Volume-outcome relationship on survival and cost benefits in severe burn injury: a retrospective analysis of a Japanese nationwide administrative database View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Akira Endo, Atsushi Shiraishi, Yasuhiro Otomo, Kiyohide Fushimi, Kiyoshi Murata

ABSTRACT

Background: Although it has been reported that high hospital patient volume results in survival and cost benefits for several diseases, it is uncertain whether this association is applicable in burn care. Methods: We conducted a retrospective observational study on severe burn patients, defined by a burn index ≥ 10, using 2010-2015 data from a Japanese national administrative claim database. A generalized additive mixed-effect model (GAMM) was used to evaluate the nonlinear associations between patient volume and the outcomes (in-hospital mortality, healthcare costs per admission, and hospital-free days at 90 days). Generalized linear mixed-effect regression models (GLMMs) in which patient volume was incorporated as a continuous or categorical variable (≤ 5 or > 5) were also performed. Patient severity was adjusted using the prognostic burn index (PBI) or the risk adjustment model developed in this study, simultaneously controlling for hospital-level clustering. Sensitivity analyses evaluating patients who were directly transported, those with PBI ≤ 120 and those excluding patients who died within 2 days of admission, were also performed. Results: We analyzed 5250 eligible severe burn patients from 737 hospitals. The PBI and the developed risk adjustment model had good discriminative ability with areas under the receiver operating characteristic curves of 0.86 and 0.89, respectively. The GAMM plots showed that in-hospital mortality and healthcare costs increased according to the increase in patient volumes; then, they reached a plateau. Fewer hospital-free days were observed in the higher volume hospitals. The GLMM model showed that patient volume (incorporated as a continuous variable) was significantly associated with increased in-hospital mortality (adjusted odds ratio [95% confidence interval (CI)] = 1.14 [1.09-1.19]), high healthcare costs (adjusted difference [95% CI] = $4876 [4436-5316]), and few hospital-free days (adjusted difference [95% CI] = - 3.1 days [- 3.4 to - 2.8]). Similar trends were observed in the analyses in which patient volume was incorporated as a categorical variable. The results of sensitivity analyses showed comparable results. Conclusions: Analysis of Japanese nationwide administrative database demonstrated that high burn patient volume was significantly associated with increased in-hospital mortality, high healthcare costs, and few hospital-free days. Further studies are needed to validate our results. More... »

PAGES

7

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s40560-019-0363-7

DOI

http://dx.doi.org/10.1186/s40560-019-0363-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111777705

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30733868


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    "description": "Background: Although it has been reported that high hospital patient volume results in survival and cost benefits for several diseases, it is uncertain whether this association is applicable in burn care.\nMethods: We conducted a retrospective observational study on severe burn patients, defined by a burn index \u2265\u200910, using 2010-2015 data from a Japanese national administrative claim database. A generalized additive mixed-effect model (GAMM) was used to evaluate the nonlinear associations between patient volume and the outcomes (in-hospital mortality, healthcare costs per admission, and hospital-free days at 90\u2009days). Generalized linear mixed-effect regression models (GLMMs) in which patient volume was incorporated as a continuous or categorical variable (\u2264\u20095 or >\u20095) were also performed. Patient severity was adjusted using the prognostic burn index (PBI) or the risk adjustment model developed in this study, simultaneously controlling for hospital-level clustering. Sensitivity analyses evaluating patients who were directly transported, those with PBI \u2264\u2009120 and those excluding patients who died within 2\u2009days of admission, were also performed.\nResults: We analyzed 5250 eligible severe burn patients from 737 hospitals. The PBI and the developed risk adjustment model had good discriminative ability with areas under the receiver operating characteristic curves of 0.86 and 0.89, respectively. The GAMM plots showed that in-hospital mortality and healthcare costs increased according to the increase in patient volumes; then, they reached a plateau. Fewer hospital-free days were observed in the higher volume hospitals. The GLMM model showed that patient volume (incorporated as a continuous variable) was significantly associated with increased in-hospital mortality (adjusted odds ratio [95% confidence interval (CI)]\u2009=\u20091.14 [1.09-1.19]), high healthcare costs (adjusted difference [95% CI]\u2009=\u2009$4876 [4436-5316]), and few hospital-free days (adjusted difference [95% CI]\u2009=\u2009-\u20093.1\u2009days [-\u20093.4 to -\u20092.8]). Similar trends were observed in the analyses in which patient volume was incorporated as a categorical variable. The results of sensitivity analyses showed comparable results.\nConclusions: Analysis of Japanese nationwide administrative database demonstrated that high burn patient volume was significantly associated with increased in-hospital mortality, high healthcare costs, and few hospital-free days. Further studies are needed to validate our results.", 
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