IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0287234.html
   My bibliography  Save this article

Interaction of mental comorbidity and physical multimorbidity predicts length-of-stay in medical inpatients

Author

Listed:
  • Sophia Stahl-Toyota
  • Christoph Nikendei
  • Ede Nagy
  • Stefan Bönsel
  • Ivo Rollmann
  • Inga Unger
  • Julia Szendrödi
  • Norbert Frey
  • Patrick Michl
  • Carsten Müller-Tidow
  • Dirk Jäger
  • Hans-Christoph Friederich
  • Achim Hochlehnert

Abstract

Background: Mental comorbidities of physically ill patients lead to higher morbidity, mortality, health-care utilization and costs. Objective: The aim of the study was to investigate the impact of mental comorbidity and physical multimorbidity on the length-of-stay in medical inpatients at a maximum-care university hospital. Design: The study follows a retrospective, quantitative cross-sectional analysis approach to investigate mental comorbidity and physical multimorbidity in internal medicine patients. Patients: The study comprised a total of n = 28.553 inpatients treated in 2017, 2018 and 2019 at a German Medical University Hospital. Main measures: Inpatients with a mental comorbidity showed a median length-of-stay of eight days that was two days longer compared to inpatients without a mental comorbidity. Neurotic and somatoform disorders (ICD-10 F4), behavioral syndromes (F5) and organic disorders (F0) were leading with respect to length-of-stay, followed by affective disorders (F3), schizophrenia and delusional disorders (F2), and substance use (F1), all above the sample mean length-of-stay. The impact of mental comorbidity on length-of-stay was greatest for middle-aged patients. Mental comorbidity and Elixhauser score as a measure for physical multimorbidity showed a significant interaction effect indicating that the impact of mental comorbidity on length-of-stay was greater in patients with higher Elixhauser scores. Conclusions: The findings provide new insights in medical inpatients how mental comorbidity and physical multimorbidity interact with respect to length-of-stay. Mental comorbidity had a large effect on length-of-stay, especially in patients with high levels of physical multimorbidity. Thus, there is an urgent need for new service models to especially care for multimorbid inpatients with mental comorbidity.

Suggested Citation

  • Sophia Stahl-Toyota & Christoph Nikendei & Ede Nagy & Stefan Bönsel & Ivo Rollmann & Inga Unger & Julia Szendrödi & Norbert Frey & Patrick Michl & Carsten Müller-Tidow & Dirk Jäger & Hans-Christoph Fr, 2023. "Interaction of mental comorbidity and physical multimorbidity predicts length-of-stay in medical inpatients," PLOS ONE, Public Library of Science, vol. 18(6), pages 1-16, June.
    • Handle: RePEc:plo:pone00:0287234
    DOI: 10.1371/journal.pone.0287234
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0287234
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0287234&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0287234?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Rand Wilcox, 1994. "The percentage bend correlation coefficient," Psychometrika, Springer;The Psychometric Society, vol. 59(4), pages 601-616, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jinse Jacob & R Varadharajan, 2024. "Robust Variance Inflation Factor: A Promising Approach for Collinearity Diagnostics in the Presence of Outliers," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 86(2), pages 845-871, November.
    2. W. Holmes Finch, 2024. "Comparison of Methods for Addressing Outliers in Exploratory Factor Analysis and Impact on Accuracy of Determining the Number of Factors," Stats, MDPI, vol. 7(3), pages 1-21, August.
    3. Alhamzawi, Rahim & Yu, Keming, 2013. "Conjugate priors and variable selection for Bayesian quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 209-219.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0287234. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may 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.