[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Springer Nature Link
Log in

Human resource management: new approach to nurse scheduling by considering human error

  • Original Article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

Human error is a critical concern in healthcare systems from primary care clinics to operating rooms in hospitals. Prevention or reduction of the chance of occurrence of such errors through increasing human reliabilities is tremendously important and deserves to be focused within personnel scheduling problems in healthcare systems. The present study is to develop a new multi-objective integer mathematical model which includes human errors of nurses to determine optimal shift scheduling of nurses. In addition to medical errors, several constraints in real-world problem including “minimum number of available nurses in each shift”, “restrictions on shift rotation for each nurse”, and “Minimum and maximum working hours in a week” are also taken into account. Nurses’ preference score, allocation costs, penalty cost of violating soft constraints, and human errors are all considered as objectives to be optimized. The multi-objective model, developed in this study, is solved by employing the weighted-sum method. To verify and validate the proposed model, a test problem is also solved. Sensitivity analysis on the model indicates that the solution method can reach acceptable solutions within an acceptable time. The present study is to help decision-makers to achieve optimal scheduling for decreasing costs and improving safety in healthcare systems. Based on this approach, decision makers can totally minimize the number of errors by considering the number of nurses required in each grade as well as proper allocation of them to different work shifts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Aickelin U, Dowsland KA (2004) An indirect genetic algorithm for a nurse-scheduling problem. Comput Oper Res 31:761–778

    Article  MATH  Google Scholar 

  • Aickelin U, Li J (2007) An estimation of distribution algorithm for nurse scheduling. Ann Oper Res 155:289–309

    Article  MathSciNet  MATH  Google Scholar 

  • Åkerstedt T (1990) Psychological and psychophysiological effects of shift work. Scand J Work Environ Health 16(1):67–73

    Article  Google Scholar 

  • Ásgeirsson EI, Sigurðardóttir GL (2016) Near-optimal MIP solutions for preference based self-scheduling. Ann Oper Res 239:273–293

    Article  MathSciNet  MATH  Google Scholar 

  • Azadeh A, Ahvazi MP, Haghighii SM, Keramati A (2016) Simulation optimization of an emergency department by modeling human errors. Simul Model Pract Theory 67:117–136

    Article  Google Scholar 

  • Bastan M, Azizi L, Grösser S, Sheikhahmadi F (2018a) Analysis of development policies in occupational health and safety management system: a system dynamics approach. In: The 2nd IEOM European international conference on industrial engineering and operations management, Paris, France

  • Bastan M, Grösser S, Zadfallah E (2018b) Model-based risk assessment to clinical risk management policies. In: The 36th international conference of the system dynamics society Reykjavík, Island

  • Beddoe G, Petrovic S, Li J (2009) A hybrid metaheuristic case-based reasoning system for nurse rostering. J Sched 12:99–119

    Article  MATH  Google Scholar 

  • Brucker P, Burke EK, Curtois T, Qu R, Vanden Berghe G (2010) A shift sequence based approach for nurse scheduling and a new benchmark dataset. J Heuristics 16:559–573

    Article  MATH  Google Scholar 

  • Brunner JO, Edenharter GM (2011) Long term staff scheduling of physicians with different experience levels in hospitals using column generation. Health Care Manag Sci 14:189–202

    Article  Google Scholar 

  • Brunner JO, Bard JF, Kolisch R (2009) Flexible shift scheduling of physicians. Health Care Manag Sci 12:285–305

    Article  Google Scholar 

  • Burke EK, De Causmaecker P, Berghe GV, Van Landeghem H (2004) The state of the art of nurse rostering. J Sched 7:441–499

    Article  MathSciNet  MATH  Google Scholar 

  • Burke EK, Li J, Qu R (2010) A hybrid model of integer programming and variable neighbourhood search for highly-constrained nurse rostering problems. Eur J Oper Res 203:484–493

    Article  MathSciNet  MATH  Google Scholar 

  • De Causmaecker P, Vanden Berghe G (2011) A categorisation of nurse rostering problems. J Sched 14:3–16

    Article  Google Scholar 

  • De Grano ML, Medeiros D, Eitel D (2009) Accommodating individual preferences in nurse scheduling via auctions and optimization. Health Care Manag Sci 12:228–242

    Article  Google Scholar 

  • Ernst AT, Jiang H, Krishnamoorthy M, Sier D (2004) Staff scheduling and rostering: a review of applications, methods and models. Eur J Oper Res 153:3–27

    Article  MathSciNet  MATH  Google Scholar 

  • Govindan K, Khodaverdi R, Vafadarnikjoo A (2015) Intuitionistic fuzzy based DEMATEL method for developing green practices and performances in a green supply chain. Expert Syst Appl 42:7207–7220

    Article  Google Scholar 

  • Govindan K, Khodaverdi R, Vafadarnikjoo A (2016) A grey DEMATEL approach to develop third-party logistics provider selection criteria. Ind Manag Data Syst 116:690–722

    Article  Google Scholar 

  • Gutjahr WJ, Rauner MS (2007) An ACO algorithm for a dynamic regional nurse-scheduling problem in Austria. Comput Oper Res 34:642–666

    Article  MATH  Google Scholar 

  • Hamid M, Barzinpour F, Hamid M, Mirzamohammadi S (2018a) A multi-objective mathematical model for nurse scheduling problem with hybrid DEA and augmented ε-constraint method: a case study. J Ind Syst Eng 11:98–108

    Google Scholar 

  • Hamid M, Hamid M, Musavi M, Azadeh A (2018b) Scheduling elective patients based on sequence-dependent setup times in an open-heart surgical department using an optimization and simulation approach. Simulation (in press)

  • Hamid M, Hamid M, Nasiri MM, Ebrahimnia M (2018c) Improvement of operating room performance using a multi-objective mathematical model and data envelopment analysis: a case study. Int J Ind Eng Prod Res 29:117–132. https://doi.org/10.22068/ijiepr.29.2.117

    Article  Google Scholar 

  • Huang HZ, Tian Z, Zuo MJ (2005) Intelligent interactive multiobjective optimization method and its application to reliability optimization. IIE Trans 37:983–993

    Article  Google Scholar 

  • Ikegami A, Niwa A (2003) A subproblem-centric model and approach to the nurse scheduling problem. Math Program 97:517–541

    Article  MathSciNet  MATH  Google Scholar 

  • Jafari H, Salmasi N (2015) Maximizing the nurses’ preferences in nurse scheduling problem: mathematical modeling and a meta-heuristic algorithm. J Ind Eng Int 11:439–458

    Article  Google Scholar 

  • Jamili A, Hamid M, Gharoun H, khoshnoudi R (2018) Developing a comprehensive and multi-objective mathematical model for university course timetabling problem: a real case study. In: Conference: proceedings of the international conference on industrial engineering and operations management, Paris, France, pp 2108–2119

  • Jeang A, Chiang A-J (2012) Economic and quality scheduling for effective utilization of operating rooms. J Med Syst 36:1205–1222

    Article  Google Scholar 

  • Landrigan CP et al (2004) Effect of reducing interns’ work hours on serious medical errors in intensive care units. N Engl J Med 351:1838–1848

    Article  Google Scholar 

  • Leape LL (1994) Error in medicine. JAMA 272:1851–1856

    Article  Google Scholar 

  • Lim G, Mobasher A (2011) AM robust nurse scheduling problem. In: Proceedings of the 2011 industrial engineering research conference

  • Maenhout B, Vanhoucke M (2008) Comparison and hybridization of crossover operators for the nurse scheduling problem. Ann Oper Res 159:333–353

    Article  MATH  Google Scholar 

  • Mavrotas G, Florios K (2013) An improved version of the augmented ε-constraint method (AUGMECON2) for finding the exact pareto set in multi-objective integer programming problems. Appl Math Comput 219:9652–9669

    MathSciNet  MATH  Google Scholar 

  • Miller HE, Pierskalla WP, Rath GJ (1976) Nurse scheduling using mathematical programming. Oper Res 24:857–870

    Article  MATH  Google Scholar 

  • Mitler MM, Carskadon MA, Czeisler CA, Dement WC, Dinges DF, Graeber RC (1988) Catastrophes, sleep, and public policy: consensus report. Sleep 11:100

    Article  Google Scholar 

  • Mokhtari H, Salmasnia A, Bastan M (2012) Three dimensional time, cost and quality tradeoff optimization in project decision making. Adv Mater Res 433–440:5746–5752. https://doi.org/10.4028/www.scientific.net/AMR.433-440.5746

    Article  Google Scholar 

  • Moz M, Vaz Pato M (2007) A genetic algorithm approach to a nurse rerostering problem. Comput Oper Res 34:667–691

    Article  MATH  Google Scholar 

  • Ogulata SN, Koyuncu M, Karakas E (2008) Personnel and patient scheduling in the high demanded hospital services: a case study in the physiotherapy service. J Med Syst 32:221–228

    Article  Google Scholar 

  • Parr D, Thompson JM (2007) Solving the multi-objective nurse scheduling problem with a weighted cost function. Ann Oper Res 155:279–288

    Article  MathSciNet  MATH  Google Scholar 

  • Randhawa S, Sitompul D (1990) Nurse rostering models: a state-of-the-art. Rev J Soc Health Syst 2:62–72

    Google Scholar 

  • Rasmussen J (1982) Human errors. A taxonomy for describing human malfunction in industrial installations. J Occup Accid 4:311–333

    Article  Google Scholar 

  • Ribak J et al (1983) Diurnal rhythmicity and air force flight accidents due to pilot error. Aviat Space Environ Med 54(12):1096–1099

    Google Scholar 

  • Roth C, Brewer M, Wieck KL (2017) Using a Delphi method to identify human factors contributing to nursing errors. Nurs Forum 52(3):173–179. https://doi.org/10.1111/nuf.12178

    Article  Google Scholar 

  • Scott LD, Rogers AE, Hwang WT, Zhang Y (2006) Effects of critical care nurses’ work hours on vigilance and patients’ safety. Am J Crit Care 15:30–37

    Google Scholar 

  • Silén-Lipponen M, Tossavainen K, Turunen H, Smith A (2004) Potential errors and their prevention in operating room teamwork as experienced by Finnish. Br Am Nurses Int J Nurs Pract 11:21–32

    Article  Google Scholar 

  • Svirsko AC, Norman BA, Rausch D, Woodring J (2019) Using mathematical modeling to improve the emergency department nurse-scheduling process. J Emerg Nurs 45(4):425–432

    Article  Google Scholar 

  • Topaloglu S (2009) A shift scheduling model for employees with different seniority levels and an application in healthcare. Eur J Oper Res 198:943–957

    Article  MathSciNet  MATH  Google Scholar 

  • Valouxis C, Gogos C, Goulas G, Alefragis P, Housos E (2012) A systematic two phase approach for the Nurse Rostering problem European Journal of Operational Research

  • Vanhoucke M, Maenhout B (2009) On the characterization and generation of nurse scheduling problem instances. Eur J Oper Res 196:457–467

    Article  MATH  Google Scholar 

  • Warner M, Keller B, Martel S (1990) Automated nurse scheduling. J Soc Health Syst 2:66–80

    Google Scholar 

  • Wong T, Xu M, Chin K (2014) A two-stage heuristic approach for nurse scheduling problem: a case study in an emergency department. Comput Oper Res 51:99–110

    Article  MathSciNet  MATH  Google Scholar 

  • Yazdanparast R, Hamid M, Azadeh A, Keramati A (2018) An intelligent algorithm for optimization of resource allocation problem by considering human error in an emergency. J Ind Syst Eng 11:287–309

    Google Scholar 

  • Yilmaz E (2012) A mathematical programming model for scheduling of nurses’ labor shifts. J Med Syst 36:491–496

    Article  Google Scholar 

  • Youssef A, Senbel S (2018) A Bi-level heuristic solution for the nurse scheduling problem based on shift-swapping. In: 2018 IEEE 8th annual computing and communication workshop and conference (CCWC). IEEE, pp 72–78

  • Zhao Z, Niu P, Ji X, Sweet RM (2017) State of simulation in healthcare education: an initial survey in Beijing. J Soc Laparoendosc Surg 21(1):1–8. https://doi.org/10.4293/JSLS.2016.00090

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

    Peyman Kiani Nahand, Mahdi Hamid & Ali Mollajan

  2. Department of Industrial Engineering, University of Eyvanekey, Garmsar, Iran

    Mahdi Bastan

Authors
  1. Peyman Kiani Nahand
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mahdi Hamid
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mahdi Bastan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ali Mollajan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mahdi Bastan.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kiani Nahand, P., Hamid, M., Bastan, M. et al. Human resource management: new approach to nurse scheduling by considering human error. Int J Syst Assur Eng Manag 10, 1429–1443 (2019). https://doi.org/10.1007/s13198-019-00893-8

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-019-00893-8

Keywords

Search

Navigation