The direct and indirect effects of length of hospital stay on the costs of inpatients with stroke in Ningxia, China, between 2015 and 2020

A retrospective study using quantile regression and structural equation models

Bibliographic Data

ID22067017
AuthorsMing Su (0000-0002-0252-7936, Ningxia Medical University), Dongfeng Pan (0000-0003-4224-1606, The Fourth People's Hospital of Ningxia Hui Autonomous Region), Yuan Zhao (0000-0003-3523-9751, The Fourth People's Hospital of Ningxia Hui Autonomous Region), Chen Chen (0000-0002-9786-8003, The Fourth People's Hospital of Ningxia Hui Autonomous Region), Xingtian Wang (0000-0002-8957-9826, Ningxia Medical University), Wenwen Lu (0000-0002-7656-2312, Ningxia Medical University), Hua Meng (0000-0003-3286-9424, Ningxia Medical University), Xinya Su (0009-0007-7047-7313, Ningxia Medical University), Peifeng Liang (0000-0002-8473-9843, The Fourth People's Hospital of Ningxia Hui Autonomous Region, corresponding author)
Year2022
Volume10
Pages881273-881273
Publication date2022-08-12
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2022.881273
PMID36033765
OpenAlexW4290840326
LanguageEN
Citations received3
References cited28

Importance: Length of hospital stay (LOHS) is the main cost-determining factor of hospitalization for stroke patients. However, previous analyses involving LOHS did not consider confounding or indirect factors, or the effects of other factors on LOHS and inpatient costs. Objective: To investigate the direct and indirect effects of LOHS on the hospitalization costs of inpatients with ischemic and hemorrhagic stroke. Design setting and participants: This was a population-based, retrospective, and observational study that analyzed data acquired from the Nationwide Inpatient Sample between 2015 and 2020 relating to ischemic and hemorrhagic stroke in Ningxia, China. Main outcomes and measures: Hospitalizations were identified by the International Classification of Diseases 10th Revision (ICD-10). Inpatient costs were described by the median M (P25, P75). We used a quantile regression model to estimate the linear relationships between a group of independent variables X and the quantile of the explained variable hospitalization cost (Y). A structural equation model (SEM) was then used to investigate the direct and indirect effects of LOHS on inpatient costs. Results: ) of inpatient costs was $1020 (742-1545) for ischemic stroke and 2813 (1576-6191) for hemorrhagic stroke. The total effect of LOHS on inpatient costs was 0.795 in patients with ischemic stroke. The effect of yearof discharge (X4) and CCI (X8) on inpatient costs was dominated by an indirect effect through the LOHS. The indirect effect was -0.071 (84.52% of the total effect value) and 0.034 (69.39% of the total effect value), respectively. The total effect of LOHS on inpatient costs in patients with hemorrhagic stroke was 0.754. The influence of CCI on inpatient costs was dominated by an indirect effect through LOHS; the indirect effect value was -0.028 (77.78% of the total effect value). The payment type, surgery, method of discharge, and hospital level also exerted an impact on inpatient costs by direct and indirect effects through the LOHS. Conclusions and relevance: Length of hospital stay (LOHS) was identified as the main factor influencing hospitalization costs. However, other social factors were shown to indirectly influence hospitalization costs through the LOHS. Taking effective measures to further reduce hospitalization costs remains an effective way to control hospitalization costs for stroke patients

Confounding · Indirect costs · Ischemic stroke · Observational study · Quantile regression · Retrospective cohort study · Statistics · Acute Ischemic Stroke Management · Intracerebral and Subarachnoid Hemorrhage Research · Medicine · Stroke Rehabilitation and Recovery · Emergency Medicine · Internal Medicine

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