2017
DOI: 10.1007/s00264-017-3425-2
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Predicting the post-operative length of stay for the orthopaedic trauma patient

Abstract: Utilizing a large prospective cohort of orthopaedic trauma patients, we created the first personalized LOS calculator based on pre-operative comorbidities, post-operative complications and location of surgery. Future work may assess the use of this calculator and attempt to validate its utility as an accurate model. To improve the quality measures of hospitals, orthopaedists must employ such predictive tools to optimize care and better manage resources.

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Cited by 28 publications
(11 citation statements)
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“…Age as a risk factor for increased hospital length of stay and complications in geriatric trauma patients has been demonstrated in several studies. 19 This correlation even remains after controlling for patient comorbidities and ISS score. However, the mean/expected length of stay, complications, cost of care for different age groups are not cited in these studies.…”
Section: Discussionmentioning
confidence: 92%
See 1 more Smart Citation
“…Age as a risk factor for increased hospital length of stay and complications in geriatric trauma patients has been demonstrated in several studies. 19 This correlation even remains after controlling for patient comorbidities and ISS score. However, the mean/expected length of stay, complications, cost of care for different age groups are not cited in these studies.…”
Section: Discussionmentioning
confidence: 92%
“…However, the mean/expected length of stay, complications, cost of care for different age groups are not cited in these studies. 19 , 20 Furthermore, previous analyses including those from our institution have demonstrated that several injury severity scores including TRISS, ISS, and STTGMA, can predict mortality and length of stay. Of these scores, only STTGMA includes age as a continuous variable.…”
Section: Discussionmentioning
confidence: 93%
“…2, hinted that some patients had a negative length of stay (meaning the registered discharge date was before the admission date), and some patients apparently had been in treatment for up to 370 days, which seemed implausible. The average length of stay of trauma patients analysed in a publication by Chona et al was 3.8 ± 5.4 days [20]. Since the university hospital in Lübeck treated severely injured and complicated cases, the maximum plausible length of stay was extended to the first visibly aberrant value at 130 days.…”
Section: Resultsmentioning
confidence: 99%
“…This approach is suitable for large data sets, yet somehow questionable due to selection bias from the primary to the secondary database. Partly, a similar approach was used when scoring the data quality of the BFCC registry, when the length of stay was oriented on 49.778 orthopaedic and trauma patients analysed by Chona et al 4 .…”
Section: Discussionmentioning
confidence: 99%