Introduction: The purpose of this study was to introduce a measure of patient's burden based on Elixhauser's comorbidity index. The mentioned measure needed to be based solely on administrative data and be applicable to all specialisations of hospital treatment. Moreover, the intention was to validate the estimation power of the models based on the groups of hospitalisations which were similar with respect to the primary diagnosis.
Material and methods: In the study, we considered all hospitalisations in Poland from 2014 and 2015. Overall, 22 045 267 hospitalisation records of 11 566 525 patients were retrieved. An important element of this research was to validate the estimation power of the models based on the groups of patients who were similar with respect to the main reason for hospitalisation. Therefore, the population was split into 21 Homogeneous Groups based on the changed primary diagnosis. As explanatory variables we used demographic variables and 31 comorbidities defined by Elixhauser. The outcome variable was patient's mortality - in-hospital or up to 365 days after discharge.
Results: Out of the 21 created models, 9 had a very good estimation power (C-statistic over 0.85), the other 9 had satysfying results (C-statistic between 0.75 and 0.85) and only 3 performed poorly (C-statistic below 0.75). The odds ratio of variables varied widely between the groups.
Conclusions: Our results support the hypothesis that comorbidity properly describes mortality in homogeneous groups of patients. Our models could be condensed into one, uniform, single-number comorbidity scale that summarizes all of the patient's burden. It was found that the odds ratio of some variables differed between homogeneous groups.
Keywords: Elixhauser comorbidity index; administrative data; mortality; quality of healthcare; risk adjustment.
Copyright: © 2019 Termedia & Banach.