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Reducing Crowding in Hospital Inpatient Unit Using Queuing Theory

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Advanced Information Technology, Services and Systems (AIT2S 2017)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 25))

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Abstract

Nowadays, emergency department encounters several difficulties to provide quality service to patients, especially inpatient unit that faces a big number of patients random arrivals with different ages and acuities. Patients must be examined and treated in a restricted time, while the constraint of this unit which is limited capacity (human and materiel resources) given the big daily load creates high length of stay, long waiting times and then overcrowding. Those factors impact patient satisfaction and service quality. So, our goal is patients’ length of stay and waiting time reduction by increasing inpatient unit service rate according to care load. In this paper, we present our approach which consists essentially in determining the adequate combinations of human and materiel resources to be attributed to each inpatient unit room, in order to insure and provide the optimal service rate. This approach is performed using queuing theory.

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References

  1. Mezouar, H., El Afia, A., Chiheb, R.: A new concept of intelligence in the electric power management. In: 2nd IEEE International Conference on Electrical and Information Technologies, Tangier (2016)

    Google Scholar 

  2. Mezouar, H., El Afia, A., Chiheb, R., Ouzayd, F.: Proposal of a modeling approach and a set of KPI to the drug supply chain within the hospital. In: 3rd IEEE International Conference on Logistics Operations Management, Fez (2016)

    Google Scholar 

  3. Mezouar, H., EL Afia, A., Chiheb, R., Ouzayd, F.: Toward a process model of Moroccan electric supply chain. In: IEEE International Conference on Electrical and Information Technologies, Marrakech (2015)

    Google Scholar 

  4. Izady, N., Worthington, D.: Setting staffing requirements for time dependent queuing networks: The case of accident and emergency departments. Eur. J. Oper. Res. 219, 531–540 (2012)

    Article  MATH  Google Scholar 

  5. Paul, J.A., Lin, L.: Models for improving patient throughput and waiting at hospital emergency departments. Am. J. Emerg. Med. 43, 1119–1126 (2012)

    Article  Google Scholar 

  6. Jebbor, S., El Afia, A., Chiheb, R., Ouzayd, F.: Comparative analysis of drug supply and inventory management methods literature review. In: 4th IEEE International Colloquium on Information Science and Technology, Tangier (2016)

    Google Scholar 

  7. Jebbor, S., El Afia, A., Chiheb, R., Ouzayd, F.: Management and control of stochastic drug supply chain by KANBAN and Petri Net. In: 3rd IEEE International Conference on Logistics Operations Management, Fez (2016)

    Google Scholar 

  8. Boyle, A., Beniuk, K., Higginson, I., Atkinson, P.: Emergency department crowding: time for interventions and policy evaluations. Emerg. Med. Int. 2012, 1–8 (2012)

    Article  Google Scholar 

  9. Chen, T.L.: Decision support system based on distributed simulation optimization for medical resource allocation in emergency department. Lecture Notes in Computer Science, vol. 8527, pp. 15–24 (2014)

    Google Scholar 

  10. Ben Bachouch, R., Guinet, A., Hajri-Gabouj, S.: An integer linear model for hospital bed planning. Int. J. Prod. Econ. 140, 833–843 (2012)

    Article  Google Scholar 

  11. Guide de gestion de l’unité d’urgence, la Direction des communications du ministère de la Santé et des Services sociaux, bibliothèque nationale du Québec. http://www.banq.qc.ca/dotAsset/ae7e54d4-6379-4fea-88d8-bdac78173e06.pdf

  12. Mital, K.M.: Queuing analysis for outpatient and inpatient services: a case study. Manag. Decis. 48, 419–439 (2010)

    Article  Google Scholar 

  13. Department of Veterans Affairs, Office of Construction & Facilities Management, Medical/surgical inpatient unit & intensive care nursing units. https://www.cfm.va.gov/til/dGuide/dgInpatientNU.pdf

  14. Vass, H., Szabo, Z.K.: Application of queuing model to patient flow in emergency department case study. Procedia Econ. Finan. 32, 479–487 (2015)

    Article  Google Scholar 

  15. Berquedich, M., Kamach, O., Masmoudi, M., Deshayes, L.: Méthodologie organisationnelle des processus en environnement incertain et perturbé: application au domaine hospitalier. In: The 10th International Conference: Conception et Production Intégrées, CPI 2015, Tangier, pp. 1–7 (2015)

    Google Scholar 

  16. Vissers, J.M.H.: Patient flow-based allocation of inpatient resources: A case study. Eur. J. Oper. Res. 105, 356–370 (1998)

    Article  MATH  Google Scholar 

  17. Hulshof, P.J.H., Kortbeek, N., Boucherie, R.J., Hans, E.W., Bakker, P.J.M.: Taxonomic classification of planning decisions in health care: a structured review of the state of the art in OR/MS. Health Syst. 1, 129–175 (2012)

    Article  Google Scholar 

  18. Bai, J., Fügener, A., Schoenfelder, J., Brunner, J. O.: Operations research in intensive care unit management: a literature review. Health Care Manage. Sci. 1–24 (2016)

    Google Scholar 

  19. Shi, P., Dai, J.G., Ding, D., Ang, J., Chou, M.C., Jin, X., Sim, J.: Patient Flow from Emergency Department to Inpatient Wards: Empirical Observations from a Singaporean Hospital (2013)

    Google Scholar 

  20. Tancrez, J.S., Roland, B., Cordier, J.P., Riane, F.: Étude de la perturbation par les urgences du planning opératoire. Logistique Manage. 19, 4–52 (2011)

    Article  Google Scholar 

  21. Casalino, E., Choquet, Ch., Bernard, J., Debit, A., Doumenc, B., Berthoumieu, A., Wargon, M.: Predictive variables of an emergency department quality and performance indicator: a 1-year prospective, observational, cohort study evaluating hospital and emergency census variables and emergency department time interval measurements. Emerg. Med. J. 30, 45–638 (2013)

    Article  Google Scholar 

  22. Zeng, Z., Ma, X., Hu, Y., Li, J., Bryant, D.: A simulation study to improve quality of care in the emergency department of a community hospital. J. Emerg. Nursing 38, 8–322 (2012)

    Article  Google Scholar 

  23. Jlassi, J., El Mhamedi, A., Chabchoub, H.: Networks of queues with multiple customer types: application in emergency departments. Int. J. Behav. Healthc. Res. 1, 400–419 (2009)

    Article  Google Scholar 

  24. Zeltyn, S., Carmeli, B., Greenshpan, O., Mesika, Y., Wasserkrug, S., Vortman, P., Marmor, Y.N., Mandelbaum, A., Shtub, A., Lauterman, T., Schwartz, D., Moskovitch, K., Tzafrir, S., Basis, F.: Simulation-based models of emergency departments: operational, tactical and strategic staffing. ACM Trans. Model. Comput. Simul. 21, 1–25 (2011)

    Article  Google Scholar 

  25. Askarian, M., Hesami, S.A., Kharazmi, E., Hatam, N., Haghighinejad, H.A., Danaei, M.: Evaluation of the patients’ queue status at emergency department of nemazee hospital and how to decrease it, 2014. Glob. J. Health Sci. 9, 1916–9744 (2017)

    Google Scholar 

  26. Amaral, T.M., Costa, A.P.C.: Improving decision-making and management of hospital resources: An application of the PROMETHEE II method in an emergency department. Oper. Res. Health Care 3, 1–6 (2014)

    Article  Google Scholar 

  27. Gül, M., Guneri, A.F.: A comprehensive review of emergency department simulation applications for normal and disaster conditions. Comput. Ind. Eng. 83, 327–344 (2015)

    Article  Google Scholar 

  28. de Bruin, A.M., Bekker, R., van Zanten, L., Koole, G.M.: Dimensioning hospital wards using the Erlang loss model. Ann. Oper. Res. 178, 23–43 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  29. Green, L.V., Soares, J., Giglio, J.F., Robert, R.A.: Using queuing theory to increase the effectiveness of emergency department provider staffing. Acad. Emerg. Med. 13, 61–68 (2006)

    Article  Google Scholar 

  30. Beeknoo, N., Jones, R.P.: Achieving economy of scale in critical care, planning information necessary to support the choice of bed numbers. British J. Med. Med. Res. 17, 1–15 (2016)

    Google Scholar 

  31. Green, L.V., Liu, N.: A study of New York city obstetrics units demonstrates the potential for reducing hospital inpatient capacity. Med. Care Res. Rev. 72, 86–168 (2015)

    Article  Google Scholar 

  32. Boulton, J., Akhtar, N., Shuaib, A., Bourke, P.: Waiting for a stroke bed: Planning stroke unit capacity using queuing theory. Int. J. Healthc. Manage. 9, 4–10 (2016)

    Article  Google Scholar 

  33. Lane, D.C., Monefeldt, C., Rosenhead, J.V.: Looking in the wrong place for healthcare improvements: A system dynamics study of an accident and emergency department. J. Oper. Res. Soc. 51, 518–531 (2000)

    Article  MATH  Google Scholar 

  34. Defachelle, C.: L’organisation des soins en hospitalisation de jour: quelles contraintes pour quels enjeux?. Mémoire de l’Ecole Nationale de la Santé Publique, France (1999)

    Google Scholar 

  35. Chaabane, S.: Gestion prédictive des blocs opératoires. INSA de Lyon, France (2004)

    Google Scholar 

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Authors and Affiliations

  1. Mohammed V University in Rabat, Rabat, Morocco

    Sara Jebbor, Abdellatif El Afia & Raddouane Chiheb

Authors
  1. Sara Jebbor
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  2. Abdellatif El Afia
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  3. Raddouane Chiheb
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Corresponding author

Correspondence to Sara Jebbor .

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Editors and Affiliations

  1. Faculty of Sciences and Technologies, Tangier, Morocco

    Mostafa Ezziyyani

  2. Faculty of Sciences and Technologies, University Hassan 1st, Settat, Morocco

    Mohamed Bahaj

  3. Faculty of Sciences and Technologies, Mohammedia, Morocco

    Faddoul Khoukhi

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Jebbor, S., El Afia, A., Chiheb, R. (2018). Reducing Crowding in Hospital Inpatient Unit Using Queuing Theory. In: Ezziyyani, M., Bahaj, M., Khoukhi, F. (eds) Advanced Information Technology, Services and Systems. AIT2S 2017. Lecture Notes in Networks and Systems, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-69137-4_40

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  • DOI: https://doi.org/10.1007/978-3-319-69137-4_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69136-7

  • Online ISBN: 978-3-319-69137-4

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