decision making in management for large medical equipment
DESCRIPTION
Decision making in management for large medical equipment. Ilya Ivlev and Peter KneppoTRANSCRIPT
Number of MRI units per million population
Source: OECD Health Data
The difference in the availabilityof MRI
JapanMRI units/mill: 43,1
41
MexicoMRI units/mill: 1,5
Source: OECD Health Data
Financial losses in health care
Source: WHO “World health statistics 2010”
WHO: causes of inefficiency and recommendations
CAUSES OF INEFFICIENCY● EXCESSIVE PURCHASING and use of EQUIPMENT● Financial drain etc.
SOLUTION● DEVELOPMENT OF SYSTEMS SELECTION AND PROCUREMENT● Control government expenditure on health care● Implementing new regulations etc.
Source: WHO “The world health report: health systems financing: the path to universal coverage 2010”
Development of a system for rational choice of large medical equipment
Difficulties in decision making
Suppler policies
difference in purchase price
heterogeneous information
about the units
Objectives of the application
specialization of health
facility
Specifi-cations
more than 900
specifications
difficult for understandin
g
Source: XJ., Zhou, How can I Purchase My Dream MRI Scanner?
Questionnaire for evaluation of expert's competence
Golupkov, Е., 1998
Reference table of indices of argumentation (ka)
Fedoraev, S.V., 2010
General competence index for a specific experts
hjo; hj
s - objective and subjective indiceskа – index of argumentationki – index of familiarity with the problem
Private weights of experts
The overall competence of the experts
0 1 2 3 4 5 6 7 8 90.40
0.45
0.50
0.55
0.60
0.65
0.708.00
7.006.00
5.00
4.00 3.00 2.00
1.00
Serial number of expert
Mai
n w
eigh
ting
coe
f-fic
ient
AHPMAUT;
ELECTRE
ease
AHPMAUT;
ELECTRE
ease adding new alternatives
AHPMAUT;
ELECTRE
adding new alternatives
no hard and preferences
ease
AHPMAUT;
ELECTRE
adding new alternatives
no hard and preferences
ease
level of preference
AHPMAUT;
ELECTRE
adding new alternatives
no hard and preferences
measurement of quality
ease
level of preference
AHPMAUT;
ELECTRE
adding new alternatives
no hard and preferences
measurement of quality
ease
level of preference
evaluation of inconsistency
AHPMAUT;
ELECTRE
ease
level of preference
evaluation of inconsistency
qualitative characteristics
adding new alternatives
no solid opinion
measurement of quality
Proposed decision hierarchy for MRI
Pairwise comparisons
Results of paired comparisons
serial number of the specifications
seria
l num
ber o
f the
spe
cific
ation
s
Mutual dependence of the characteristics
serial number of the specifications
seria
l num
ber o
f the
spe
cific
ation
s
Independent characteristicsDependent characteristics
Mutual dependence(network structure)
Ranked by priority list of MRI• SIEMENS MAGNETOM
Aera;• SIEMENS MAGNETOM
Avanto;• GE HEALTHCARE Optima
MR450w;• PHILIPS INTERA;• TOSHIBA1.5 T Vantage
Atlas;• PHILIPS Achieva;• PHILIPS Ingenia;• SIEMENS MAGNETOM
Espree…etc.
Examination design and the prediction of the characteristics weights
Summary• Method for experts' competence identification.• Defined the raked list of the experts.• AHP method with network elements can be
applied;• The way how to predict changes of weights.• Web-system for identification of experts'
preferences.• Defined a list of 16 key parameters.• Algorithm for selection of preferences of
experts, processing and evaluation of results.
