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  1. See KF, Yen SH
    Health Econ Rev, 2018 Dec 21;8(1):33.
    PMID: 30578526 DOI: 10.1186/s13561-018-0214-6
    BACKGROUND: The main objective of this study is to assess the performance of the global health system, emphasising the contribution of people's happiness to health system efficiency across countries. Technical efficiency (TE) scores are estimated using the output-oriented variable returns to scale (VRS) data envelopment analysis (DEA) model based on the input measures: health expenditure, labour, hospital beds and education, and the output measures: healthy life expectancy and inverse mortality index. The efficiency scores are regressed against three explanatory variables: happiness index, population density, and healthcare share of gross domestic product (GDP). The analysis involved 121 selected countries using double bootstrap DEA as proposed by Simar, L., Wilson, P.W J Econ 136:1‑34, 2007.

    RESULTS: The bootstrap truncated regression indicates that happiness is one of the factors that contributes significantly to health system efficiency. The study also revealed that the selected health systems perform well, on average, in terms of population density and healthcare share of GDP.

    CONCLUSIONS: In addition to improving the economic standard of living, policy-makers should also consider ways to increase the happiness and well-being of society. Policies focusing on well-being and happiness can lead to improved well-being and improved health outcomes, which may ultimately reduce the healthcare burden and enhance healthcare performance.

  2. Hamzah NM, See KF
    Health Care Manag Sci, 2019 Sep;22(3):462-474.
    PMID: 30868325 DOI: 10.1007/s10729-019-09470-8
    Various pharmacy services are offered in public health facilities, ranging from distributive activities (dispensing) to patient-oriented services (pharmaceutical care). These activities are monitored through indicators established at the national level. In Malaysia, the indicators have not been transformed into a measurement of hospital pharmacy service efficiency. The main objectives of this study were to assess the relative performance of hospital pharmacy services and to investigate the factors that may affect the performance levels. Double-bootstrap data envelopment analysis was applied to measure the technical efficiency levels of 124 public hospital pharmacies in 2014. An input-oriented variable returns to scale model was adopted in the study, while bootstrap truncated regression was conducted to identify the factors that may explain the differences in the efficiency levels. The average bias-corrected technical efficiency score varies according to the hospital size (0.84, 0.78 and 0.82 in small, medium and large hospitals, respectively). The hospital size, hospital age, urban location and information technology are important determinants of the efficiency levels. The study contributes to establishing baseline technical efficiency information for public hospital pharmacy services in Malaysia. The measurement of hospital pharmacy efficiency can guide future policy making to improve performance and ensure the optimum level of available resources.
  3. Md Hamzah N, See KF
    BMC Health Serv Res, 2021 Oct 19;21(1):1119.
    PMID: 34663311 DOI: 10.1186/s12913-021-06786-6
    BACKGROUND: Policymakers are faced with the challenge of balancing patient's access for effective and affordable medicines to sustain the rising healthcare costs. In a mixed healthcare market such as Malaysia, coverage decisions of new medicines are different: public funded health system has a formulary listing process whereas for private sector, which is a market-based economy, depends on patient's willingness to pay and insurance coverage. There is little overlap between public and private healthcare service delivery with access to new innovative medicines, as differentiated by sources of funding. The objectives of this study were to examine the diffusion of New Chemical Entities (NCEs) into the public and private healthcare market between 2010 and 2014, and determine the factors explaining the diffusion.

    METHODS: We matched medicines from the product registration database by medicine formulation to medicines in IQVIA National Pharmaceutical Audit database for each year. The price per Defined Daily Dose (DDD), market concentration and generic utilization share variables were calculated. A panel fixed effect model was performed to measure diffusion of NCEs for each year and test possible determinants of diffusion of NCEs for overall market and sector specifics.

    RESULTS: The utilization of NCEs was larger in the private sector compared to the public sector but the speed of diffusion over time was higher in the public sector. Price per DDD was negatively associated with diffusion of NCEs, while generic utilization share was significantly regressive in the public sector. Market concentration was negatively associated with utilization of NCEs, however result tends to be mixed according to sector and Anatomical Therapeutic Chemical (ATC) category.

    CONCLUSIONS: Understanding key aspects of sectoral variation in diffusion of NCEs are crucial to reduce the differences of access to new medicines within a country and ensure resources are used on cost effective treatments.

  4. Md Hamzah N, Yu MM, See KF
    Health Care Manag Sci, 2021 Jun;24(2):273-285.
    PMID: 33651316 DOI: 10.1007/s10729-020-09539-9
    Malaysia was faced with a life-threatening crisis in combating COVID-19 with a number of positive cases reaching 5305 and 88 deaths by 18th April 2020 (the first detected case was on 25th January 2020). The government rapidly initiated a public health response and provided adequate medical care to manage the public health crisis during the implementation of movement restrictions, starting 18th March 2020, throughout the country. The objective of this study was to investigate the relative efficiency level of managing COVID-19 in Malaysia using network data envelopment analysis. Malaysia state-level data were extracted from secondary data sources which include variables such as total number of confirmed cases, death cases and recovered cases. These variables were used as inputs and outputs in a network process that consists of 3 sub processes i) community surveillance, ii) medical care I and iii) medical care II. A state-level analysis was performed according to low, medium and high population density categories. The efficiency level of community surveillance was highest compared to medical care processes, indicating that the overall inefficiency is greatly influenced by the inefficiency of the medical care processes rather than the community surveillance process. Results showed that high-density category performed well in both community surveillance and medical care II processes. Meanwhile, low-density category performed better in medical care I process. There was a good overall performance of the health system in Malaysia reflecting a strong preparedness and response level to this pandemic. Furthermore, resource allocation for rapid response was distributed effectively during this challenging period.
  5. Shafie AA, Mohammed NS, See KF, Ibrahim HM, Wong JHY, Chhabra IK
    Health Econ Rev, 2022 Jan 26;12(1):9.
    PMID: 35080678 DOI: 10.1186/s13561-021-00351-x
    BACKGROUND: Optimizing efficiency has become increasingly critical with the growing demand for finite healthcare resources driven by population growth and an ageing society. Hence, policymakers are urgently finding more efficient ways to deliver health services. Thalassemia is a complex inherited blood disorder with significant prevalence in Malaysia. The high number of patients put substantial strain on the healthcare system. This study aims to evaluate the technical efficiency of thalassaemia care centres throughout Malaysia and the determinants that affect the efficiency.

    METHOD: Data from 30 public hospitals with thalassaemia care centres were collected. A double bootstrap data envelopment analysis (DEA) approach is used with the assumption of input-oriented and variable-to-scale DEA models to generate technical efficiency scores. Bootstrap truncated regression was later conducted to identify the factors affecting the efficiency scores.

    RESULTS: The mean bias-corrected technical efficiency score has improved to 0.75 in 2017 from 0.71 in 2016. In both years, more than 50% of thalassaemia care centres showed good efficiency scores (0.8-1.0). Management factors that affect the efficiency scores include separation of patient management (β = 0.0653) and budget (β = 0.0843), where they are found to positively affect the efficiency scores. In contrast, having longer operating hours is found to inversely influence the performance levels (β = - 0.4023).

    CONCLUSIONS: The study provides a pioneering framework to evaluate the technical efficiency of thalassaemia treatment centres in public healthcare settings and could provide a useful guide for policymaker and thalassaemia care centre managers to improve efficiency in service delivery to thalassaemia patients and their caregivers without compromising quality of care.

  6. Handoyo RD, Ibrahim KH, Rahmawati Y, Faadhillah F, Ogawa K, Kusumawardani D, et al.
    PLoS One, 2024;19(1):e0296431.
    PMID: 38165859 DOI: 10.1371/journal.pone.0296431
    This study explores the determinants of the export performance of Indonesia's low-, medium-, and high-technology manufacturing industries by focusing on the role of raw-material imports and technical efficiency. Micro firm-level data from 2010-2015 were utilized for the analysis in this study. The stochastic frontier analysis was employed to measure technical inefficiency and to determine its effect on export performance. Our findings indicate that in all categories of industry technical efficiency, raw materials imports, foreign direct investment (FDI), location, firm size, labour productivity, and concentration of industries were significant determinants of export performance. While high efficiency increases exports in low- and medium-technology firms, exports decrease in firms with high efficiency accompanied by high imports, FDI, size, and labour productivity. Furthermore, in high-technology industries, efficiency reduces exports and again increases them when mediated by a concentration of industries and location. The empirical strategy also supports the positive effect of imports on export performance in both industries, which also aligns with decreased exports in firms with high imports accompanied by high FDI, efficiency, labour productivity, the concentration of industries, and size. To this end, the study has implications for low-, medium-, and high-technology manufacturing that are mainly concerned with increasing exports.
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