Models and Insights for Hospital Inpatient Operations: Time-Dependent ED Boarding Time

References

• Allon G, Deo S, Lin W (2013) The impact of size and occupancy of hospital on the extent of ambulance diversion: Theory and evidence. Oper. Res. 61(3):544–562.Link, Google Scholar
• Armony M, Israelit S, Mandelbaum A, Marmor Y, Tseytlin Y, Yom-Tov G (2015) On patient flow in hospitals: A data-based queueing-science perspective. Stochastic Systems. Forthcoming.Link, Google Scholar
• Bair AE, Song WT, Chen Y-C, Morris BA (2010) The impact of inpatient boarding on ED efficiency: A discrete-event simulation study. J. Medical Systems 34(5):919–929.Crossref, Google Scholar
• Bertsekas D, Gallager R (1992) Data Networks (Prentice-Hall, Englewood Cliffs, NJ).Google Scholar
• Birjandi A, Bragg LM (2008) Discharge Planning Handbook for Healthcare: Top 10 Secrets to Unlocking a New Revenue Pipeline (Productivity Press, New York).Crossref, Google Scholar
• Borghans I, Heijink R, Kool T, Lagoe RJ, Westert GP (2008) Benchmarking and reducing length of stay in Dutch hospitals. BMC Health Services Res. 8(1), doi: 10.1186/1472-6963-8-220.Crossref, Google Scholar
• Brown L, Gans N, Mandelbaum A, Sakov A, Shen H, Zeltyn S, Zhao L (2005) Statistical analysis of a telephone call center. J. Amer. Statist. Assoc. 100(469):36–50.Crossref, Google Scholar
• Centers for Disease Control and Prevention (2011) Health, United States, 2010: With special feature on death and dying. Report, Centers for Disease Control and Prevention, Atlanta. http://www.cdc.gov/nchs/data/hus/hus10.pdf.Google Scholar
• Chan C, Yom-Tov G, Escobar GJ (2014) When to use speedup: An examination of service systems with returns. Oper. Res. 62(2):462–482.Link, Google Scholar
• Cochran J, Bharti A (2006) Stochastic bed balancing of an obstetrics hospital. Health Care Management Sci. 9(1):31–45.Crossref, Google Scholar
• Dai JG, Lin W (2005) Maximum pressure policies in stochastic processing networks. Oper. Res. 53(2):197–218.Link, Google Scholar
• Dai JG, Shi P (2014) A two-time-scale approach to time-varying queues for hospital inpatient flow management. Working paper, Cornell University, Ithaca, NY. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2489533.Crossref, Google Scholar
• de Bruin AM, van Rossum AC, Visser MC, Koole GM (2007) Modeling the emergency cardiac in-patient flow: An application of queuing theory. Health Care Management Sci. 10:125–137.Crossref, Google Scholar
• Department of Health, United Kingdom (2004) Achieving timely simple discharge from hospital: A toolkit for the multi-disciplinary team. Report, Department of Health, London. http:// webarchive.nationalarchives.gov.uk/20130107105354/http://www.dh.gov.uk/prod_consum _dh/groups/dh_digitalassets/@dh/@en/documents/ digitalasset/dh_4088367.pdf.Google Scholar
• Feldman Z, Mandelbaum A, Massey WA, Whitt W (2008) Staffing of time-varying queues to achieve time-stable performance. Management Sci. 54(2):324–338.Link, Google Scholar
• Gans N, Koole G, Mandelbaum A (2003) Telephone call centers: Tutorial, review, and research prospects. Manufacturing Service Oper. Management 5(2):79–141.Link, Google Scholar
• Green L (2002) How many hospital beds? Inquiry 39(4):400–412.Crossref, Google Scholar
• Green L (2006) Queueing analysis in healthcare. Hall RW, ed. Patient Flow: Reducing Delay in Healthcare Delivery, International Series in Operations Research and Management Science, Vol. 91 (Springer, New York), 281–307.Crossref, Google Scholar
• Griffin J, Xia S, Peng S, Keskinocak P (2011) Improving patient flow in an obstetric unit. Health Care Management Sci. 15(1):1–14.Crossref, Google Scholar
• Hall MJ, DeFrances CJ, Williams SN, Golosinskiy A, Schwartzman A (2010) National hospital discharge survey: 2007 summary. Natl. Health Stat. Report 29:1–20.Google Scholar
• Hall RW (2012) Bed assignment and bed management. Hall R, ed. Handbook of Healthcare System Scheduling, International Series in Operations Research and Management Science, Vol. 168 (Springer, New York), 177–200.Crossref, Google Scholar
• Hall RW, Belson D, Murali P, Dessouky M (2006) Modeling patient flows through the healthcare system. Hall RW, ed. Patient Flow: Reducing Delay in Healthcare Delivery (Springer, New York), 1–44.Crossref, Google Scholar
• Harrison JM (2003) Brownian models of open processing networks: Canonical representation of workload. Ann. Appl. Probab. 13(1): 390–393.Crossref, Google Scholar
• Helm J, Van Oyen M (2014) Design and optimization methods for elective hospital admissions. Oper. Res. 62(6):1265–1282.Link, Google Scholar
• Helm JE, AhmadBeygi S, Van Oyen MP (2011) Design and analysis of hospital admission control for operational effectiveness. Production Oper. Management 20(3):359–374.Crossref, Google Scholar
• Hoot NR, Aronsky D (2008) Systematic review of emergency department crowding: Causes, effects, and solutions. Ann. Emergency Medicine 52(2):126–136.Crossref, Google Scholar
• Howell E, Bessman E, Kravet S, Kolodner K, Marshall R, Wright S (2008) Active bed management by hospitalists and emergency department throughput. Ann. Internal Medicine 149(11):804–810.Crossref, Google Scholar
• Jacobson SH, Hall SN, Swisher JR (2006) Discrete-event simulation of health care systems. Hall RW, ed. Patient Flow: Reducing Delay in Healthcare Delivery, International Series in Operations Research and Management Science, Vol. 91 (Springer, New York), 211–252.Crossref, Google Scholar
• Khanna S, Boyle J, Good N, Lind J (2011) Impact of admission and discharge peak times on hospital overcrowding. Hansen DP, Maeder AJ, Schaper LK, eds. Health Informatics: The Transformative Power of Innovation, Studies in Health Technology and Informatics, Vol. 168 (IOS, Amsterdam), 82–88.Google Scholar
• Kim S-H, Chan CW, Olivares M, Escobar G (2015) ICU admission control: An empirical study of capacity allocation and its implication on patient outcomes. Management Sci. 61(1):19–38.Link, Google Scholar
• Koizumi N, Kuno E, Smith TE (2005) Modeling patient flows using a queuing network with blocking. Health Care Management Sci. 8(1):49–60.Crossref, Google Scholar
• Kumar PR (1993) Re-entrant lines. Queueing Systems 13(1–3):87–110.Crossref, Google Scholar
• Law AM, Kelton DW (2000) Simulation Modelling and Analysis (McGraw-Hill Education, Columbus, OH).Google Scholar
• Lewis PA, Shedler GS (1978) Simulation methods for Poisson processes in nonstationary systems. Proc. 10th Conf. Winter Simulation, WSC ’78, Vol. 1 (IEEE Press, Piscataway, NJ), 155–163.Google Scholar
• Litvak E, Long MC, Cooper AB, McManus ML (2001) Emergency department diversion: Causes and solutions. Acad. Emergency Medicine 8(11):1108–1110.Google Scholar
• Liu Y, Whitt W (2012) Stabilizing customer abandonment in many-server queues with time-varying arrivals. Oper. Res. 60(6):1551–1564.Link, Google Scholar
• Liu SW, Thomas SH, Gordon JA, Hamedani AG, Weissman JS (2009) A pilot study examining undesirable events among emergency department-boarded patients awaiting inpatient beds. Ann. Emergency Medicine 54(3):381–385.Crossref, Google Scholar
• Mandelbaum A, Momcilovic P, Tseytlin Y (2012) On fair routing from emergency departments to hospital wards: QED queues with heterogeneous servers. Management Sci. 58(7):1273–1291.Link, Google Scholar
• National University Hospital (2011) BMU Training Guide: Inpatient Operations, National University Hospital, Singapore.Google Scholar
• Pines JM, Batt RJ, Hilton JA, Terwiesch C (2011a) The financial consequences of lost demand and reducing boarding in hospital emergency departments. Ann. Emergency Medicine 58(4): 331–340.Crossref, Google Scholar
• Pines JM, Iyer S, Disbot M, Hollander JE, Shofer FS, Datner EM (2008) The effect of emergency department crowding on patient satisfaction for admitted patients. Acad. Emergency Medicine 15(9):825–831.Crossref, Google Scholar
• Pines JM, Hilton JA, Weber EJ, Alkemade AJ, Al Shabanah H, Anderson PD, Bernhard Met al. (2011b) International perspectives on emergency department crowding. Acad. Emergency Medicine 18(12):1358–1370.Crossref, Google Scholar
• Powell ES, Khare RK, Venkatesh AK, Van Roo BD, Adams JG, Reinhardt G (2011) The relationship between inpatient discharge timing and emergency department boarding. J. Emergency Medicine 42(2):186–196.Crossref, Google Scholar
• Ramakrishnan M, Sier D, Taylor P (2005) A two-time-scale model for hospital patient flow. IMA J. Management Math. 16(3): 197–215.Crossref, Google Scholar
• Schneider S, Zwemer F, Doniger A, Dick R, Czapranski T, Davis E (2001) Rochester, New York: A decade of emergency department overcrowding. Acad. Emergency Medicine 8(11):1044–1050.Crossref, Google Scholar
• Shi P (2013) Stochastic modeling and decision making in two healthcare applications: Inpatient flow management and influenza pandemics. Ph.D. dissertation, Georgia Institute of Technology, Atlanta.Google Scholar
• Shi P, Dai JG, Ding D, Ang J, Chou MC, Jin X, Sim J (2014) Patient flow from emergency department to inpatient wards: Empirical observations from a Singaporean hospital. Working paper, Purdue University, West Lafayette, IN. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2517050.Google Scholar
• Sinagpore Ministry of Health (2012) Waiting time for admission to ward. Accessed October 30, 2014, https://www.moh.gov.sg/content/moh_web/home/statistics/healthcare_institutionstatistics/ Waiting_Time_for_Admission_to_Ward.html.Google Scholar
• Singer AJ, Thode J, Henry C, Viccellio P, Pines JM (2011) The association between length of emergency department boarding and mortality. Acad. Emergency Medicine 18(12):1324–1329.Crossref, Google Scholar
• Teow K, El-Darzi E, Foo C, Jin X, Sim J (2012) Intelligent analysis of acute bed overflow in a tertiary hospital in Singapore. J. Medical Systems 36(3):1873–1882.Crossref, Google Scholar
• Thompson S, Nunez M, Garfinkel R, Dean M (2009) Efficient short-term allocation and reallocation of patients to floors of a hospital during demand surges. Oper. Res. 57(2):261–273.Link, Google Scholar
• United States General Accounting Office (2003) Hospital emergency departments: Crowded conditions vary among hospitals and communities Report, United States General Accounting Office, Washington, DC.Google Scholar
• Vericourt Fd, Jennings OB (2011) Nurse staffing in medical units: A queueing perspective. Oper. Res. 59(6):1320–1331.Link, Google Scholar
• Wong HJ, Morra D, Caesar M, Carter MW, Abrams H (2010) Understanding hospital and emergency department congestion: An examination of inpatient admission trends and bed resources. Canadian J. Emergency Medicine 34(1):18–26.Google Scholar
• Yancer DA, Foshee D, Cole H, Beauchamp R, de la Pena W, Keefe T, Smith W, Zimmerman K, Lavine M, Toops B (2006) Managing capacity to reduce emergency department overcrowding and ambulance diversions. Joint Commission J. Quality Patient Safety 32(5):239–245.Crossref, Google Scholar
• Yankovic N, Green LV (2011) Identifying good nursing levels: A queuing approach. Oper. Res. 59(4):942–955.Link, Google Scholar
• Yao DD (1994) Stochastic Modeling and Analysis of Manufacturing Systems, Springer Series in Operations Research (Springer, New York).Crossref, Google Scholar
• Zacharias C, Armony M (2015) Joint panel sizing and appointment scheduling in outpatient care. Working paper, University of Miami, Coral Gables, FL.Google Scholar
• Zeltyn S, Marmor YN, Mandelbaum A, Carmeli B, Greenshpan O, Mesika Y, Wasserkrug Set al., eds. (2011) Simulation-based models of emergency departments: Operational, tactical, and strategic staffing. ACM Trans. Model. Comput. Simul. 21(4): Article 24.Crossref, Google Scholar