Technical Efficiency of Regional Hospitals, Evidence from Albania using Data Envelopment Analysis

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DOI : 10.18843/rwjasc/v9i3/10 DOI URL : http://dx.doi.org/10.18843/rwjasc/v9i3/10 Technical Efficiency of Regional Hospitals, Evidence from Albania using Data Envelopment Analysis Edi Dragusha, M.Sc., Faculty of Economic, Political and Social Sciences, Catholic University "Our Lady of Good Counsel", Tirana, Albania ABSTRACT The evolving strategies to finance hospitals in more efficient ways, and, specifically on the reforms of the Albanian Health System to introduce the DRGs, aiming the improvement of hospital service productivity, the technical efficiency of the Albanian hospitals necessities to be evaluated. This study performs, given a level of inputs, the ranking of the regional hospitals based on their technical efficiency. There have been collected data on all eleven Albanian regional hospitals for three consecutive years, 2015-2017. The data relate to input data such as number of physicians, nurses, hospitals capacity and it s financing. The output data instead, relate to the number of hospital patients discharges. The data have been analyzed by Data Envelopment Analysis (DEA), a technique used in service management and benchmarking. This technique compares regional hospitals considering all resources used and services provided and identifies the most efficient hospitals or best practice hospitals. The results suggest that more that 50% of all regional hospitals result efficient, followed by the other hospitals with an average of 7% reduction on technical efficiency. The study evidenced that the majority of the Albanian Regional Hospitals operate at the efficient frontier followed by other hospitals that operate just below. The efficient levels of hospitals indicate an optimal use of their capacities in offering services to the population. Keywords: Albanian healthcare, Healthcare financing system, Albanian Regional Hospitals, Technical Efficiency, DEA Analysis. INTRODUCTION: The Albanian healthcare system is currently undergoing important steps in reforming its financing system in relation to performance driven strategic pathways. Currently, in Albania, there are 23 District hospitals, 11 Regional hospitals, 5 University hospitals, and 8 Private hospitals contracted, for specific health services packages, by the Compulsory Health Insurance Fund (CHIF) (CHIF, 2018). The financing of all public hospitals is completed by CHIF significantly on historical base (Persiani N., 2014) through Ministerial Decree without any regard to the performance and the hospitals efficiency. Given this scenario, the Hospitals financing isn t depending on the efficiency of the output produced, since there isn t any relationship between the total amount of Hospitals financing and its efficiency (Dragusha, July, 2018). In Albania, the hospitals receive a financing that measures around 50% of the entire CHIF budget that goes to the Albanian Hospital Tertiary Healthcare. On the other hands, a set of performance indicators must be considered to drive the hospitals allocation of financing. Measuring performance, i.e. the improved health status for the hospitals, is rather difficult considering the complexity of the services offered. To evaluate the regional hospitals by their performance, analyzing hospital s technical efficiency can contribute to reach this goal. Efficiency is explained as the ratio of output to input. The technical efficiency ponders the levels of inputs and International Refereed Research Journal www.researchersworld.com Vol. IX, Issue 3, July 2018 [90]

outputs of the hospital. It s considered as input-oriented, when seeking to minimize the inputs given a certain level of outputs, or output-oriented when the system s efforts goes to maximize outputs given a certain level of inputs. The technique for measuring technical efficiency, is a linear model, as for this study, the Data Envelopment Analysis (DEA) is applied. METHODOLOGY: The data from all eleven Albanian district hospitals have been collected and organized by hospital, year, input category and output. The inputs considered for measuring the technical efficiency for each hospital are: number of physicians, number of nurses, bed capacity and the hospital s expenditures. The output considered is the patient s discharge number. For the data analysis, Excel 2016 and DEAP 2 (version 2.0) software are utilized. Data from all eleven hospitals has been collected through institutional official visit, which, upon request, the data was delivered. These data relate to the consecutive period of years 2015-2017. As all four inputs and one output that are engaged for this study, have been assessed and organized as in Table 1, the data was then inserted in DEAP 2 platform for processing. Data Envelopment Analysis (DEA) is a very powerful service management and benchmarking technique originally developed by Chames, et al. (1978) to evaluate nonprofit and public-sector organizations. DEA compares service units considering all resources used and services provided and, identifies the most efficient units or best practice units (branches, departments, individuals) and the inefficient units in which real efficiency improvements are possible (Sherman & Zhu, 2006). DEA utilizes linear programing techniques to asses technical efficiency scores for each hospital, i.e. a fully efficient hospital in terms of technical efficiency, at efficiency frontier, reaches the score 1 (or 100%). Less efficient hospitals score less than 1. The DEA linear programing is reppresented as follows. Max h 0 = U r Y rj0 Subject to: m s r=1 v i x ij0 = 1 i=1 s u r y rj v i x ij 0, r=1 m i=1 j = 1,, n u r, v j 0 Where: y rj = amount of output r from hospital j x ij = amount of input i to hospital j u r = weight given to output r v i = weight given to input i n = number of hospitals s = number of outputs m = number of inputs The benchmark considered to compare all the hospitals, isn t found outside the group, but inside it. This means that the efficiency of a particular regional hospital is determined by the group of all regional hospitals. FINDINGS AND DISCUSSION: The data presented in Table 1, presents the inputs unit and the output s unit for three-year period 2015-2017. For these data, the statistical summary is represented in Table 2. It can be noticed that, for year 2015 the patient s discharge data related to Shkodër hospital is as 173% greater than the average data related to the last two years, which strongly influences our analysis. Due to this significant discordance on Shkodër s patients discharge data, the efficiency scores represented on Error! Reference source not found., establish Shkodër hospital as the efficient one, and all other hospitals rank subsequently. In order to consider the efficiency scores ranked homogenously and to test the robustness of DEA technical scores, the Jackknife analysis was used (Efron, 1979), omitting the one unit, i.e. Shkodër. International Refereed Research Journal www.researchersworld.com Vol. IX, Issue 3, July 2018 [91]

2017 Year -Journal of Arts, Science & Commerce E-ISSN 2229-4686 ISSN 2231-4172 Table 4 illustrates the efficiency scores were, 60% of the hospitals result to be efficient (θcrts=1), following Kukës, Berat, Elbasan and Korçë. Given the above scenario, a one period DEA analysis was performed by considering the data related to year 2017. In this analysis, referring to the results presented in Table 5, 6 out 11 regional Hospitals result to be efficient (θcrts=1), following Berat, Shkodër, Vlorë, Elbasan and Korçë. CONCLUSION: It is considered that, as demonstrated through the study performed, the majority of the Albanian Regional Hospitals operate at the technical efficient frontier followed by other hospitals that operate just below. For an given input, the hospitals maximizes the level of output. The efficient levels of hospitals indicate an optimal use of their capacities in offering services to the population. On this study, the unit of output, i.e. amount of patients discharge has been considered. As it has been mentioned earlier, measuring the service performance is rather difficult considering the complexity of the services offered. Since Health is the main goal of each health system, an improvement on health status should be the ultimate unit of output to be considered on DEA analysis. This study deserves going deeper into analysis and must be followed by other studies to measure efficiency, considering a variety of other outputs and performing the DEA analysis also in terms of input-oriented. LIMITATIONS OF THE STUDY: Measuring improvement on health in Albania, given the absence of a financing system which is based on the performance, and, furthermore, the absence of Diagnoses Related Groups (DRGs) classification system, makes it impossible. The data related to Shkodër hospital, year 2015, lacks explanations ACKNOWLEDGMENTS: A great appreciation goes to the Compulsory Health Insurance Fund for all the absolute sustainability given to the research in providing the data for the analysis. REFERENCES: CHIF. (2018). Compulsory Health Insurance Fund. Dragusha, E. (July, 2018). Financing efficiency on Albanian tertiary healthcare facilities. Researchers World Journal of Arts, Science & Commerce. Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. The Annals of Statistics, pp. 1-26. Persiani N., G. C. (2014). Reforming the Financial Health Care System: The Case of the Republic of Albania. China-USA Business Review. Sherman, H. D., & Zhu, J. (2006). Data Envelopment Analysis Explained. In H. D. Sherman, & J. Zhu, Service Productivity Management. Improving Service Performance using Data Envelopment Analysis (DEA) (p. 49-89). Springer US. Sherman, H., & Zhu, J. (2006). DATA ENVELOPMENT ANALYSIS EXPLAINED. In H. Sherman, & J. Zhu, Service Productivity Management. Springer. Table 1: Input and output data by Regional Hospital Regional Hospital Berat Dibër Durrës Elbasan Fier Gjirok astër Korçë Kukës Lezhë Shkodër Vlorë Physicians 62 15 134 76 89 29 72 28 41 88 101 Nurses 167 200 328 292 236 87 259 145 153 316 266 Beds 268 299 340 408 348 177 463 236 162 478 368 Total Costs 1 453.315 375.598 768.746 708.338 543.113 342.001 624.027 335.786 354.705 743.586 678.579 1 In thousand leke. Exchange Rate 1 Lekë = 0.0075 Euro International Refereed Research Journal www.researchersworld.com Vol. IX, Issue 3, July 2018 [92]

2015 2016 Year -Journal of Arts, Science & Commerce E-ISSN 2229-4686 ISSN 2231-4172 Regional Hospital Berat Dibër Durrës Elbasan Fier Gjirok astër Korçë Kukës Lezhë Shkodër Vlorë Discharges 7.648 6.995 14.764 11.364 10.398 4.936 9.911 6.030 5.990 12.772 11.171 Physicians 65 17 143 128 86 28 68 31 41 90 69 Nurses 167 184 337 290 206 78 265 160 156 320 234 Beds 268 299 340 432 348 177 463 236 162 478 368 TotalCosts 415.263 372.690 707.914 715.228 488.577 316.228 586.570 326.177 324.445 708.661 584.766 Discharges 7.114 7.864 15.166 10.957 10.724 5.058 10.204 6.206 6.675 12.929 12.921 Physicians 59 23 142 92 104 27 75 26 40 89 85 Nurses 182 199 360 313 243 102 273 140 139 325 234 Beds 279 299 340 432 368 184 463 236 162 478 368 TotalCosts 420.834 370.185 752.910 690.911 496.616 299.113 598.911 336.460 296.456 727.265 558.692 Discharges 8.205 7.722 15.753 11.610 12.797 5.162 10.088 5.736 6.297 35.075 13.347 Source: Compulsory Health Insurance Fund (CHIF) Description Table 2: Regional Hospitals Summary statistics Mean Standard Deviation Minimum Maximum Year 2017 Physicians 67 34 15 134 Nurses 223 74 87 328 Beds 322 101 162 478 Total Costs 1 538.890 164.636 335.786 768.746 Year 2016 Physicians 218 76 78 337 Nurses 70 39 17 143 Beds 325 103 162 478 Total Costs 1 504.229 155.475 316.228 715.228 Year 2015 Physicians 228 80 102 360 Nurses 69 36 23 142 Beds 328 102 162 478 Total Costs 1 504.396 164.244 296.456 752.910 Table 3: Efficiency Scores for three-year period 2015-2017 Berat 0,42 Dibër 0,85 Durrës 0,63 International Refereed Research Journal www.researchersworld.com Vol. IX, Issue 3, July 2018 [93]

Elbasan 0,37 Fier 0,53 Gjirokastër 0,49 Korçë 0,35 Kukës 0,56 Lezhë 0,53 Shkodër 1 * Vlorë 0,53 Table 4: Efficiency scores for three-year period 2015-2017, excluded Shkodër Hospital Berat 0,84 Dibër 1,00 * Durrës 1,00 * Elbasan 0,75 Fier 1,00 * Gjirokastër 1,00 * Korçë 0,73 Kukës 0,92 Lezhë 1,00 * Vlorë 1,00 * Table 5: Efficiency scores for one-year period (2017) Berat 0,96 Dibër 1,00 * Durrës 1,00 * Elbasan 0,91 Fier 1,00 * Gjirokastër 1,00 * Korçë 0,88 Kukës 1,00 * Lezhë 1,00 * Shkodër 0,94 Vlorë 0,91 ---- International Refereed Research Journal www.researchersworld.com Vol. IX, Issue 3, July 2018 [94]