Health Care Management Science

, Volume 21, Issue 3, pp 305–316 | Cite as

RFID-based information visibility for hospital operations: exploring its positive effects using discrete event simulation

  • Daniel A. AsamoahEmail author
  • Ramesh Sharda
  • Howard N. Rude
  • Derek Doran


Long queues and wait times often occur at hospitals and affect smooth delivery of health services. To improve hospital operations, prior studies have developed scheduling techniques to minimize patient wait times. However, these studies lack in demonstrating how such techniques respond to real-time information needs of hospitals and efficiently manage wait times. This article presents a multi-method study on the positive impact of providing real-time scheduling information to patients using the RFID technology. Using a simulation methodology, we present a generic scenario, which can be mapped to real-life situations, where patients can select the order of laboratory services. The study shows that information visibility offered by RFID technology results in decreased wait times and improves resource utilization. We also discuss the applicability of the results based on field interviews granted by hospital clinicians and administrators on the perceived barriers and benefits of an RFID system.


RFID Information visibility Discrete event simulation Scheduling Health care Field interview 

JEL Classification

90B22 90B36 90B90 


  1. 1.
    Brezina PR, Shah AA, Myers ER et al (2013) How Obamacare will impact reproductive health. In: Thieme Medical Publishers. Semin Reprod Med 31:189–197Google Scholar
  2. 2.
    Lailomthong N, Prichanont S (2014) Patient’s waiting time reduction in outpatient department. 468–472Google Scholar
  3. 3.
    Su S, Shih CL (2003) Managing a mixed-registration-type appointment system in outpatient clinics. Int J Med Inform 70:31–40CrossRefGoogle Scholar
  4. 4.
    Motorola (2010) Mobility throughout hospital lab workflows: improve efficiency and reduce errors with real-time information at the point of work.Google Scholar
  5. 5.
    Decker K, Li J (1998) Coordinated hospital patient scheduling. In: Multi Agent Systems 1998. Proceedings. International Conference, p 104–111Google Scholar
  6. 6.
    Xu SH, Gao L, Ou J (2007) Service performance analysis and improvement for a ticket queue with balking customers. Manag Sci 53:971–990CrossRefGoogle Scholar
  7. 7.
    Zhou W (2009) RFID and item-level information visibility. Eur J Oper Res 198:252–258CrossRefGoogle Scholar
  8. 8.
    Yazici HJ (2014) An exploratory analysis of hospital perspectives on real time information requirements and perceived benefits of RFID technology for future adoption. Int J Inf Manag 34:603–621CrossRefGoogle Scholar
  9. 9.
    Rosen MA, Goeschel CA, Che X-X et al (2015) Simulation in the executive suite: lessons learned for building patient safety leadership. Simul Healthc 10:372–377CrossRefGoogle Scholar
  10. 10.
    Fetter RB, Thompson JD (1966) Patients’ waiting time and doctors’ idle time in the outpatient setting. Health Serv Res 1:66–90Google Scholar
  11. 11.
    Xiao N, Dutta S, Sharman R, Rao HR (2009) A simulation based study in a hospital emergency department: capacity and workflow issues. AMCIS 2009 Proc 495Google Scholar
  12. 12.
    Haraden C, Resar R (2004) Patient flow in hospitals: understanding and controlling it better. Front Health Serv Manag 20:3–15CrossRefGoogle Scholar
  13. 13.
    Bailey NTJ (1952) A study of queues and appointment systems in hospital out-patient departments, with special reference to waiting-times. J R Stat Soc 14:185–199Google Scholar
  14. 14.
    Cayirli T, Veral E (2003) Outpatient scheduling in healthcare: a review of literature. Prod Oper Manag 12:519–549. doi: 10.1111/j.1937-5956.2003.tb00218.x CrossRefGoogle Scholar
  15. 15.
    Brahimi M, Worthington DJ (1991) Queueing models for out-patient appointment systems-a case study. J Oper Res Soc 42:733–746Google Scholar
  16. 16.
    Yeh J, Lin W (2007) Using simulation technique and genetic algorithm to improve the quality care of a hospital emergency department. Expert Syst Appl 32:1073–1083CrossRefGoogle Scholar
  17. 17.
    Weinstein R (2005) RFID: a technical overview and its application to the Enterprise. IT Prof 7:27–33CrossRefGoogle Scholar
  18. 18.
    Chowdhury B, Khosla R (2007) RFID-based hospital real-time patient management system. In: Proc. - 6th IEEE/ACIS Int. Conf. Comput. Inf. Sci. ICIS 2007; 1st IEEE/ACIS Int. Work. e-Activity, IWEA 2007. p 363–368Google Scholar
  19. 19.
    Amini M, Otondo RF, Janz BD, Pitts MG (2009) Simulation modeling and analysis: a collateral application and exposition of RFID technology. Prod Oper Manag 16:586–598. doi: 10.1111/j.1937-5956.2007.tb00282.x CrossRefGoogle Scholar
  20. 20.
    Fisher JA, Monahan T (2012) Evaluation of real-time location systems in their hospital contexts. Int J Med Inform 81:705–712CrossRefGoogle Scholar
  21. 21.
    Wyld DC (2008) RuBee: applying low-frequency technology for retail and medical uses. Manag Res News 31:549–554CrossRefGoogle Scholar
  22. 22.
    Coustasse A, Tomblin S, Slack C (2013) Impact of radio-frequency identification (RFID) technologies on the hospital supply chain: a literature review. Perspect Heal Inf Manag 1;10:1dGoogle Scholar
  23. 23.
    Ferrer G, Dew N, Apte U (2010) When is RFID right for your service? Int J Prod Econ 124:414–425CrossRefGoogle Scholar
  24. 24.
    Burke D, Yu F, Au D, Menachemi N (2009) Best of breed strategies-hospital characteristics associated with organizational HIT strategy. Journal of Healthcare Information Management 23:46–51Google Scholar
  25. 25.
    Delen D, Hardgrave BC, Sharda R (2007) RFID for better supply-chain management through enhanced information visibility. Prod Oper Manag 16:613–624. doi: 10.1111/j.1937-5956.2007.tb00284.x CrossRefGoogle Scholar
  26. 26.
    Joines JA, Roberts SD (2010) Simulation modeling with SIMIO: A workbook, 3rd edn. North Carolina State University, Raleigh, North CarolinaGoogle Scholar
  27. 27.
    Burns J (2013) Study at Johns Hopkins shows price transparency works: physicians order fewer clinical pathology laboratory tests when they know the cost. Dark Dly, In Accessed 15 May 2016Google Scholar
  28. 28.
    Prinyapol N, Fan JP, Lau S (2009) A hospital based dynamic platform workflow management.Google Scholar
  29. 29.
    Takakuwa S, Shiozaki H (2004) Functional analysis for operating emergency department of a general hospital. In: Simul. Conf. 2004. Proc. 2004 Winter 2:2003–2011Google Scholar
  30. 30.
    Rohleder TR, Klassen KJ (2002) Rolling horizon appointment scheduling: a simulation study. Health Care Management Science 5:201–209. doi: 10.1023/A:1019748703353 CrossRefGoogle Scholar
  31. 31.
    Ogden J, Bavalia K, Bull M et al (2004) “I want more time with my doctor”: a quantitative study of time and the consultation. Fam Pract 21:479–483. doi: 10.1093/fampra/cmh502 CrossRefGoogle Scholar
  32. 32.
    Hing E, Hall MJ, Ashman JJ, Xu J (2010) National hospital ambulatory medical care survey: 2007 outpatient department summary. Natl Health Stat Report 1–32Google Scholar
  33. 33.
    Wijewickrama A, Takakuwa S (2005) Simulation analysis of appointment scheduling in an outpatient department of internal medicine. Simul Conf 2005 Proc Winter 10 pp. doi: 10.1109/WSC.2005.1574515
  34. 34.
    Huarng F, Lee MH (1996) Using simulation in out-patient queues: a case study. International Journal of Health Care Quality Assurance 9:21–25CrossRefGoogle Scholar
  35. 35.
    Cangialosi A, Monaly JE Jr, Yang SC (2007) Leveraging RFID in hospitals: patient life cycle and mobility perspectives. Commun Mag IEEE 45:18–23CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Daniel A. Asamoah
    • 1
    Email author
  • Ramesh Sharda
    • 2
  • Howard N. Rude
    • 3
  • Derek Doran
    • 3
  1. 1.Information Systems and Supply Chain Management DepartmentWright State UniversityDaytonUSA
  2. 2.Management Science and Information Systems DepartmentOklahoma State UniversityStillwaterUSA
  3. 3.Computer Science and Engineering DepartmentWright State UniversityDaytonUSA

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