IDEAS home Printed from https://ideas.repec.org/e/pad106.html
   My authors  Follow this author

Shola Adeyemi

Personal Details

First Name:Shola
Middle Name:
Last Name:Adeyemi
Suffix:
RePEc Short-ID:pad106
http://www.statsxperts.co.uk/

Research output

as
Jump to: Articles

Articles

  1. Eren Demir & Reda Lebcir & Shola Adeyemi, 2014. "Modelling length of stay and patient flows: methodological case studies from the UK neonatal care services," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(4), pages 532-545, April.
  2. Shola Adeyemi & Thierry Chaussalet & Eren Demir, 2011. "Nonproportional random effects modelling of a neonatal unit operational patient pathways," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 507-518, November.
  3. Shola Adeyemi & Thierry Chaussalet & Haifeng Xie & Md Asaduzaman, 2010. "Random effects models for operational patient pathways," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(4), pages 691-701.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Eren Demir & Reda Lebcir & Shola Adeyemi, 2014. "Modelling length of stay and patient flows: methodological case studies from the UK neonatal care services," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(4), pages 532-545, April.

    Cited by:

    1. Azcarate, Cristina & Esparza, Laida & Mallor, Fermin, 2020. "The problem of the last bed: Contextualization and a new simulation framework for analyzing physician decisions," Omega, Elsevier, vol. 96(C).
    2. Shola Adeyemi & Eren Demir, 2020. "Modelling the neonatal system: A joint analysis of length of stay and patient pathways," International Journal of Health Planning and Management, Wiley Blackwell, vol. 35(3), pages 704-717, May.
    3. Josephine Varney & Nigel Bean & Mark Mackay, 2019. "The self-regulating nature of occupancy in ICUs: stochastic homoeostasis," Health Care Management Science, Springer, vol. 22(4), pages 615-634, December.
    4. Chih‐Tung Hsiao & Chun‐Cheng Chen & Lee‐Kai Lin & Chung‐Shu Liu, 2023. "A systems view of responding to the COVID‐19 pandemic: A causal loop model for Taiwan's approach," Systems Research and Behavioral Science, Wiley Blackwell, vol. 40(1), pages 194-206, January.
    5. Jie Bai & Andreas Fügener & Jan Schoenfelder & Jens O. Brunner, 2018. "Operations research in intensive care unit management: a literature review," Health Care Management Science, Springer, vol. 21(1), pages 1-24, March.
    6. Reda Lebcir & Rifat Atun, 2021. "Resources management impact on neonatal services performance in the United Kingdom: A system dynamics modelling approach," International Journal of Health Planning and Management, Wiley Blackwell, vol. 36(3), pages 793-812, May.
    7. Yuta Kanai & Hideaki Takagi, 2021. "Markov chain analysis for the neonatal inpatient flow in a hospital," Health Care Management Science, Springer, vol. 24(1), pages 92-116, March.

  2. Shola Adeyemi & Thierry Chaussalet & Eren Demir, 2011. "Nonproportional random effects modelling of a neonatal unit operational patient pathways," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 507-518, November.

    Cited by:

    1. Shola Adeyemi & Eren Demir, 2020. "Modelling the neonatal system: A joint analysis of length of stay and patient pathways," International Journal of Health Planning and Management, Wiley Blackwell, vol. 35(3), pages 704-717, May.
    2. Yuta Kanai & Hideaki Takagi, 2021. "Markov chain analysis for the neonatal inpatient flow in a hospital," Health Care Management Science, Springer, vol. 24(1), pages 92-116, March.

  3. Shola Adeyemi & Thierry Chaussalet & Haifeng Xie & Md Asaduzaman, 2010. "Random effects models for operational patient pathways," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(4), pages 691-701.

    Cited by:

    1. Shola Adeyemi & Eren Demir, 2020. "Modelling the neonatal system: A joint analysis of length of stay and patient pathways," International Journal of Health Planning and Management, Wiley Blackwell, vol. 35(3), pages 704-717, May.
    2. Debora Sarno & Maria Elena Nenni, 2016. "Daily nurse requirements planning based on simulation of patient flows," Flexible Services and Manufacturing Journal, Springer, vol. 28(3), pages 526-549, September.
    3. Shola Adeyemi & Thierry Chaussalet & Eren Demir, 2011. "Nonproportional random effects modelling of a neonatal unit operational patient pathways," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 507-518, November.
    4. Yuta Kanai & Hideaki Takagi, 2021. "Markov chain analysis for the neonatal inpatient flow in a hospital," Health Care Management Science, Springer, vol. 24(1), pages 92-116, March.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Shola Adeyemi should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.