Hongpeng Liu
1 
, Baoyun Song
2, Jingfen Jin
3, Yilan Liu
4, Xianxiu Wen
5, Shouzhen Cheng
6, Stephen Nicholas
7,8,9,10 , Elizabeth Maitland
11, Xinjuan Wu
1* , Dawei Zhu
12* 1 Department of Nursing, Chinese Academy of Medical Sciences - Peking Union Medical College, Peking Union Medical College Hospital, Beijing, China.
2 Department of Nursing, Henan Provincial People’s Hospital, Zhengzhou, China.
3 Department of Nursing, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, China.
4 Department of Nursing, Wuhan Union Hospital, Wuhan, China.
5 Department of Nursing, Sichuan Provincial People’s Hospital, Chengdu, China.
6 Department of Nursing, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
7 Australian National Institute of Management and Commerce, Sydney, NSW, Australia.
8 School of Economics and School of Management, Tianjin Normal University, Tianjin, China.
9 Guangdong Institute for International Strategies, Guangdong University of Foreign Studies, Guangzhou, China.
10 Newcastle Business School, University of Newcastle, Newcastle, NSW, Australia.
11 School of Management, University of Liverpool, Liverpool, UK.
12 China Center for Health Development Studies, Peking University, Beijing, China.
Abstract
Background: In this study, we examined the length of stay (LoS)-predictive comorbidities, hospital costs-predictive comorbidities, and mortality‐predictive comorbidities in immobile ischemic stroke (IS) patients; second, we used the Charlson Comorbidity Index (CCI) to assess the association between comorbidity and the LoS and hospitalization costs of stroke; third, we assessed the magnitude of excess IS mortality related to comorbidities.
Methods: Between November 2015 and July 2017, 5114 patients hospitalized for IS in 25 general hospitals from six provinces in eastern, western, and central China were evaluated. LoS was the period from the date of admission to the date of discharge or date of death. Costs were collected from the hospital information system (HIS) after the enrolled patients were discharged or died in hospital. The HIS belongs to the hospital’s financial system, which records all the expenses of the patient during the hospital stay. Cause of death was recorded in the HIS for 90 days after admission regardless of whether death occurred before or after discharge. Using the CCI, a comorbidity index was categorized as zero, one, two, and three or more CCI diseases. A generalized linear model with a gamma distribution and a log link was used to assess the association of LoS and hospital costs with the comorbidity index. Kaplan–Meier survival curves was used to examine overall survival rates.
Results: We found that 55.2% of IS patients had a comorbidity. Prevalence of peripheral vascular disease (21.7%) and diabetes without end-organ damage (18.8%) were the major comorbidities. A high CCI=3+ score was an effective predictor of a high risk of longer LoS and death compared with a low CCI score; and CCI=2 score and CCI=3+ score were efficient predictors of a high risk of elevated hospital costs. Specifically, the most notable LoS-specific comorbidities, and cost-specific comorbidities was dementia, while the most notable mortality-specific comorbidities was moderate or severe renal disease.
Conclusion: CCI has significant predictive value for clinical outcomes in IS. Due to population aging, the CCI should be used to identify, monitor and manage chronic comorbidities among immobile IS populations.