Decision making in management for large medical equipment

Decision making in management for large

medical equipment

Ilya Ivlev and Peter Kneppoilya.ivlev@fbmi.cvut.cz

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.

Thank you

ilya.ivlev@fbmi.cvut.cz