Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 1 de 1
Filter
Add filters

Database
Language
Document Type
Year range
1.
Int J Qual Health Care ; 33(2)2021 May 07.
Article in English | MEDLINE | ID: covidwho-1205645

ABSTRACT

OBJECTIVE: Unprecedented rigorous public health measures were implemented during the coronavirus disease 2019 (COVID-19) epidemic, but it is still unclear how the intervention influenced hospital visits for different types of diseases. We aimed to evaluate the impact of the intervention on hospital visits in Yinzhou District, Ningbo, Zhejiang province, China. METHODS: We conducted an interrupted time-series analysis from 1 January 2017 to 6 September 2020 based on the Yinzhou Health Information System in Ningbo, Zhejiang province. The beginning of the intervention was on 23 January 2020, and thus, there were 160 weeks before the intervention and 32 weeks after the implementation of the intervention. Level changes between expected and observed hospital visits in the post-intervention period were estimated using quasi-Poisson regression models. RESULTS: Compared with the expected level, there was an estimated decrease of -22.60% (95% confidence interval (CI): -27.53%, -17.36%) in the observed total hospital visits following the intervention. Observed hospital visits for diseases of the respiratory system were found to be decreased dramatically (-62.25%; 95% CI: -65.62%, -58.60%). However, observed hospital visits for certain diseases were estimated to be increased, including diseases of the nervous system (+11.17%; 95% CI: +3.21%, +19.74%); diseases of pregnancy, childbirth and the puerperium (+27.01%; 95% CI: +17.89%, +36.85%); certain conditions originating in the perinatal period (+45.05%; 95% CI: +30.24%, +61.56%); and congenital malformation deformations and chromosomal abnormalities (+35.50%; 95% CI: +21.24%, +51.45%). CONCLUSIONS: Our findings provided scientific evidence that cause-specific hospital visits evolve differently following the intervention during the COVID-19 epidemic.


Subject(s)
COVID-19 , Hospitals/statistics & numerical data , COVID-19/epidemiology , China/epidemiology , Female , Humans , Interrupted Time Series Analysis , Pandemics , Pregnancy , SARS-CoV-2
SELECTION OF CITATIONS
SEARCH DETAIL