Using Simulation and Six-Sigma Tools in Improving Process Flow in Outpatient Clinics

Heidarzadeh, Elham and Sajadnia, Sahar (2017): Using Simulation and Six-Sigma Tools in Improving Process Flow in Outpatient Clinics.

Abstract

It is apparent that outpatient clinics are becoming complex and need to be optimized and improved on a daily basis. In this project, we used several methods including discrete event simulation, quality function deployment (QFD), and failure modes and effects analysis (FMEA) to optimize and improve these clinics. We conducted this study at a major suburban outpatient clinic to propose main recommendations which most likely apply to a vast majority of such clinics. Firstly, the simulation-based modeling that we ran assisted us in recognizing optimum staff number which would result in decreasing waiting times that patients usually spend and making the process flow at the facility smoother. Secondly, QFD approach for analyzing outpatient clinic requirement is also proposed and realized through a case study. It is realized that the proposed approach can adjust service quality toward customer requirements effectively. Lastly, the health care failure modes and effects analysis (FMEA) that we implemented as a novel method to discover conditions and active failures and to prioritize these based on the potential severity of risks associated with them.

• Item Type: MPRA Paper
• Language: English
• Keywords: Outpatient clinic, discrete event simulation, quality function deployment (QFD), failure modes and effects analysis (FMEA)
• Subjects: C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs; C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C83 - Survey Methods ; Sampling Methods; L - Industrial Organization > L8 - Industry Studies: Services; L - Industrial Organization > L8 - Industry Studies: Services > L80 - General

References

[1] C.E. Noon, C.T. Hankins, M.J. Cote, “Understanding the Impact of Variation in the Delivery of Healthcare Services,” J. HealthcManag, Volume No. 48, PP. 82–98, 2003.

[2] M.W. Isken, T.J. Ward, T.C. McKee, “Simulating Outpatient Obstetrical Clinics,” Proceedings of the 1999 Winter Simulation Conference, PP. 1557-1563. Piscataway, New Jersey, 1999.

[3] M. Guo, M. Wagner, C. West, “Outpatient Clinic Scheduling – a Simulation Approach,” Proceedings of the 2004 Winter Simulation Conference, PP. 1250-1268, Piscataway, New Jersey 2004.

[4] J.E. Everett, “A Decision Support Simulation Model for the Management of an Elective Surgery Waiting System,” J. Health Care Management Science, Volume No. 5, PP. 89-96, 2002.

[5] V. Merode, G.G. Groothuis, S. Schoenmakers, M. Boersma, “Simulation Studies and the Alignment of Interests,” J. Health Care Management Science, Volume No. 5, PP. 97-102, 2002.

[6] J.T. Blake, M.W. Carter, S. Richardson, “An Analysis of Emergency Room Wait Time Issues via Computer Simulation,” J. INFOR, Volume No. 34, PP. 263-73, 1996.

[7] D.C. Lane, C. Monefeldt, J.V. Rosenhead, “Looking in the Wrong Place for Healthcare Improvements: a System Dynamics Study of an Accident and Emergency Department,” J. Operational Research Society, Volume No. 51, PP. 518-31, 2000.

[8] D.H. Stamatis. “Failure mode and effects analysis: FMEA from theory to execution”, Milwaukee, WI: ASQC Quality Press; 1995.

[9] Strategies and tips of maximizing failure mode and effects in your organization. White Paper. Chicago: American Society for Healthcare Risk Management; 2002. Available at: www.ashrm.org/ashrm/resources/files/FMEAwhitepaper.pdf. Access April 7, 2008.

[10] L. K. C. Chan, & M. L. W. Wu, “Quality function deployment: A literature review”, Informally published manuscript, Management Sciences, City University of Hong Kong, Kowloon, Hong Kong, China, 2001.

[11] G. H. M. Mazur, “The application of quality function deployment (qfd) to design a course in total quality management (tqm) at the university of Michigan college of engineering”. Unpublished manuscript, College of Engineering, University of Michigan, Michigan, 1996.

[12] Y. Akao, “An Introduction to Quality Function Deployment; Quality Function Deployment (QFD): Integrating Customer Requirements Into Product Design”, Productivity Press, Cambridge, Massachusetts, (1990) 1-24.

[13] V.T. Luu, S.Y. Kim, T.Q. Truong, O.O. Stephen, Quality improvement of apartment projects using fuzzy-QFD approach: A case study in Vietnam, KSCE J. Civil Engineering 13 (2009) 305-315.

[14] Akar, Navid, and Hossein Lotfizadeh. “A New Integrated FQFD Approach for Improving Quality and Reliability of Solar Drying Systems.” arXiv preprint arXiv:1704.07895 (2017).

[15] L. Wang, Y.K Juan, J. Wang, K.M. Li, C. Ong , Fuzzy-QFD approach based decision support model for licensor selection, J. Expert Systems with Applications 39 (2012) 1484–1491.

[16] L.K. Chan, M.L. Wue, A systematic approach to quality function deployment with a full illustrative example, J. Management and Science 33 (2005) 119–139.

[17] M. Bevilacqua, F.E. Ciarapica, B. Marchetti, Development and test of a new fuzzy-QFD approach for characterizing customers rating of extra virgin olive oil, J. Food Quality and Preference 24 (2012) 75–84.

[18] Feili, H. R., Molaee Aghaee, E., Bairampour, M., Akar, N., & Fadaee, A. (2012, May). Development of Solar Drying Systems in Saffron Industry Using FAHP & FQFD. In 3rd International Conference on Nuclear & Renewable Energy Resources, Turkey (pp. 20-23).

[19] E. Bottani, A. Rizzi, Strategic management of logistics service: A fuzzy-QFD approach. J. Production Economics 103 (2006) 585–599.

[20] Akar, N., Daj, E., & Boroojerdi, S. S. (2016). Using Fuzzy Quality Function Deployment in Improving Reliabality of Wind Power Systems.

[21] C. Kahraman, T. Ertay, G. Buyukozkan, A fuzzy optimization model for QFD planning process using analytic network approach, J. Operational Research 171 (2006) 390–411.

[22] D.E. Lee, T.K Lim, D. Arditi, Automated stochastic quality function deployment system for measuring the quality performance of design/build contractors, Automation in Construction 18 (2009) 348–356.

[23] Xiao N, Huang HZ, Li Y, He L, Jin T. Multiple failure modes analysis and weighted risk priority number evaluation in FMEA. J Eng Fail Anal 2011;18:1162–70.

[24] Mazur Z, Garcia Illescas R, Porcayo Calderon J. Last stage blades failure analysis of a 28 MW geothermal turbine. J Eng Fail Anal 2009;16:1020–32.

[25] Feili, H. R., Akar, N., Lotfizadeh, H., Bairampour, M., & Nasiri, S. (2013). Risk analysis of geothermal power plants using Failure Modes and Effects Analysis (FMEA) technique. Energy Conversion and Management, 72, 69-76.

[26] Narayanagounder S, Gurusami K. A new approach for prioritization of failure modes in design FMEA using ANOVA. World Acad Sci, Eng Technol 2009;49.

[27] W.W. Vandenbrande, “How to use FMEA to reduce the size of your qualitytoolbox”, J Qual Prog 1998;31:97–100.

[28] Sajadnia, Sahar, and Elham Heidarzadeh. “Improving Patient’s Satisfaction at Urgent Care Clinics by Using Simulation-based Risk Analysis and Quality Improvement”, Munich Personal RePEc Archive, September 2016.