Can differences in length of stay between Dutch university hospitals and other hospitals be explained by patient characteristics? A cross-sectional study
Objectives The indicator unexpectedly long length of stay (UL-LOS) is used to gain insight into quality and safety of care in hospitals. The calculation of UL-LOS takes patients’ age, main diagnosis and main procedure into account. University hospitals have relatively more patients with a UL-LOS than other hospitals. Our main research question is whether the high number of patients with a UL-LOS in university hospitals is caused by differences in additional patient characteristics between university hospitals and other hospitals. Design We performed a cross-sectional study and used administrat... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2019 |
Reihe/Periodikum: | BMJ Open ; volume 9, issue 2, page e021851 ; ISSN 2044-6055 2044-6055 |
Verlag/Hrsg.: |
BMJ
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Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-29009820 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://dx.doi.org/10.1136/bmjopen-2018-021851 |
Objectives The indicator unexpectedly long length of stay (UL-LOS) is used to gain insight into quality and safety of care in hospitals. The calculation of UL-LOS takes patients’ age, main diagnosis and main procedure into account. University hospitals have relatively more patients with a UL-LOS than other hospitals. Our main research question is whether the high number of patients with a UL-LOS in university hospitals is caused by differences in additional patient characteristics between university hospitals and other hospitals. Design We performed a cross-sectional study and used administrative data from 1 510 627 clinical admissions in 87 Dutch hospitals. Patients who died in hospital, stayed in hospital for 100 days or longer or whose country of residence was not the Netherlands were excluded from the UL-LOS indicator. We identified which patient groups were treated only in university hospitals or only in other hospitals and which were treated in both hospital types. For these last patient groups, we added supplementary patient characteristics to the current model to determine the effect on the UL-LOS model. Results Patient groups treated in both hospital types differed in terms of detailed primary diagnosis, socioeconomic status, source of admission, type of admission and amount of Charlson comorbidities. Nevertheless, when adding these characteristics to the current model, university hospitals still have a significantly higher mean UL-LOS score compared with other hospitals (p<0.001). Conclusions The difference in UL-LOS scores between both hospital types remains after adding patient characteristics in which both hospital types differ. We conclude that the high UL-LOS scores in university hospitals are not caused by the investigated additional patient characteristics that differ between university and other hospitals. Patients might stay relatively longer in university hospitals due to differences in work processes because of their education and research tasks or financing differences of both hospital ...