Skip to main content
SpringerLink
Log in

Improving Clinic Operational Efficiency and Utilization with RTLS

  • Systems-Level Quality Improvement
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

New sources of operational data are leading to novel healthcare delivery system design and opportunities to support operational planning and decision-making. Technologies such as real time locating systems (RTLS) provide a unique view and understanding of how healthcare delivery settings behave and respond to operational design changes. In this paper RTLS data from an outpatient clinical setting is leveraged to identify the appropriate number of scheduled providers in order to improve the utilization of the clinical space while balancing the negative effects of clinic congestion. The approaches presented pair historical utilization rates for the clinical space with scheduled provider and patient volumes to support scheduling decisions in an operationally flexible clinic design. These historical data are augmented with clinic staff observation logs to identify target utilization rates as well as high congestion levels. Results are presented for two approaches: one where utilization of clinical space is a key performance metric and another where the decision-maker may be risk averse toward the use of provider time and use a probabilistic approach to determine provider staffing levels.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Reid, P. P. , Compton, W. D, Grossman, J. H, Fanjiang, G., et al., Building a better delivery system: a new engineering/health care partnership. Vol. 15. Washington: National Academies Press, 2005.

    Google Scholar 

  2. Cutler, D. M., Rising medical costs mean more rough times ahead. JAMA 318(6):508–509, 2017.

    Article  Google Scholar 

  3. Cote, M. J., Patient flow and resource utilization in an outpatient clinic. Socioecon. Plann. Sci. 33(3):231–245, 1999.

    Article  Google Scholar 

  4. Berg, B., Denton, B., Nelson, H., Balasubramanian, H., Rahman, A., Bailey, A., and Lindor, K., A discrete event simulation model to evaluate operational performance of a colonoscopy suite. Med. Decis. Making 30(3):380–387, 2010.

    Article  Google Scholar 

  5. Santibáñez, P, Chow, V.S., French, J., Puterman, M.L., and Tyldesley, S., Reducing patient wait times and improving resource utilization at British Columbia cancer agency’s ambulatory care unit through simulation. Health Care Manag Sci 12(4):392, 2009.

    Article  Google Scholar 

  6. Norouzzadeh, S., Riebling, N., Carter, L., Conigliaro, J., and Doerfler, M.E.: Simulation modeling to optimize healthcare delivery in an outpatient clinic. In: Winter Simulation Conference (WSC), 2015. pp. 1355–1366. IEEE, 2015

  7. Rohleder, T.R., Bischak, D.P., and Baskin, L.B., Modeling patient service centers with simulation and system dynamics. Health Care Manag. Sci. 10(1):1–12, 2007.

    Article  Google Scholar 

  8. Vahdat, V., Griffin, J., and Stahl, J.E.: Decreasing patient length of stay via new flexible exam room allocation policies in ambulatory care clinics. Health Care Manag Sci, 1–25, 2017

  9. Berg, B., Longley, G., and Dunitz, J.: Use of simulation to evaluate resource assignment policies in a multidisciplinary outpatient clinic. In: Proceedings of the 2018 Winter Simulation Conference, page in press. Winter Simulation Conference, 2018

  10. Yazici, H.J., 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(5):603–621, 2014.

    Article  Google Scholar 

  11. Yao, W., Chu, C. -H., and Li, Z., The adoption and implementation of rfid technologies in healthcare: a literature review. J. Med. Syst. 36(6):3507–3525, 2012.

    Article  Google Scholar 

  12. Boulos, M.N.K., and Berry, G., Real-time locating systems (rtls) in healthcare: a condensed primer. Int. J. Health Geograph. 11(1):25, 2012.

    Article  Google Scholar 

  13. Østbye, T, Lobach, D.F., Cheesborough, D., Lee, A.M.M., Krause, K.M., Hasselblad, V., and Bright, D., Evaluation of an infrared/radiofrequency equipment-tracking system in a tertiary care hospital. J. Med. Syst. 27(4):367–380, 2003.

    Article  Google Scholar 

  14. Boginski, V., Mun, I.K., Wu, Y., Mason, K.P., and Zhang, C.: Simulation and analysis of hospital operations and resource utilization using rfid data. In: IEEE International Conference on RFID, 2007. pp. 199–204. IEEE, 2007

  15. Booth, P., Frisch, P.H., and Miodownik, S.: Application of rfid in an integrated healthcare environment. In: EMBS’06. 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006. pp. 117–119. IEEE, 2006

  16. Miller, M.J., Ferrin, D.M., Flynn, T., Ashby, M., Preston White, K Jr, and Mauer, M. G: Using rfid technologies to capture simulation data in a hospital emergency department. In: Proceedings of the 38th conference on Winter simulation. pp. 1365–1370. Winter Simulation Conference, 2006

  17. Wicks, A. M, Visich, J.K., and Li, S., Radio frequency identification applications in hospital environments. Hosp. Top. 84(3):3–9, 2006.

    Article  Google Scholar 

  18. Chen, C. -I, Liu, C. -Y., Li, Y.-C., Chao, C.-C., Liu, C.-T., Chen, C.-F., and Kuan, C.-F.: Pervasive observation medicine: The application of rfid to improve patient safety in observation unit of hospital emergency department, Vol. 116, 2005

  19. Froehle, C. M, and Magazine, M. J: Improving scheduling and flow in complex outpatient clinics. In: Handbook of healthcare operations management. pp. 229–250. Springer, 2013

  20. Gupta, D., and Denton, B., Appointment scheduling in health care: challenges and opportunities. IIE Trans. 40(9):800–819, 2008.

    Article  Google Scholar 

  21. Jones, T.L, Radiofrequency identification: exploiting an old technology for measuring nurse time and motion. Comput. Inf. Nurs.: CIN 30(9):463, 2012.

    Article  Google Scholar 

  22. Jones, T. L, and Schlegel, C., Can real time location system technology (rtls) provide useful estimates of time use by nursing personnel? Res. Nurs. Health 37(1):75–84, 2014.

    Article  Google Scholar 

  23. Stahl, J. E, Drew, M. A, Weilburg, J., Sistrom, C., and Kimball, A. B: Face time versus test ordering: is there a trade-off? The American Journal of Managed Care, 19 (10 Spec No): SP362–8, 2013

  24. Stahl, J. E, Drew, M. A, and Kimball, A. B, Real-time location systems, normative messaging and modifying clinician behavior: a pilot study. Health Syst. 3(3):165–172, 2014.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Minnesota Twin Cities, Minneapolis, MN, USA

    Bjorn Berg, Grant Longley & Jordan Dunitz

Authors
  1. Bjorn Berg
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Grant Longley
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jordan Dunitz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bjorn Berg.

Ethics declarations

Conflict of interests

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

Additional information

Publisher’s Note

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

This article is part of the Topical Collection on Systems-Level Quality Improvement

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Berg, B., Longley, G. & Dunitz, J. Improving Clinic Operational Efficiency and Utilization with RTLS. J Med Syst 43, 56 (2019). https://doi.org/10.1007/s10916-019-1174-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10916-019-1174-z

Keywords

Search

Navigation