METHODS: A cross-sectional study was employed involving 239 ambulances from selected hospitals and clinics. Ambulance service utilization was based on the number of trips, distance and duration of travel obtained from travel logbooks. A mixed top-down and activity-based costing approach was used to estimate the monthly cost of ambulance services. This constituted personnel, maintenance, fuel, overhead, consumables, ambulance, and medical equipment costs. The utilization and costs of ambulance services were further compared between settings and geographical locations.
RESULTS: The average total cost of ambulance services was MYR 11,410.44 (US$ 2,756.14) for hospitals and MYR 9,574.39 (US$ 2,312.65) for clinics, albeit not significantly different. Personnel cost was found to be the main contributor to the total cost, at around 44% and 42% in hospitals and clinics, respectively. There was however a significant difference in the total cost in terms of the type and age of ambulances, in addition to their location. In terms of service utilization, the median number of trips and duration of ambulance usage was significantly higher in clinics (31.88 trips and 58.58 hours) compared to hospitals (16.25 trips and 39.25 hours).
CONCLUSIONS: The total cost of ambulance services was higher in hospitals compared to clinics, while its utilization showed a converse trend. The current findings evidence that despite the ambulance services being all under the MOH, their operating process and utilization reflected an inherent difference by setting.
METHODS: A Markov model was developed to estimate the cost and outcomes ambulance replacement strategies over a period of 20 years. The model was tested using two alternative strategies of 10-year and 15-year. Model inputs were derived from published literature and local study. Model development and economic analysis were accomplished using Microsoft Excel 2016. The outcomes generated were costs per year, the number of missed trips and the number of lives saved, in addition to the Incremental Cost-Effectiveness Ratio (ICER). One-Way Deterministic Sensitivity Analysis (DSA) and Probabilistic Sensitivity Analysis (PSA) were conducted to identify the key drivers and to assess the robustness of the model.
RESULTS: Findings showed that the most expensive strategy, which is the implementation of 10 years replacement strategy was more cost-effective than 15 years ambulance replacement strategy, with an ICER of MYR 11,276.61 per life saved. While an additional MYR 13.0 million would be incurred by switching from a 15- to 10-year replacement strategy, this would result in 1,157 deaths averted or additional live saved per year. Sensitivity analysis showed that the utilization of ambulances and the mortality rate of cases unattended by ambulances were the key drivers for the cost-effectiveness of the replacement strategies.
CONCLUSIONS: The cost-effectiveness model developed suggests that an ambulance replacement strategy of every 10 years should be considered by the MOH in planning sustainable EMS. While this model may have its own limitation and may require some modifications to suit the local context, it can be used as a guide for future economic evaluations of ambulance replacement strategies and further exploration of alternative solutions.
METHODS: This cross-sectional study analyzed the efficiency of 76 Decision-Making Units (DMUs) or health facilities, consisting of 62 health clinics and 14 hospitals. Data Envelopment Analysis (DEA) was used for computing efficiency scores while adopting the Variable Return to Scale (VRS) approach. The analysis was based on input orientation. The input was the cost of ambulance services, while the output for this analysis was the distance coverage (in km), the number of patients transferred, and hours of usage (in hours). Subsequent analysis was conducted to test the Overall Technical Efficiency (OTE), the Pure Technical Efficiency (PTE), the Scale Efficiency (SE), and the Return to Scale with the type of health facilities and geographical areas using a Mann-Whitney U-test and a chi-square test.
RESULTS: The mean scores of OTE, PTE, and SE were 0.508 (±0.207), 0.721 (±0.185), and 0.700 (±0.200), respectively. Approximately, 14.47% of the total health facilities were PTE. The results showed a significant difference in OTE and SE between ambulance services in hospitals and health clinics (p < 0.05), but no significant difference in PTE between hospitals and clinics (p>0.05). There was no significant difference in efficiency scores between urban and rural health facilities in terms of ambulance services except for OTE (p < 0.05).
DISCUSSION: The ambulance services provided in healthcare facilities in the MOH Malaysia operate at 72.1% PTE. The difference in OTE between hospitals and health clinics' ambulance services was mainly due to the operating size rather than PTE. This study will be beneficial in providing a guide to the policymakers in improving ambulance services through the readjustment of health resources and improvement in the outputs.
METHODS: This was an observational manikin-based study. A total of 96 participants as well as two types of mechanical compression devices: Lucas-2 and AutoPulse, performed one minute of continuous chest compression on BT-CPEA programmed manikin while the ambulance travelled at different speeds, i.e., idle state, 30km/hr and 60km/hr. Seven outcome variables of chest compression were measured. Performance data of different groups of compressor were compared and analysed using repeated measures analysis of variance (ANOVA).
RESULTS: In manual chest compression, significant variation were noted among different speeds in term of average compression rate (p<0.001), average compression depth (p=0.007), fraction of adequate/insufficient compression depth and fraction of normal hands positioning with p=0.018, 0.022 and 0.034 respectively. Overall, AutoPulse and Lucas-2 were not affected by ambulance speed. Lucas- 2 showed more consistent average compression rate, higher fraction of adequate compression depth and reduced fraction of insufficient compression depth as compared to manual compression with p<0.001, 0.001 and 0.043 respectively.
CONCLUSION: In this study we found that ambulance speed significantly affected certain aspects of manual chest compression most notably compression depth, rate and hand positioning. AutoPulse and Lucas-2 can improve these aspects by providing more consistent compression rate, depth and fraction of adequate compression depth during transport.