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: The DEA was performed using countries as decision-making units, schizophrenia disease investment (cost of disease as a percentage of total health care expenditure) as the input, and disability-adjusted life years (DALYs) per patient due to schizophrenia as the output. Data were obtained from the Global Burden of Disease 2017 study, the World Bank Group, and a literature search of the PubMed database.
RESULTS: Data were obtained for 44 countries; of these, 34 had complete data and were included in the DEA. Disease investment (percentage of total health care expenditure) ranged from 1.11 in Switzerland to 6.73 in Thailand. DALYs per patient ranged from 0.621 in Lithuania to 0.651 in Malaysia. According to the DEA, countries with the most efficient schizophrenia health care were Lithuania, Norway, Switzerland and the US (all with efficiency score 1.000). The least efficient countries were Malaysia (0.955), China (0.959) and Thailand (0.965).
LIMITATIONS: DEA findings depend on the countries and variables that are included in the dataset.
CONCLUSIONS: In this international DEA, despite the difference in schizophrenia disease investment across countries, there was little difference in output as measured by DALYs per patient. Potentially, Lithuania, Norway, Switzerland and the US should be considered 'benchmark' countries by policy makers, thereby providing useful information to countries with less efficient systems.
Design/methodology/approach: This study uses multi-directional efficiency analysis to measure the technical inefficiency scores on a sample of 200 farm observations and single-bootstrap truncated regression model to define factors affecting technical inefficiency.
Findings: Managerial and program inefficiency scores are presented for intensive and semi-intensive production systems. The results reveal marked differences in the inefficiency scores across inputs and between production systems.
Practical implications: Intensive systems generally have lowest managerial and program inefficiency scores in the Malaysian dairy farming sector. Policy makers could use this information to advise dairy farmers to convert their farming system to the intensive system.
Social implications: The results suggest that the Malaysian Government should redefine its policy for providing farm finance and should target young farmers when designing training and extension programs in order to improve the performance of the dairy sector.
Originality/value: The existing literature on Southeast Asian dairy farming has neither focused on investigating input-specific efficiency nor on comparing managerial and program efficiency. This paper aims to fill this gap.
DESIGN/METHODOLOGY/APPROACH: This study has been carried out by using a methodology combining an in-depth literature review with a comparison framework, which is called as the "Framework for Comparing Business Process Improvement Methods." The framework is composed of seven dimensions and has been adapted from four recognized, related frameworks. In addition to the in-depth review of related literature and the adapted comparison framework, researchers have conducted several interviews with healthcare BPI practitioners in different hospitals, to attain their opinions of BPI methods and tools used in their practices.
FINDINGS: The main results have indicated that significant improvements have been achieved by implementing BPIMs in the healthcare domain according to related literature. However, there were some shortfalls in the existing methods that need to be resolved. The most important of these has been the shortfall in representing and analyzing targeted domain knowledge during improvement phases. The tool currently used for representing the domain, specifically flowcharts, is very abstract and does not present the domain in a clear form. The flowchart tool also fails to clearly present the separation of concerns between business processes and the information systems processes that support a business in a given domain.
PRACTICAL IMPLICATIONS: The findings of this study can be useful for BPI practitioners and researchers, mainly within the healthcare domain. The findings can help these groups to understand BPIMs shortfalls and encourage them to consider how BPIMs can be potentially improved.
ORIGINALITY/VALUE: This researchers of this paper have proposed a comparison framework for highlighting popular BPIMs in the healthcare domain, along with their uses and shortfalls. In addition, they have conducted a deep literature review based on the practical results obtained from different healthcare institutions implementing unique BPIMs around the world. There has also been valuable interview feedback attained from BPI leaders of specific hospitals in Saudi Arabia. This combination is expected to contribute to knowledge of BPIMs from both theoretical and practical points of view.