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- Hindawi Publishing Corporation
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- Copyright © 2018 Mustapha D. Ibrahim and Sahand Daneshvar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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- 2040-2295
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- 10.1155/2018/2060138
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Abstract
Hindawi Journal of Healthcare Engineering Volume 2018, Article ID 2060138, 6 pages https://doi.org/10.1155/2018/2060138 Research Article Efficiency Analysis of Healthcare System in Lebanon Using Modified Data Envelopment Analysis Mustapha D. Ibrahim and Sahand Daneshvar Department of Industrial Engineering, Eastern Mediterranean University, North Cyprus, via Mersin 10, Turkey Correspondence should be addressed to Mustapha D. Ibrahim; mustapha.ibrahim@emu.edu.tr Received 12 December 2017; Accepted 4 June 2018; Published 2 July 2018 Academic Editor: John S. Katsanis Copyright © 2018 Mustapha D. Ibrahim and Sahand Daneshvar. )is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. )e inflow of refugees from Syria into Lebanon necessitates a robust and efficient healthcare system in Lebanon to withstand the growing demand for healthcare service. For this purpose, we evaluate the efficiency of healthcare system in Lebanon from 2000 through 2015 by applying a modified data envelopment analysis (DEA) model. We have selected four output variables: life expectancy at birth, maternal mortality ratio, infant mortality rate, and newly infected with HIV and two input variables: total health expenditure (% of GDP) and number of hospital beds. )e findings of the paper show improvement in the efficiency of the healthcare system in Lebanon after the widespread of the health system reform in 2005. It also shows that reduction in health expenditure does not necessarily reduce efficiency if operational and technical aspect of the healthcare system is improved. )e study infers that the healthcare system in Lebanon is capable of withstanding the increase in health demand provided further resources are made available and the existing technical and operational improvement are maintained. )e healthcare service of societies has improved im- 1. Introduction pressively over the past couple years, more so for the services provided for maternal and infant health, and improving live )e improvement of a population’s health is dependent on an equitable and efficient healthcare system [1]. Productivity expectancy. However, the increase of healthcare outcomes at of citizens depends on their health level, and higher rate national level may not necessarily translate to improvement of economic growth can be influenced by a more efficient of the indicators for some of the citizens who are predis- healthcare system [2]. In economies with both high develop- posed to sicknesses. In addition, the progress of some cases is ment index and medium development index, increase in ef- stagnant, and the improvements are insignificant. In this ficiency of expenditure seems to be the only way public context, the efficiency of financial infrastructure and human healthcare systems can overcome the pressure of expenditure resources in the health sector across Lebanon is a relevant [3]. Identifying areas of improvement in the healthcare system topic for researchers and health policy makers. )e growing concern for the efficiency of the healthcare necessitates evaluating the efficiency of the existing system. Evaluation of healthcare system is a complex process due to system in Lebanon is motivated by the inflow of refugees from Syria. According to the United Nations High Com- limited data and methodological complications. )e health status of the citizens has to be identified, which is influenced by missioner for Refugees (UNHCR), there are more than 1 their socioeconomic stability, productivity level, and welfare million Syrian refugees in Lebanon, 23% women and 51.6% level [1]. Researches are becoming increasingly focused on the are children, 18% of which are under five years old. )e efficiency of the healthcare system. Hellingsworth, in his review needs of the refugees have had enormous impact on the of 317 references on the efficiency of healthcare delivery in the public finance of Lebanon, increasing Government expen- context of frontier analysis, shows that only a few performed diture in public services and compounding the negative the analysis on the basis of macroperspective, which gives an economic consequences of the regional instability. )e insight into the overall healthcare system performance [4]. current humanitarian system has contributed in increasing 2 Journal of Healthcare Engineering system in the country in the context of the available selected the fragmentation of the Lebanese health system [5], rec- ognizing the fact that healthcare is needed and available variables. Most of the studies that are reviewed used life expectancy at birth as output and health expenditure as resources to satisfy the growing demand is limited. Going forward, it is important to maintain a viable healthcare inputs [11]. Other studies such as Alfonso and St. Aubyn system to satisfy the citizens and refugees. Efficiency im- [13] used number of beds and health employment as inputs. provement, cost reduction, and introduction of new tech- In a more recent study, Asandului et al. [1] and Medeiros nology will contribute to that effect [6]. )erefore, it is and Schwierz [14] analyzed the entire European states’ imperative for the healthcare system of Lebanon to operate healthcare system, the list of variables used were the efficiently in order to handle the increase in healthcare number of hospital beds per 1000, number of physicians per 1000, health expenditure % of GDP, life expectancy, demand. )e health sector priorities as identified by the national health policy include health service delivery and adjusted life expectancy, infant mortality, and health ex- penditure per capita. In this paper, similar indicators are strengthening the role of the ministry of public health as the principal steward. Providing universal health coverage to the used to estimate the performance of the healthcare system in Lebanon. national residents is a considerable step towards reform at the social level [7]. To ensure universal health coverage for the vulnerable )e healthcare system in Lebanon is diversified with Lebanese, Syrians, and Palestine refugees, the Lebanese public and private healthcare providers, financiers, political healthcare system needs to perform efficiently [5]. Getting agenda, and various laws and regulations [8]. National the data on the health status of the refugees is a challenging Social Security Fund (NSSF) was established in 1963 to task. However, the performance of the Lebanese healthcare provide employees and their dependents with national system should show their ability to withstand the increasing pressure as a result of the refugees’ impact on the existing insurance coverage for work-related incidents, maternity, sickness, and diseases. )e Ministry of Health financing system. Consequently, improving the efficiency and oper- ations of the existing healthcare system would impact the scheme insures the uninsured; the beneficiaries are ma- jority of the population, about (42.7%). )e scheme is healthcare services delivered to the refugees. funded by the government budget and covers 80% of the hospital bills as the direct payment with absolute coverage 2. Method of expensive intervention. Prior to 1975, Lebanon was the center for the entire region’s healthcare because of its 2.1. Data Envelopment Analysis. )is paper utilizes the data advance healthcare services and medical institutions. )e envelopment analysis (DEA) method developed by Charnes 1975 civil war caused enormous problems, and the treat- et al. [15] to evaluate the efficiency of the healthcare system ment of traumatic injuries overwhelmed the health sector. in Lebanon. It is a nonparametric linear programming )e health sector declined rapidly and was taken over by method that estimates the efficiency frontier of evaluated the private sector and nongovernmental organizations units known as decision-making units (DMUs). Emrouznejad (NGOs). Similar case can be made with the growing and Dey [16] highlighted the use of frontier methodologies number of refugees from Syria, hence the urgent need for and multicriteria decision-making for performance mea- a performance evaluation of the existing system and proper surement in the health sector. Cheng and Zervopoulos [17] improvement strategies for sustaining efficient services. evaluated health system using directional distance function in )e overall objective of this paper is to evaluate efficiency DEA. )eir analysis incorporates both desirable and un- and present efficiency improvement options of the desirable outputs of a health system. healthcare system in the context of finance, infrastructure, In this paper, in order to evaluate the relative efficiency and medical indicators. Lebanon has one of the most ex- of the healthcare system in Lebanon over a 16-year period pensive healthcare systems in the world [9]. Lebanon has (2000–2015), a modified DEA model developed by a high out of pocket health expenditure which leads to Daneshvar et al. [18] is employed. )e modified DEA model exposure of households to financial risk as a result of ill pays special attention to the weak efficient and highly in- health [10]. And the minimum public expenditure to efficient units. It proposes efficiency scores that do not primary healthcare compared to secondary and tertiary exaggerate the performance of the units at the weak part of health brings more burden to Lebanese and vulnerable the frontier under variable return to scale (VRS) assumption. population in particular. A performance measure of the )e modified DEA model used is as follows. health system in eastern Mediterranean region ranks Consider nDMUs (years in our case) with each DMU Lebanon as 17 out of 21 countries in health production and j(j � 1, . . . , n) using m inputs x � (x , x , . . . , x )> 0 to j 1j 2j mj determinants [11]. Ammar [12] presented a document produce s outputsy � (y , y , . . . , y )> 0. )e best j 1j 2j sj (health reform in Lebanon) stating the 12 key achievements weights for the variables are u for outputs and v for inputs. r i of the ministry of public health over a 10-year period. )e y and x are the input and output for a particular DMU j r0 i0 document points out an increase in performance of the under evaluation. )e steps for applying the modified DEA healthcare system, with improvement in supply of human model is as follows: first use model (1) on the entire DMUs, resources, strength of the primary healthcare system, and then use model (2) on only the DMUs with score � 1 quality and accreditation improvement, and autonomy of identified by model (1). Use (3) to find the upper bound for public hospitals among others. )e aim of this study is to u , in our case φ � 0.77. Finally, apply model (4) on the create some idea as to the present state of the healthcare entire DMUs to get the efficiency scores for each DMU: Journal of Healthcare Engineering 3 Table 1: Efficiency data. max u y + u r r0 0 Years DMUs x1 x2 y1 y2 y3 y4 r�1 m 2000 1 10.8616 2.93 74.4317 42 17.1 100 subject to v x � 1 2001 2 10.9044 3 74.9221 39 16.1 100 i i0 2002 3 10.0465 3.15 75.4147 36 15.1 100 i�1 s m 2003 4 9.30239 3.3 75.9033 33 14.1 200 (1) u y − v x + u ≤ 0, j � 1 . . . n, 2004 5 8.90981 3.45 76.3801 30 13.1 200 r rj i ij 0 r�1 i�1 2005 6 8.41981 3.6 76.8326 27 12.1 200 2006 7 8.83001 3.515 77.2467 24 11.2 200 u ≥ 0, 2007 8 8.90376 3.43 77.6159 23 10.4 200 v ≥ 0, 2008 9 8.07053 3.465 77.9392 21 9.7 200 u free. 2009 10 7.42449 3.5 78.2195 20 9.2 200 2010 11 7.19134 3.5 78.4654 19 8.7 200 2011 12 7.12493 3.5 78.6899 18 8.3 200 φ � max u 2012 13 6.99093 3.5 78.9085 17 7.9 200 2013 14 6.63325 3.5 79.1337 16 7.6 200 subject to u y + u � 1 r r0 0 2014 15 6.39371 3.5 79.3731 16 7.3 200 r�1 2015 16 6.27 3.5 79.6286 15 7.1 200 x1: health expenditure, total (% of GDP); x2: hospital beds (per 1,000 people); y1: v x � 1, i i0 life expectancy at birth, total (years); y2: maternal mortality ratio (modeled i�1 (2) estimate, per 100,000 live births); y3: mortality rate, infant (per 1,000 live births); s m y4: adults (aged 15+) and children (aged 0–14) newly infected with HIV. u y − v x + u ≤ 0, r rj i ij 0 r�1 i�1 one of the primary indicators of the healthcare system ef- u ≥ 0, ficiency of a country. It is confirmed by international studies v ≥ 0, as an output variable used to asses efficiency of healthcare u free. 0 systems [20]. As for the maternal mortality ratio, infant mortality rate, and people newly infected with HIV, which φ � max φ| φ≠ 1 for efficient units . (3) are also seldom used in the literature as outputs are negative outputs, since the DEA technique is applied in such a way that “more is better,” the inverse of the data is used in the max u y + u r r0 0 efficiency analysis, thus satisfying the more is better ap- r�1 proach by converting the largest number to the smallest, and vice versa [1, 14, 21–23]. )e inputs included in the analysis subject to v x � 1 i i0 are as follows: health expenditure total (% of GDP) and i�1 hospital beds (per 1,000 people), which are commonly used (4) u y − v x + u ≤ 0, j � 1 . . . n, in this context and accepted by the conceptual model that r rj i ij 0 i�1 r�1 recognizes the following determinants on individuals health and available medical services and environment. Table 2 u ≥ 0, presents the definition of inputs and outputs used in the v ≥ 0, DEA model. )e data used for the analysis are extracted from u ≤ φ . 0 the World Bank database under the world development in- dicator (http://databank.worldbank.org/data/reports.aspx? 2.2. Efficiency Analysis. Each year (2000 to 2015) is referred source�world-development-indicators). Using the modified to as the decision-making units (DMUs) and included in the DEA model (1 to 4), with the WinQSB linear program- analysis as shown in Table 1. We utilized an input- ming software 2.0, the efficiency of the healthcare system orientation model. )e input-orientation model is appro- is analyzed. priate in this context because the inputs are assumed to be at the discretion of the health industry and should be properly 3. Results utilized to achieve the best possible outcome. )is analysis provides policy makers and general public with useful in- Table 3 shows the efficiency score for each year from 2000 to formation regarding the state of the healthcare system and 2015; 100% signifies the year as efficient and anything less as provides improvement in focus of health outcomes for inefficient. )e result of the DEA model reveals that the proper utilization of resources. Four outputs were chosen for overall efficiency of the healthcare system in Lebanon is the efficiency model: life expectancy at birth, maternal inefficient, with only 4 years (2000, 2001, 2002, and 2015) as mortality ratio, infant mortality rate, and people newly efficient over the 16-year period, with an efficiency average infected with HIV. Life expectancy at birth is a robust of 96.79%. As can be seen from Figure 1, there is a sharp healthcare system outcome used widely in the literature. )e decrease in efficiency from 2003 to 2005. )is can be at- effect of increase in health expenditure that has on life tributed to the increase in the number of newly infected HIV expectancy was accentuated by [19]. It is considered to be and maternal mortality ratio. )e increase in the number of 4 Journal of Healthcare Engineering Table 2: De nition of variable used in the DEA model. Variable Role De nition e sum of public and private health expenditure which covers health service provision (preventive and Health expenditure, total (% of GDP) Input (x1) curative) but does not include provision of water and sanitation. Hospital beds include inpatient beds available in Hospital beds (per 1,000 people) Input (x2) public, private, general, and specialized hospitals and rehabilitation centers. Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of Life expectancy at birth, total (years) Output (y1) mortality at the time of its birth were to stay the same throughout its life. Maternal mortality ratio — Maternal mortality ratio is the number of women Modeled estimate (per 100,000 live births) Output (y2) who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination. Infant mortality rate is the number of infants dying Mortality rate, infant (per 1,000 live births) Output (y3) before reaching one year of age. Adults (aged 15+) and children (aged 0–14) newly Number of adults (aged 15+) and children (aged Output (y4) infected with HIV 0–14) newly infected with HIV. Table 3: Eciency scores. Efficiency (%) Years Eciency (%) 2000 100 2001 100 2002 100 2003 95.15 2004 92.84 2005 90.78 90 2006 92.54 2007 94.82 2008 95.73 2009 96.3 2010 96.99 Figure 1: Eciency description. 2011 97.37 2012 97.87 2013 98.75 self-estimated health status. Our analysis shows that im- 2014 99.47 provement in the healthcare system has more to do with 2015 100 policy reforms and proper implementation than increasing Mean. 96.79 health expenditure. Investing in preventive treatments and proper technology can be an important factor in improving hospital beds per 1000 does not reect signi cantly on the healthcare system eciency. It can therefore be concluded infant mortality rate despite its improvement. However, that the healthcare system in Lebanon utilizes their nancial the eciency improved constantly from 2006 to 2015. e resources eciently, and further investment in this indicator improvement in eciency can be attributed to the enhanced can have signi cant impact on the health outcomes if proper health sector reform project, in addition to strengthening utilization of the nancial resources is maintained. other aspects of administrative and technical nature of the Weight of a variable in DEA signi es the level of con- health sector. Furthermore, the introduction of information tribution of that variable to the eciency of a DMU. e weight distribution across the entire DMUs gives a general technology via automation data collection and shearing to ensure transparency in public nancing contributes to ef- idea as to which variable contributes the most to eciency. e weight distribution of the variables used in the eciency ciency improvement [24]. e development of the visa system and its coverage of the entire Lebanon in February evaluation shows that (x2) hospital beds (per 1,000 people) 2005 linking all data bases are among the major achieve- and (y1) life expectancy at birth total (years) contribute the ments in the healthcare system [12]. e data show a con- most to eciency, given their high average values and tinuous decrease in health expenditure, total (% of GDP), distribution. erefore, improving the utilization of the from 2008 to 2015; however, the eciency continues to show number of beds and increasing the life expectancy at birth steady improvement. is nding contradicts the hypothesis will a—ect the eciency signi cantly. 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