IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0198522.html
   My bibliography  Save this article

The association between outcome-based quality indicators for intensive care units

Author

Listed:
  • Ilona W M Verburg
  • Evert de Jonge
  • Niels Peek
  • Nicolette F de Keizer

Abstract

Purpose: To assess and improve the effectiveness of ICU care, in-hospital mortality rates are often used as principal quality indicator for benchmarking purposes. Two other often used, easily quantifiable, quality indicators to assess the efficiency of ICU care are based on readmission to the ICU and ICU length of stay. Our aim was to examine whether there is an association between case-mix adjusted outcome-based quality indicators in the general ICU population as well as within specific subgroups. Materials and methods: We included patients admitted in 2015 of all Dutch ICUs. We derived the standardized in-hospital mortality ratio (SMR); the standardized readmission ratio (SRR); and the standardized length of stay ratio (SLOSR). We expressed association through Pearson’s correlation coefficients. Results: The SMR ranged from 0.6 to 1.5; the SRR ranged from 0.7 to 2.1; and the SLOSR ranged from 0.7 to 1.3. For the total ICU population we found no significant associations. We found a positive, non-significant, association between SMR and SLOSR for admissions with low-mortality risk, (r = 0.25; p = 0.024), and a negative association between these indicators for admissions with high-mortality risk (r = -0.49; p

Suggested Citation

  • Ilona W M Verburg & Evert de Jonge & Niels Peek & Nicolette F de Keizer, 2018. "The association between outcome-based quality indicators for intensive care units," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-14, June.
    • Handle: RePEc:plo:pone00:0198522
    DOI: 10.1371/journal.pone.0198522
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0198522
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0198522&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0198522?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. Harvey Goldstein & David J. Spiegelhalter, 1996. "League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(3), pages 385-409, May.
    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. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    2. Bornmann, Lutz & Leydesdorff, Loet & Wang, Jian, 2014. "How to improve the prediction based on citation impact percentiles for years shortly after the publication date?," Journal of Informetrics, Elsevier, vol. 8(1), pages 175-180.
    3. Arpino, Bruno & Varriale, Roberta, 2009. "Assessing the quality of institutions’ rankings obtained through multilevel linear regression models," MPRA Paper 19873, University Library of Munich, Germany.
    4. Mutz, Rüdiger & Daniel, Hans-Dieter, 2018. "The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model," Journal of Informetrics, Elsevier, vol. 12(4), pages 1282-1295.
    5. Magne Mogstad & Joseph P. Romano & Azeem Shaikh & Daniel Wilhelm, 2020. "Inference for Ranks with Applications to Mobility across Neighborhoods and Academic Achievement across Countries," NBER Working Papers 26883, National Bureau of Economic Research, Inc.
    6. Daraio, Cinzia & Bonaccorsi, Andrea & Simar, Léopold, 2015. "Rankings and university performance: A conditional multidimensional approach," European Journal of Operational Research, Elsevier, vol. 244(3), pages 918-930.
    7. repec:lan:wpaper:991 is not listed on IDEAS
    8. Nils Gutacker & Andrew Street, 2015. "Multidimensional performance assessment using dominance criteria," Working Papers 115cherp, Centre for Health Economics, University of York.
    9. Nils Gutacker & Andrew Street, 2018. "Multidimensional performance assessment of public sector organisations using dominance criteria," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 13-27, February.
    10. Sulis, Isabella & Giambona, Francesca & Porcu, Mariano, 2020. "Adjusted indicators of quality and equity for monitoring the education systems over time. Insights on EU15 countries from PISA surveys," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    11. Pia Kjær Kristensen & Raquel Perez-Vicente & George Leckie & Søren Paaske Johnsen & Juan Merlo, 2020. "Disentangling the contribution of hospitals and municipalities for understanding patient level differences in one-year mortality risk after hip-fracture: A cross-classified multilevel analysis in Swed," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-14, June.
    12. Paolo Berta & Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini, 2016. "Multilevel cluster-weighted models for the evaluation of hospitals," METRON, Springer;Sapienza Università di Roma, vol. 74(3), pages 275-292, December.
    13. Cristiano Varin & Manuela Cattelan & David Firth, 2016. "Statistical modelling of citation exchange between statistics journals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(1), pages 1-63, January.
    14. Frank Eijkenaar & René C. J. A. van Vliet, 2014. "Performance Profiling in Primary Care," Medical Decision Making, , vol. 34(2), pages 192-205, February.
    15. John Robinson & Scott Zeger & Christopher Forrest, 2004. "A Hierarchical Multivariate Two-Part Model for Profiling Providers' Effects on Healthcare Charges," Johns Hopkins University Dept. of Biostatistics Working Paper Series 1052, Berkeley Electronic Press.
    16. Martini, Gianmaria & Berta, Paolo & Mullahy, John & Vittadini, Giorgio, 2014. "The effectiveness–efficiency trade-off in health care: The case of hospitals in Lombardy, Italy," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 217-231.
    17. Anna Cuxart & Nicholas T. Longford, 1997. "Monitoring the university admissions process in Spain," Economics Working Papers 257, Department of Economics and Business, Universitat Pompeu Fabra, revised Dec 1997.
    18. Adnett, Nick & Bougheas, Spiros & Davies, Peter, 2002. "Market-based reforms of public schooling: some unpleasant dynamics," Economics of Education Review, Elsevier, vol. 21(4), pages 323-330, August.
    19. Francesca Giambona & Mariano Porcu & Isabella Sulis, 2017. "Students Mobility: Assessing the Determinants of Attractiveness Across Competing Territorial Areas," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(3), pages 1105-1132, September.
    20. Li Mingliang & Tobias Justin, 2005. "Bayesian Modeling of School Effects Using Hierarchical Models with Smoothing Priors," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(3), pages 1-33, September.
    21. Pier Ferrari & Laura Pagani & Carlo Fiorio, 2011. "A Two-Step Approach to Analyze Satisfaction Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 104(3), pages 545-554, December.

    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:pone00:0198522. 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.