Sains Malaysiana 47(9)(2018): 2231–2240

http://dx.doi.org/10.17576/jsm-2018-4709-34

 

Penambahbaikan Sumber Jabatan Kecemasan menggunakan Kaedah Simulasi dan Analisis Pengumpulan Data

(Resources Improvement in Emergency Department using Simulation and Data Envelopment Analysis)

 

WAN MALISSA WAN MOHD AMINUDDIN, WAN ROSMANIRA ISMAIL* & HUSYAIRI HARUNARASHID

 

Pusat Pengajian Sains Matematik, Fakulti Sains dan Teknologi, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor Darul Ehsan, Malaysia

 

Diserahkan: 20 September 2017/Diterima: 5 Mei 2018

 

ABSTRAK

Jabatan Kecemasan Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM) menerima kedatangan pesakit yang ramai pada setiap hari menyebabkan jabatan ini kerap berdepan dengan masalah kesesakan. Justeru, objektif kajian ini adalah mengenal pasti model pengoptimuman terbaik untuk menambahbaik sumber bagi meningkatkan tahap kecekapan Jabatan Kecemasan PPUKM dan menyelesaikan masalah kesesakan jabatan. Kaedah simulasi digunakan bagi membina model jabatan kecemasan dengan pemboleh ubah yang digunakan dalam pemodelan simulasi ini adalah dikhususkan berdasarkan zon atau ruang rawatan. Alternatif penambahbaikan yang dicadangkan ini mengandungi konfigurasi bilangan sumber jabatan yang baru. Enam model gabungan yang digunakan terdiri daripada Model CCR dan Set Rujukan, Model BCC dan Set Rujukan, Model CCR dan Kecekapan-Super, Model BCC dan Kecekapan-Super, Model Bi-Objektif MCDEA-CCR dan Kecekapan Silang dan Model Bi-Objektif MCDEA-BCC dan Kecekapan Silang. Model Bi-Objektif MCDEA-BCC merupakan lanjutan kepada Model Bi-Objektif MCDEA-CCR daripada kajian terdahulu. Keputusan kajian menunjukkan Model Bi-Objektif MCDEA-BCC yang dibina telah memberikan bilangan alternatif penambahbaikan cekap yang paling kecil berbanding model-model gabungan lain. Melalui model gabungan ini juga satu alternatif penambahbaikan yang optimum yang telah dicadangkan dapat mengurangkan masa menunggu pesakit di Zon Hijau sebanyak 51% manakala peratusan penggunaan tenaga kerja sumber berjaya ditambahbaik agar lebih munasabah. Alternatif ini memerlukan susun atur kembali kedudukan sumber tanpa melakukan perubahan yang besar ke atas sistem asal.

 

Kata kunci: Analisis Pengumpulan Data; jabatan kecemasan; kesesakan; pengoptimuman sumber; simulasi

 

ABSTRACT

The Emergency Department of Universiti Kebangsaan Medical Centre (PPUKM) receives a high number of patients daily resulted in numerous problems particularly overcrowding. Therefore, this study is designed to identify the best optimization model that improve resources in order to improve the efficiency level of the PPUKM Emergency Department and solve the overcrowding problem. Simulation technique is used to build a simulation model of the emergency department where the variables used in the model are specified by triage zones or treatment areas. The proposed alternative improvements contains a new configuration of department resources. Six combined models used are the CCR Model and Reference Set, BCC Model and Reference Set, CCR Model and Super-Efficiency, BCC Model and Super-Efficiency, Bi-Objective MCDEA-CCR Model and Cross-Efficiency and Bi-Objective MCDEA-BCC Model and Cross Efficiency. Bi-Objective MCDEA-BCC Model is a continuation of Bi-Objective MCDEA-CCR Model from previous studies. The results showed that the Bi-Objective MCDEA-BCC Model has derived the least number of efficient alternative improvements compared to other combined models. It also suggested an optimum alternative that can reduce the patient waiting time in the Green Zone by 51% while the percentage of resource utilisation has been improved to be more reasonable. This alternative needs redesigning the department’s resources without making major changes to the original system.

 

Keywords: Data Envelopment Analysis; emergency department; overcrowding; resource optimisation; simulation

RUJUKAN

 

Aboukanda, E. & Latif, M. 2013. Exploiting simulation to reduce patient waiting time using a streaming strategy in an emergency department. International Journal of Advanced Technology & Engineering Research 3(2): 79-86.

Aiken, H.L., Charles, S.P., Sloane, D.M., Sochalski, J. & Silber, S.H. 2002. Hospital nurse staffing and patient mortality, nurse burnout and job dissatisfaction. JAMA 288(16): 1987-1993.

Al-Refaie, A., Fouad, R.H., Li, M. & Shurrab, M. 2014. Applying simulation and DEA to improve performance of emergency department in a Jordanian hospital. Simulation Modelling Practice and Theory 41: 59-72.

Aminuddin, W.M.W.M., Ismail, W.R., Harunarashid, H., Ali, R.A., Ismail, M.S. & Johar, M. 2016. Utilization of Emergency Department, UKM Medical Centre: Pattern of patient. Jurnal Teknologi 4: 53-58.

Andersen, P. & Petersen, N. 1993. A procedure for ranking efficient units in data envelopment analysis. Management Science 39(10): 1261-1264.

Ansari, Z.M., Yasin, H., Zehra, N. & Faisal, A. 2015. Occupational stress among Emergency Department (ED) staff and the need for invesment in health care; A view from Pakistan. British Journal of Medicine & Medical Research 10(10): 1-9.

Azadeh, A., Sepahi, M. & Haghighi, S.M. 2013. An integrated simulation-DEA approach to improve quality care of medical centres. Int. J. Process Management and Benchmarking 3(3): 352-370.

Azaiez, M.N. & Al-Sharif, S. 2005. A 0-1 goal programming model for nurse scheduling. Computers & Operations Research 32(3): 491-507.

Azlan, N., Saibon, I.M. & Azizol, M. 2013. Management of emergency department overcrowding (EDOC) in a teaching hospital. Med. & Health 8(1): 42-46.

Bal, H. & Orkc, H.H. 2010. Improving the discrimination power and weights dispersion in the data envelopment analysis. Computers & Operations Research 37(1): 99-107.

Banker, R., Charnes, A. & Cooper, W. 1984. Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science 30(9): 1078- 1092.

Brailsford, S.C. 2007. Tutorial: Advances and challenges in healthcare simulation modeling. Proceeding of the 2007 Winter Simulation Conference. pp. 1436-1448.

Carmen, R., Defraeye, M. & Van Nieuwenhuyse, I. 2015. A decision support system for capacity planning in emergency departments. Int. J. Simul. Model 14(2): 299-312.

Carrilloa, M. & Jorge, J.M. 2015. A multiobjective DEA approach to ranking alternatives. Expert Systems With Applications 12: 1-27.

Carson, J.S. 2002. Model verification and validation. Proceeding of the 2002 Winter Simulation Conference. pp. 52-58.

Carter, M.W. & Lapierre, S.D. 2001. Scheduling emergency room physicians. Health Care Management Science 4(4): 347-360.

Centeno, M.A., Giachetti, R., Linn, R. & Ismail, A.M. 2003. A simulation-ILP based tool for scheduling ER staff. Proceeding of the 2003 Winter Simulation Conference. pp. 1930-1938.

Charnes, A., Cooper, W. & Rhodes, E. 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2(6): 429-444.

Cooper, W., Seiford, L. & Tone, K. 2007. Data Envelopment Analysis. New York: Springer.

Cowan, R.M. & Trzeciak, S. 2005. Clinical review: Emergency department overcrowding and the potential impact on the critically ill. Critical Care 9(3): 291-295.

Di, S., Lorenzo, S., Vaughan, L., Lalle, I., Magrini, L. & Magnanti, M. 2015. Overcrowding in emergency department: An international issue. Intern Emerg. Med. 10(2): 171-175.

Doyle, J. & Green, R. 1994. Efficiency and cross-efficiency in DEA: Derivations, meanings and uses. Journal of the Operational Research Society 45(5): 567-578.

Emrouznejad, A. 2012. Data Envelopment Analysis Homepage. http://www.DEAzone.com.

Eskandari, H., Riyahifard, M., Khosravi, S. & Geiger, C.D. 2011. Improving the emergency department performance using simulation and MCDM methods. Proceeding of 2011 Winter Simulation Conference. pp. 1211-1222.

Francisco, A., Augusto, F., Marins, S., Tamura, P.M. & Dias, E.X. 2017. Bi-Objective multiple criteria data envelopment analysis combined with the overall equipment effectiveness: An application in an automotive company. Journal of Cleaner Production 157: 278-288.

Gharahighehi, A., Kheirkhah, A.S., Bagheri, A. & Rashidi, E. 2016. Improving performances of the emergency department using discrete event simulation, DEA and the MADM methods. Digital Health 2: 1-14.

Ghasemi, M., Ignatius, J. & Emrouznejad, A. 2014. A bi-objective weighted model for improving the discrimination power in MCDEA. European Journal of Operational Research 233(3): 640-650.

Holm, L.B., Luras, H. & Dahl, F.A. 2013. Improving hospital bed utilisation through simulation and optimisation. International Journal of Medical Informatics 82(2): 80-89.

Horwitz, L.I., Green, J. & Bradley, E.H. 2010. US emergency department performance on wait time and length of visit. Annals Of Emergency Medicine 55(2): 133-141.

Jeenanunta, C., Ayudhya, S.I.N., Doungraksa, P., Sereewattanapong, C., Pongtanupattana, A. & Nuchjarin Intalar. 2013. Resource analysis in emergency department using simulation-based framework. 4th International Conference on Engineering Project and Production Management. pp. 1073-1083.

Jun, J., Jacobson, S. & Swisher, J. 2013. Application of discrete-event simulation in health care clinics: A survey. Journal of the Operational Research Society 50(2): 109-123.

Kelton, W.D., Sadowski, R.P. & Swets, N.B. 2010. Simulation with Arena. New York: McGraw-Hill.

Li, X. & Reeves, G.R. 1999. A multiple criteria approach to data envelopment analysis. Engineering and Technology Management 115: 507-517.

Lv, X., Li, L., Xu, W. & Rong, X. 2015. Sufficient and comprehensive measurement of multi-band camouflage screen performance applying bi-objective super-efficiency dea. The 10th International Conference on Computer Science & Education. pp. 542-546.

Medical Development Division. 2012. Emergency Medicine and Trauma Services Policy. http://www.moh.gov.my/index.php/ pages/view/195. Diakses pada 5 Disember 2015.

Moashiri, H., Aljunid, S.M., Amin, R.M., Dahlui, M. & Ibrahim, W.N. 2011. Measuring efficiency of teaching hospital in Malaysia. International Journal of Business and Management 6(4): 207-213.

Meza, L.A. & Lins, M.P.E. 2002. Review of methods for increasing discrimination in data envelopment analysis. Annals of Operations Research 116(1-4): 225-242.

Paul, S.A., Reddy, M.C. & Deflitch, C.J. 2010. A systematic review of simulation studies investigating emergency department overcrowding. Simulation 86(8-9): 559-571.

Redeker, G.A., Webber, T., Czekster, R.M., Quickert, S. & Bowles, J.K.F. 2017. Estimating capacity and resource allocation in healthcare settings using business process modelling and simulation. Anais XXXVII Congresso da Sociedade Brasileira de Computação. pp. 5-8.

Ruohonen, T., Neittaanmaki, P. & Teittinen, J. 2006. Simulation model for improving the operation of the emergency department of special health care. The Proceeding of 2006 Winter Simulation Conference. pp. 453-458.

Sarkis, J. 2000. Comparative analysis of DEA as a discrete alternative multicriteria decision tool. European Journal of Operational Research 123(3): 543-557.

Sexton, T. 1986. Measuring Efficiency: An Assessment of Data Envelopment Analysis. San Francisco: Jossey-Bass.

Somma, S.D., Paladino, L., Vaughan, L., Lalle, I., Magrini, L. & Magnanti, M. 2015. Overcrowding in emergency department: An international issue. Intern. Emerg. Med. 10(2): 171-175.

Subramaniam, S. 2016. Kementerian Kesihatan Usaha Tangani Pengurangan Bajet. https://www.bharian.com.my/ node/181872. Diakses oleh 10 Ogos 2016.

Tahar, R.M. 2006. A Practical Approach to Computer Simulation Modelling. Serdang: Universiti Putra Malaysia Press.

Unit Perancang Ekonomi. 2016. Rancangan Malaysia Ke-Sebelas 2016-2020.

Uriarte, A.G., Zuniga, E.R., Moris, M.U. & Ng, A.H.C. 2015. System design and improvement of an emergency department using simulation-based multi-objective optimization. Journal of Physics 1: 1-11.

Weng, S., Tsai, B.S., Wang, L.M. & Chang, C.Y. 2011. Using simulation and data envelopment analysis in optimal healthcare efficiency allocations. The Proceeding of 2011 Winter Simulation Conference. pp. 1295-1305.

Yarmohammadian, M.H., Rezaei, F., Haghshenas, A. & Tavakoli, N. 2017. Overcrowding in emergency departments: A review of strategies to decrease future challenges. Journal of Research in Medical Sciences 22(1): 23.

Zeinali, F., Mahootch, M. & Sepehri, M.M. 2015. Resource planning in the emergency departments: A simulation-based metamodeling approach. Simulation Modelling Practice and Theory 53: 123-138.

 

 

*Pengarang untuk surat-menyurat: email: wrismail@ukm.edu.my