Modelling cost-effectiveness of replacement strategies for ambulance services in the Ministry of Health Malaysia

Table 2 Ambulance data for the Markov model

Variables	Values	Range	Alpha	Beta	Distribution
Transitional Probabilities ≤ 5 years
Functioning to functioning	0.980
Functioning to breakdown	0.020	0.016–0.024	24.480	1199.520	Beta
Functioning to BER^a	0.000
Breakdown to breakdown	0.250
Breakdown to functioning	0.375
Breakdown to BER^a	0.375	0.300–0.450	15.250	25.417	Beta
BER^a to Functioning (replacement)	1.000
Transitional Probabilities 6–10 years
Functioning to functioning	0.893
Functioning to breakdown	0.087	0.070–0.104	22.738	238.618	Beta
Functioning to BER^a	0.020
Breakdown to breakdown	0.161
Breakdown to functioning	0.129
Breakdown to BER^a	0.710	0.568–0.852	6.540	2.671	Beta
BER ^a to Functioning (replacement)	1.000
Transitional Probabilities > 10 years
Functioning to functioning	0.525
Functioning to breakdown	0.378	0.302–0.454	15.172	24.966	Beta
Functioning to BER^a	0.097
Breakdown to breakdown	0.016
Breakdown to functioning	0.141
Breakdown to BER^a	0.843	0.674–1.000	3.082	0.574	Beta
BER^a to Functioning (replacement)	1.000
Effectiveness Data
Ambulance utilization (number of trips) per year
≤ 5 years	555	444–666			Gamma
6–10 years	385	308–462			Gamma
>10 years	294	235–353			Gamma
Optimum utilization per year^b	555
Mortality rate without ambulance^c	0.04	0.032–0.048			Gamma
Other ambulance data
Number of Minor Maintenance per year
≤ 5 years	3
6–10 years	3
> 10 years	5
Number of Major Maintenance per year	1

^aBER stands for Beyond Economic Repair
^bOptimum utilization per year is based on the number of utilization of ambulances of age five years and less
^cMortality rate of patient unattended by ambulance [3]

ISSN: 1472-6963