Factors affecting in‐hospital cost and mortality of patients with stroke: Evidence from a case study in a tertiary hospital in China

Abstract

Objective: The study aims to investigate the factors causing the difference of stroke patients' in-hospital cost and study these factors on health outcome in terms of mortality. Methods: Eight hundred and sixty-two in-patients with stroke in a tertiary hospital in China from 2017 to 2019 were included in the database. Descriptive statistics indexes were used to describe patients' in-hospital cost and mortality. Based on Elixhauser coding algorithms, multiple linear regression and logistic regressions (LRs) were used to evaluate the impact of factors identified from univariate analysis on in-hospital cost and mortality, respectively. In addition to LRs, a comparison study was then carried out with random forest, gradient boosting decision tree and artificial neural network. Results: Factors affecting both cost and mortality are age, discharged day-of-week, length of stay, stroke subtype, other neurological disorders, renal failure, fluid and electrolyte disorders and total number of comorbidities. Conclusion: With the increase of age, the mortality rate of in-patients (except for the juvenile) with stroke increases and the cost of hospitalization decreases. Intracerebral haemorrhage is the most devastating stroke for its highest mortality in short length of stay. Medical services should focus on these specific comorbidities.

Estimation and predictors of direct hospitalisation expenses and in-hospital mortality for patients who had a stroke in a low-middle income country: evidence from a nationwide cross-sectional study in Iranian hospitals

“…Liu C et al showed that with increasing LoS, the mortality rate among patients decreases. 20 Because LoS is adjustable, it can be used as a target to control hospitalisation expenses and improve hospitalisation care.…”

“…This is in contrast to the findings of Liu et al in China, who found that hospitalisation costs for surviving patients were approximately five times higher than for patients who died. 20 The discrepancy could stem from more complex procedures and specialised therapies because of the acute condition of dying patients or their stay in the ICU and the difference in hospital Accommodation and nursing tariffs for ICU beds.…”

“…Hospitalisation expenses are the sum of all medical and non-medical expenses incurred by patients who had a stroke during hospitalisation. 20 GLM with gamma distribution has been shown to predict mean costs as well as total hospitalisation costs closely. In addition, the log link function has the advantage of ensuring non-negative results by preserving the original scale of the data, as opposed to log transformation.…”

“…The second outcome variable, in-hospital mortality, is an important index in measuring clinical quality. 20 It is used in this study to evaluate the health outcome of patients.…”

“…Hospitalisation expenses are the sum of all medical and non-medical expenses incurred by patients who had a stroke during hospitalisation. 20 …”