Functional regression-based monitoring of quality of service in hospital emergency departments

References

• Ahmad, N., Ghani, N.A., Kamil, A.A. and Tahar, R.M. (2015) Modelling the complexity of emergency department operations using hybrid simulation. International Journal of Simulation and Process Modelling, 10(4), 360–371.
   Google Scholar
• Benedetti, J.K. (1977) On the nonparametric estimation of regression functions. Journal of the Royal Statistical Society. Series B (Methodological), 39, 248–253.
   Google Scholar
• Bertsimas, D. and Vinh Doan, X. (2010) Robust and data-driven approaches to call centers. European Journal of Operational Research, 207(2), 1072–1085.
   Web of Science ®Google Scholar
• Bhat, U.N. (1987) A sequential technique for the control of traffic intensity in Markovian queues. Annals of Operations Research, 8(1), 151–164.
   Google Scholar
• Bhat, U.N. and Subba Rao, S. (1972) A statistical technique for the control of traffic intensity in the queuing systems m/g/1 and gi/m/1. Operations Research, 20(5), 955–966.
   Web of Science ®Google Scholar
• Callahan, C.D. and Griffen, D.L. (2003) Advanced statistics: Applying statistical process control techniques to emergency medicine: A primer for providers. Academic Emergency Medicine, 10(8), 883–890.
   PubMed Web of Science ®Google Scholar
• Chen, N., Yuan, Y. and Zhou, S. (2011) Performance analysis of queue length monitoring of m/g/1 systems. Naval Research Logistics, 58(8), 782–794.
   Web of Science ®Google Scholar
• Chen, N. and Zhou, S. (2015) CUSUM statistical monitoring of m/m/1 queues and extensions. Technometrics, 57(2), 245–256.
   Web of Science ®Google Scholar
• Defraeye, M. and van Nieuwenhuyse, T. (2016) Staffing and scheduling under nonstationary demand for service: A literature review. Omega, 58, 4–25.
   Web of Science ®Google Scholar
• Derlet, R.W. (2002) Overcrowding in emergency departments: Increased demand and decreased capacity. Annals of Emergency Medicine, 39(4), 430–432.
   PubMed Web of Science ®Google Scholar
• Drazek, L.C. (2013) Intensity estimation for Poisson processes. PhD thesis, The University of Leeds, UK.
   Google Scholar
• Eick, S.G., Massey, W.A. and Whitt, W. (1993) The physics of the mt/g/∞ queue. Operations Research, 41(4), 731–742.
   Web of Science ®Google Scholar
• Goodwin, S., Lin, Y,L., Singh, S. and Kuo, Y.F. (2013) Variation in length of stay and outcomes among hospitalized patients attributable to hospitals and hospitalists. Journal of General Internal Medicine, 28(3), 370–376.
   PubMed Web of Science ®Google Scholar
• Huang, X., Zhou, Q., Zeng, L. and Li, X. (2017) Monitoring spatial uniformity of particle distributions in manufacturing processes using the k function. IEEE Transactions on Automation Science and Engineering, 14(2), 1031–1041.
   Web of Science ®Google Scholar
• Ibrahim, M.R. and Whitt, W. (2009) Real-time delay estimation in overloaded multiserver queues with abandonments. Management Science, 55(10), 1729–1742.
   Web of Science ®Google Scholar
• Jennings, O.B., Mandelbaum, A., Massey, W.A. and Whitt, W. (1996) Server staffing to meet time-varying demand. Management Science, 42(10),1383–1394.
   Web of Science ®Google Scholar
• Jin, N., Zhou, S., Chang, T.S. and Huang, H.H.H. (2008) Identification of influential functional process variables for surface quality control in hot rolling processes. IEEE Transactions on Automation Science and Engineering, 5(3), 557–562.
   Web of Science ®Google Scholar
• Joint Commission. (2019) Specifications manual for national hospital inpatient quality measures, version 5.5a. https://www.jointcommission.org/specifications_manual_for_national_hospital_inpatient_quality_measures.aspx.
   Google Scholar
• Liao, H. and Sun, J. (2011) Nonparametric and semi-parametric sensor recovery in multichannel condition monitoring systems. IEEE Transactions on Automation Science and Engineering, 8(4), 744–753.
   Web of Science ®Google Scholar
• Malfait, N. and Ramsay, J.O. (2003) The historical functional linear model. Canadian Journal of Statistics, 31(2), 115–128.
   Web of Science ®Google Scholar
• Massey, W.A. (2002) The analysis of queues with time-varying rates for telecommunication models. Telecommunication Systems, 21(2–4), 173–204.
   Web of Science ®Google Scholar
• Matteson, D.S., McLean, M.W., Woodard, D.B. and Henderson, S.G. (2011) Forecasting emergency medical service call arrival rates. The Annals of Applied Statistics, 5, 1379–1406.
   Web of Science ®Google Scholar
• Montgomery, D.C. (2001) Introduction to Statistical Process Control. John Wiley, New York, NY.
   Google Scholar
• Ramsay, J., Hooker, G. and Graves, S. (2009) Functional data analysis with R and MATLAB. Springer Science & Business Media, New York, NY.
   Google Scholar
• Saghafian, S., Austin, G. and Traub, S.J. (2015) Operations research/management contributions to emergency department patient flow optimization: Review and research prospects. IIE Transactions on Healthcare Systems Engineering, 5(2), 101–123.
   Google Scholar
• Silverman, B.W. (1986) Density Estimation for Statistics and Data Analysis, CRC Press, Boca Raton, FL.
   Google Scholar
• Sir, M.Y., Nestler, D., Hellmich, T., Das, D., Laughlin Jr, M.J., Dohlman, M.C. and Pasupathy, K. (2017) Optimization of multidisciplinary staffing improves patient experiences at the Mayo clinic. Interfaces, 47(5), 425–441.
   Web of Science ®Google Scholar
• Wu, S., Müller, H. and Zhang, Z. (2013) Functional data analysis for point processes with rare events. Statistica Sinica, 23(1), 1–23.
   Google Scholar