hei in e es . Fo each ques ion o g oup o
ques ions on which expe ’s compe ence should
be e alua ed, he e is a co esponding scale
called he “ ela i e sel -e alua ion o expe ” in
he able o expe e alua ions.
To p e en he g ades in he scale om
infl uencing he sel -e alua ion, he ela i e
sel -e alua ion o expe scale con ains a lis
o expe compe ence p ope ies wi hou any
g ades.
Wi h his app oach, he expe has o
unde line he p ope ies ha , in his o he
opinion, de e mine he le el o his o he
pe sonal compe ence. The g ades [9] a e
added by he wo king g oup while analysing he
collec ed ques ionnai es (Tab. 1).
3.1.2 E alua ion o Expe Awa eness and
His o He Rele ance o Knowledge
Ano he way (Tab. 2) o de e mine an expe ’s
weigh ing ac o is ia he index o amilia i y
wi h he ask. I is calcula ed on he basis o an
expe ’s e alua ion o hei own amilia i y wi h
he p oblem and indica ion o ypical sou ces
o a gumen s o suppo hei opinions (index
o a gumen a ion, esul s om summing up he
g ades in he e e ence able, index o amilia i y
wi h he p oblem and esul s om he expe ’s
sel -e alua ion exp essed on a 10-g ade scale
and mul iplied by 0.1 wi h he pu pose o b inging
he alue o one). In gene al, he ela i e sel -
e alua ion o expe index is designed o make
he expe pe o m a sel -e alua ion o his o he
own compe ence on he gi en ques ion.
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Business Adminis a ion and Managemen
Objec i e e alua ion Subjec i e e alua ion
w1w2w3w4w5
Job posi ion
G ades
Educa ion
G ades
To al wo k expe ience
(yea s)
G ades
Wo k expe ience in
he p oblem a ea
G ades
Le el o pa icipa ion
in he p oblem
G ades
Head o
o ganisa ion 1.0 Ph.D. 1.0 >10 1.0 >10 1.0 Expe specialises in he gi en
issue 1.0
Depu y head 0.8
Highe
educa ion
(mas e )
0.8 10-5 0.8 10-5 0.8
Expe pa icipa es in p ac ical
wo k on sol ing he issue,
bu he issue does no belong
o he expe ’s indica ed
specialisa ion
0.8
Head o
depa men 0.6
Highe
educa ion
(bachelo )
0.6 <5 0.6 <5 0.6 The issue belongs o he
expe ’s specialisa ion 0.6
Depu y head
o depa men 0.4 less 0 0 0 0 0 The issue does no belong o
he expe ’s specialisa ion 0.3
Sou ce: [9]
w6,j Sou ces o a gumen s
Le el o sou ce’s infl uence on he expe ’s opinion
Indica o s and
hei weigh s
I ead o en
and egu-
la ly
I ead
o en, bu
no egu-
la ly
I ead
seldom
I do no
ead a all
100% 75% 20% 0%
w6,1 Summa ising pape s by local
au ho s 0.250 0.187 0.050 0
w6,2 Summa ising pape s by o eign
au ho s 0.250 0.187 0.050 0
w6,3 Pa en in o ma ion 0.250 0.187 0.050 0
w6,4 Companies’ epo s (ca alogues,
b ochu es, ecommenda ions, e c.) 0.250 0.187 0.050 0
Sou ce: own
Tab. 1: Ques ionnai e o e alua ion o expe ’s compe ence
Tab. 2: Re e ence able o indices o a gumen a ion (w6,j)
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62 2015, XVIII, 2
Ekonomika a managemen
4
66,
1
1
4j
j
WW


(2)
P ac ical esea ch on expe polls show
ha al hough sel -e alua ion me hods a e no
su fi cien as he sole c i e ion o de e mining
expe compe ence, hei applica ion p o ides
a mo e well- ounded selec ion and e alua ion
o he expe s [9]. To sol e he p oblem o
se ing he weigh coe fi cien s o expe s and,
hus, de e mining he p obabili y o ob aining
eliable e alua ions, we p opose o c ea e
a comp ehensi e me hod based on he
app oach ha combines a ious compe ence
e alua ion me hodologies: a sel -e alua ion o
expe s abou hei own compe ence on he
p oblem; an in oduc ion o g ades o objec i e
da a and an app ecia ion o he index o
a gumen a ion. The eby, he compe ence index
o an expe can be ea ed as a p obabili y o
he expe ’s gi ing a eliable e alua ion, whe e
0 ≤ We ≤ 1.
4. Resul s and Discussion
4.1 De e mining he Quali y o he
Expe G oup
The me hodology was used o he selec ion o
expe s o he p opose o a ional selec ion o
la ge medical equipmen such as, compu ed
omog aphy (CT), mammog aphic digi al
X- ay sys ems (MAM), magne ic esonance
imaging (MRI), adiog aphic/fl uo oscopic
sys ems (gene al pu pose) (RFS), ul asonic
scanning sys ems (ca diac) (USC) and
ul asonic scanning sys ems (gene al pu pose)
(USG). The lis o mos heal h ca e acili ies
o depa men s in he Czech Republic whe e
CT, MAM, MRI, RFS, USC and USG a e
loca ed was o med. Po en ial expe s we e
asked o answe he web-based ques ionnai e.
The pu pose o expe s g oups’ c ea ion was
p esen ed in each ques ionnai e. Candida es
o he expe s we e manage s (heads o
depa men s, heads o clinics, e c.) and
employees (physicians, biomedical enginee s,
adiological assis an s, senio echnicians, e c.)
om he depa men s o adiology, imaging
me hods, adio diagnos ics, in e en ional
adiology, depa men s o ca diology and he
Ins i u e o adiology and he o he depa men s
in hospi als o all le els o o ganisa ion and all
egions o he Czech Republic. The selec ion
o expe s was conduc ed wi h 872 employees
om 422 heal h acili ies in he Czech Republic
(Tab. 3).
The me hod o selec ing he mos
knowledgeable expe s o he ask o selec ing
and p ocu ing medical equipmen o hospi als
is based on 1) he expe ’s o e all wo k
expe ience, 2) expe ience in sol ing asks,
3) le el o educa ion and scien ifi c eco d,
4) in e es in sol ing he pa icula ask, 5)
cu en posi ion and 6) awa eness o how o
sol e he ask. This s udy also conside ed he
The ask
The numbe
o heal h ca e
acili ies’ s a ed
po en ial expe s
The numbe
o ques ionnai es
sen
The numbe o e-
sponses
Selec ion o MRI 34 60 19 (31.7%)
Selec ion o mammog aphic digi al
X- ay sys ems 68 125 18 (14.4%)
Selec ion o USC 101 190 22 (11.6%)
Selec ion o CT 89 162 15 (9.3%)
Selec ion o USG 116 116 9 (7.0%)
Selec ion o RFS 14 219 13 (6.0%)
To al 422 872 96 (11.0%)
Sou ce: own calcula ions
Tab. 3: The pa icipan s o he su ey
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Business Adminis a ion and Managemen
7) ele ance o he expe ’s knowledge and
8) he o e all sel -e alua ion conce ning hei
o al compe ence in sol ing he ask.
The da a ob ained om he ques ionnai e
o expe s did no ollow a no mal (Shapi o-
Wilk es ) dis ibu ion (p < 0.001) (“Sou ce o
a gumen a ion” [p = 0.029] and “Sel - anking”
[p = 0.003]). An analysis o he esul s e ealed
(Mann-Whi ney U- es ) ha he e was no
eason o ejec he null hypo hesis ha he
in e -g oup alues o he compa ed ( o al
a ing wTR and sel - a ing wSR) cha ac e is ics
we e homogeneous (p = 0.285). A medium-
s eng h posi i e co ela ion (Spea man’s
ank co ela ion) was ound be ween he wo
measu es ( = 0.550, p < 0.001) (Fig. 5).
Examina ions o he co ela ions be ween
he componen s ha de e mine he o al weigh
o he expe s we e pe o med. The co ela ions
be ween “Wo k expe ience in he p oblem
a ea” and “Educa ion” ( = 0.268; p = 0.01) and
“Wo k expe ience in he p oblem a ea” and
“Job posi ion” ( = 0.342; p = 0.001) sugges
ha sol ing he ask o selec ing la ge medical
equipmen pa icipa ing po en ial expe s wi h
highe le el o educa ion and highe ope a ing
posi ions. The ask o selec ing la ge medical
equipmen is ca ego ised as a manage ial ask
should be sol ed by he mos expe ienced
p o essionals fi lling a manage ial ole.
The mode a e co ela ion be ween “Wo k
expe ience in he p oblem a ea” and “Sou ces
o a gumen s” ( = 0.394, p < 0.001) and he
weak co ela ion be ween “Wo k expe ience in
he p oblem a ea” and “Le el o pa icipa ion
in he p oblem” ( = 0.239, p < 0.022), as well
as “Sou ces o a gumen s” and “Job posi ion”
( = 0.231, p = 0.027), indica e ha highe le els
o expe expe ience equa e o highe le els o
pa icipa ion in sol ing he ask, highe le els
o heo e ical p epa a ion and highe le els o
o e all compe ence.
The wSR index was ob ained as a esul
o expe s’ sel - ankings on a scale om ze o
(I am NOT compe en in add essing he issue o
selec ion) o 10 (I am compe en in add essing
he issue o selec ion). The wSR mos closely
co ela ed wi h “Wo k expe ience in he p oblem
a ea” ( = 0.519, p < 0.001), ha is, 52% o he
gene al weigh ing ac o consis s o he expe s’
«Wo k expe ience in he p oblem a ea». The nex
pa ame e s mos closely co ela ed o he wSR
we e he expe s’ le els o a gumen a i eness
( heo e ical p epa a ion, sou ce o a gumen s
and awa eness) ( = 0.440, p < 0.001), “Job
posi ion” ( = 0.319, p = 0.002) and “Educa ion”
( = 0.280, p = 0.007). The p esence o he
abo e co ela ions indica es ha he index o
expe s’ sel - ankings is dependen on “Wo k
expe ience in he p oblem a ea”, “Sou ces o
a gumen s”, “Job posi ion” and “Educa ion”.
A s a is ically signifi can associa ion was no
de ec ed be ween wST and he expe s’ o al
wo k expe ience (p = 0.089) o wSR and le el
o expe s’ pa icipa ion in he p oblem sol ing
ask o selec ing medical equipmen (p = 0.200).
Fig. 2 shows ha he leas sensi i e (less
a ying, depending on he expe ) indica o s
we e “To al wo k expe ience”, “Educa ion”, “Wo k
expe ience in he p oblem a ea” and “Le el o
pa icipa ion in he p oblem”. These esul s a e
indica i e o he ac ha specialis s wi h a high
le el o educa ion and high-quali y posi ions,
whose wo k was ela ed o he p oblem o
selec ion, we e p e-selec ed as expe s.
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64 2015, XVIII, 2
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Fig. 2:
The lis o expe s in o de by hei comp ehensi e assessmen o compe ence
( alues ob ained om he e alua ion o expe s on he objec i e and subjec i e
c i e ia and e alua ion o hei own opinions abou hei own compe ence)
Sou ce: own calcula ions
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65
2, XVIII, 2015
Business Adminis a ion and Managemen
4.2 The O e all Weigh o Expe s’
Compe ence
Fou di e en calcula ion models (Fig. 3) o
he o al compe ence weigh ing ac o we e
in es iga ed o de e mine he fi nal model o
calcula ing he o al weigh o compe ence o
each expe .
In he fi s me hod:

(1)
1,
2
eSTTR
Www
(3)
whe e
1
1,
n
TR i
i
ww
n



(4)
he weigh o each o he coe fi cien s (wST and
wTR [ o mula 4]) a e conside ed equal, i.e., he
con ibu ion o each o he coe fi cien s o he
o al weigh We
(1) is he same (as in We
(2) and
We
(3)) (Fig. 5). Since he a i hme ic mean is no
a obus s a is ic (is subjec o s ong infl uence
o la ge de ia ions), We
(1) inc easingly elies on
he unce ain y o wST (Fig. 6-B).
The second me hod o calcula ion
(2) 2 2
,
eSTTR
Www
(5)
is an adap a ion o he calcula ion o he A- ype
unce ain y measu emen in a calib a ion,
whe e he inpu alues a e co ela ed, as in
his case ( = 0.55, p < 0.001) (Fig. 5). The wTR
is iewed as unce ain y in he assessmen o
compe ence ob ained on he basis o objec i e
and subjec i e pa ame e s. The wST is iewed
as he unce ain y con ibu ed by o he
unaccoun ed ac o s. The expe s’ weigh ing
ac o s ob ained by his me hod we e e y
accu a e ep oduc ions o he es ima e We
(1)
( = 0.998, p < 0.001) (Fig. 6-B, Fig. 6-C) and
ai h ully ep oduced he es ima es o wST and
wTR.
Fig. 3: The equi y s uc u e o he o al weigh 1 – We
(1), 2 – We
(2), 3 – We
(3) and 4 – We
(4)
Sou ce: own calcula ions
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72 2015, XVIII, 2
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Abs ac
METHOD FOR SELECTING EXPERT GROUPS AND DETERMINING
THE IMPORTANCE OF EXPERTS’ JUDGMENTS FOR THE PURPOSE OF
MANAGERIAL DECISION-MAKING TASKS IN HEALTH SYSTEM
Ilya I le , Pe e Kneppo, Mi osla Ba ák
This wo k aims o de elop a me hodology o de e mining he quali a i e composi ion o an expe
g oup and he weigh ing ac o ega ding he impo ance o expe ’s judgmen s o he pu pose o
pa icipa ing in decision-making. I is based on he expe ’s o e all wo k expe ience, expe ience
in sol ing asks, le el o educa ion and scien i i c eco d, in e es in sol ing he pa icula ask,
cu en posi ion and awa eness o how o sol e he ask. This s udy also conside ed he ele ance
o he expe ’s knowledge and he o e all sel -e alua ion conce ning hei o al compe ence in
sol ing he ask. Fo he pu pose o alida ing he me hodology, 96 po en ial expe s (physicians,
biomedical enginee s, adiological assis an s, medical physicis s, e c.) om 72 heal h acili ies in
he Czech Republic we e in e iewed h ough a web-based ques ionnai e. The calcula ion model
ha was selec ed was able o elimina e e o s in es ima ing he p opo ionali y o ex eme alues
and educes he impac o unce ain y in he expe s’ o e all sel -e alua ions conce ning hei o al
compe ence. A s a is ically signi i can co ela ion was ound be ween he complex weigh ing ac o
and he ollowing cha ac e is ics: he expe ’s expe ience in dealing wi h simila asks ( = 0.512,
p < 0.001), he expe ’s heo e ical backg ound (awa eness) and he ele ance o he expe ’s
knowledge ( = 0.440, p < 0.001), he expe ’s cu en posi ion ( = 0.319, p = 0.002) and he le el o
his o he educa ion and scien i i c eco d ( = 0.280, p = 0.007). The de eloped me hodology may
be especially use ul in scien i i c and echnological o ecas ing, medical and manage ial decision-
making, quali y assessmen and ope a ional esea ch.
Key Wo ds: G oup decision making; expe ; expe selec ion c i e ia; medical equipmen ; sel -
assessmen ; weigh ing ac o .
JEL Classi i ca ion: C44, D81, I11.
DOI: 10.15240/ ul/001/2015-2-005
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