INTRODUCTION

Stroke mortality is a crucial indicator of the quality of acute care within a country [1–5]. Due to the need for swift intervention after a stroke occurs, it also reflects the efficiency of emergency care services. The Organization for Economic Cooperation and Development (OECD) health data use in-hospital stroke and myocardial infarction mortality rates as benchmarks to evaluate the quality of acute care [6].

Several studies have demonstrated the effects of coronavirus disease 2019 (COVID-19) on stroke treatment and mortality. Research indicates that delays in treatment following COVID-19 infection influence both admission and mortality rates [7–11]. The COVID-19 pandemic has significantly impacted public health, and hospitals, especially those with fewer beds [12], may have seen a decline in the quality of care. Due to the overwhelming number of patients and restricted access to healthcare services resulting from social distancing measures, individuals with emergency conditions [13], such as ischemic and hemorrhagic strokes, may not have received timely and appropriate treatment.

Prior investigations into the effects of COVID-19 on hospitalization and mortality rates among stroke patients have encountered several methodological challenges. Previous studies that examined the impact of COVID-19 on stroke were confined to specific geographic areas, subregions, or individual healthcare facilities. Therefore, it is imperative to assess the effects of the COVID-19 pandemic on stroke incidence on a national level. Earlier research primarily focused on comparing hospitalization and mortality rates before and after the onset of COVID-19. However, there is an urgent need for more comprehensive approaches that utilize time-series analysis over extended periods, rather than relying solely on simple before-and-after comparisons of the pandemic. This need is underscored by changing population demographics and aging trends across various countries, which must be incorporated into the analytical framework. Consequently, the main objective of this study was to explore the impact of COVID-19 on the hospitalization and mortality of patients with ischemic and hemorrhagic stroke and to identify the socioeconomic indicators that significantly influence these outcomes.

METHODS

Data Source

The data utilized in this study were obtained from the National Health Insurance Service (NHIS) database, which encompasses nearly the entire population of Korea, including beneficiaries of both the National Health Insurance (NHI) and Medical Aid (MA). This dataset comprises demographic details such as sex, age, and location, as well as diagnostic information coded according to the International Classification of Diseases-10 (ICD-10). It also includes data on treatments, prescriptions, and healthcare providers [14,15].

Study Population and Design

Using the OECD’s indicator definitions for 30-day stroke mortality, we identified patients aged 20 years and older who were admitted to hospitals with a primary diagnosis of stroke (ICD-10: I60–I64) between January 1, 2017 and December 31, 2021. Stroke patients were defined as individuals without a previous stroke diagnosis and whose primary diagnosis upon admission was stroke. Additionally, inpatients were categorized as those admitted for acute, non-elective stroke conditions, rather than for scheduled treatments. Death was operationally defined in this study as the cessation of eligibility for health insurance, due to the lack of direct linkage between health insurance claims and mortality data. This served as an indirect method of quantifying mortality, as deceased individuals are ineligible for health insurance coverage. Day-care cases and cases resulting from transfers in and out should also be considered as study subjects. Except for age, we applied the same criteria as in the OECD indicator definitions [16].

To assess the impact of the COVID-19 outbreak on monthly stroke healthcare utilization and outcomes, including hospitalization rates and 30-day mortality, an interrupted time series (ITS) analysis was conducted using segmented regression with a single interruption. The ITS design is widely utilized to evaluate the effects of interventions or exposures that occur at a specific point in time, particularly in real-world scenarios such as natural disasters or pandemics [17,18]. The analysis compared the pre-COVID-19 period, from January 2017 to January 2020, with the COVID-19 period, from February 2020 to December 2021. This comparison was based on a single-point intervention set in February 2020. The first confirmed case in Korea was reported on January 20, 2020 and the Korean government escalated the COVID-19 alert to the highest level (level 4) on February 23, 2020 [19].

Statistical Analysis

This study analyzed both raw and adjusted monthly acute admission rates for stroke per 100 000 individuals and 30-day in-hospital stroke mortality rates, segmented by age group, sex, type of insurance, and Charlson comorbidity index score to assess the impact of the pandemic. Additionally, stroke hospitalization and mortality rates were calculated for demographic groups categorized by age (20–44, 45–54, 55–64, 65–74, or ≥75 years), sex, and type of insurance (NHI or MA) program.

The analysis utilized the ITS method to evaluate the significance of changes in the indicators of the overall trend (time), the onset of the pandemic in February 2020 (intervention), and trends following the outbreak (time after intervention). A segmented regression model was employed to interpret the results, presenting both absolute and relative changes using predicted and observed values. The model is represented as Yt=β0+β1×Time+β2×Intervention+β3×Time after intervention t+ɛt, where β0 indicates the baseline level of the outcome variable, β1 represents the pre-existing trend, β2 denotes the immediate change in the outcome variable following the outbreak, and β3 illustrates the post-intervention trend, which is used to estimate the immediate and long-term impacts of the pandemic. The study also conducted a test for first-order autocorrelation using the Durbin-Watson test. All statistical analyses were carried out using SAS Enterprise Guide 7.4 (SAS Institute Inc., Cary, NC, USA), with a 2-sided significance level set at 0.05.

Ethics Statement

This study was reviewed and approved by the Institutional Review Board of Seoul National University Bundang Hospital (IRB No. X-2304-820-902). The requirement for informed consent was waived due to the use of anonymized data.

RESULTS

Characteristics of the Study Population by Types of Stroke

From 2017 to 2021, the number of ischemic stroke cases in Korea ranged from 48 715 to 63 331, marking a 30% increase, while hemorrhagic stroke cases ranged from 19 585 to 21 730, with an annual increase of 11%. The number of cases for both types of stroke varied each year. The average age of patients with ischemic stroke was 69.5±12.9 years in 2017 and increased to 70.7±13.0 years by 2021. For hemorrhagic stroke, the average age was 62.7±14.7 years in 2017 and rose to 64.5±14.8 years in 2021. Notably, over 40% of ischemic stroke cases occurred in individuals aged over 75, compared to approximately 30% for hemorrhagic stroke cases in the same age group. Additionally, 58.3% of ischemic stroke patients were male, 91.2% were covered by the NHI, and 8.8% were MA beneficiaries. The general characteristics of patients with ischemic and hemorrhagic strokes are presented in Table 1.

Changes in the Admission Rate and 30-Day In-hospital Mortality for Patients With Ischemic Stroke and the Impact of Coronavirus Disease 2019

Figure 1 shows the numbers of admitted and deceased patients with stroke from January 2017 to December 2021 by types of stroke and months.

As shown in Table 2, in January 2020, 1 month before the pandemic, hospitals admitted 5335 patients. However, by February 2020, the number of inpatients had decreased by 987 (18.5%), resulting in a total of 4348. Over time, the number of hospitalizations gradually increased. The in-hospital mortality rate rose slightly from 3.3% in January 2020 to 3.4% in February 2020. Following the pandemic, in-hospital mortality rates have shown significant fluctuations but have generally trended downward. This suggests that COVID-19 significantly impacted the number of inpatients with ischemic stroke. Figure 2 presents an ITS analysis of the monthly admission rate and 30-day in-hospital fatality by stroke type before and after the COVID-19 outbreak in February 2020. According to the results of ITS analysis in Table 3, the intervention estimate of ischemic stroke was statistically significant.

Supplemental Materials 1–5 illustrate the distribution of data by sex, age, and insurance type. Following the pandemic, the hospitalization rate decreased by approximately 2 per 100 000 individuals for both male and female, before subsequently increasing. In-hospital mortality rates for both sexes initially rose slightly after the onset of the pandemic and then decreased. When the data were analyzed by age group, the decline in hospitalization rates was more pronounced in individuals over 65, especially in those over 75, with a decrease of approximately 10 per 100 000. In contrast, the hospitalization rates in the 20–44 and 45–54 age groups remained stable before and after the pandemic. The in-hospital mortality rates in the 65–74 and over 75 age groups initially increased following the emergence of COVID-19, then decreased. Hospitalization rates declined for both NHI and MA beneficiaries, though the decrease was significantly more pronounced in the MA group, with a reduction of about 10 per 100 000 individuals. In-hospital mortality rates in the NHI and MA groups initially increased following the onset of COVID-19 and then declined. The increase in in-hospital mortality was more substantial in the MA group than in the NHI group.

Changes in the Admission Rate and 30-Day In-hospital Mortality for Patients With Hemorrhagic Stroke and the Impact of Coronavirus Disease 2019

Hemorrhagic stroke had different outcomes compared to ischemic stroke. In January 2020, a month before the pandemic, 2014 patients were admitted to hospitals. However, by February 2020, the number of inpatients had decreased by 150, a 7.4% reduction, resulting in a total of 1864. Subsequently, the number of hospitalizations stabilized. The in-hospital mortality rate for hemorrhagic stroke initially decreased from 12.9% to 12.7%, but it gradually increased over time. The p-value for this increase in mortality was not statistically significant.

Supplemental Materials 6–10 illustrate the ITS analysis by sex, age, and insurance type. After the pandemic, the hospitalization rate declined for both male and female and subsequently stabilized. The in-hospital mortality rates initially decreased and then increased for males, while for females, they slightly increased and then plateaued; however, the p-value did not indicate significance. When the data were analyzed by age group, the decline in rates was more pronounced in the >65 age group, especially in the >75 age group, which saw a decrease of approximately 1 per 100 000. In contrast, the rates in the 20–44 and 45–54 age groups remained consistent before and after the pandemic outbreak. The in-hospital mortality rates in the >75 years age group increased but showed high variability. Although hospitalization rates decreased for both NHI and MA beneficiaries, the decline was considerably more substantial in the MA beneficiaries, with a decrease of approximately 1 per 100 000 individuals. In terms of in-hospital mortality, the MA group saw a decrease of about 2 per 100 000 individuals, whereas the rates in the NHI group remained unchanged.

DISCUSSION

The results of this study indicate that the COVID-19 pandemic has led to a decrease in hospital admissions for patients with ischemic and hemorrhagic strokes, subsequently affecting in-hospital mortality rates. Specifically, in-hospital mortality for ischemic stroke initially rose following the outbreak of COVID-19 but decreased over time. Conversely, in-hospital mortality for hemorrhagic stroke initially fell but later increased. ITS analysis was utilized to conduct the time-series analysis in this study. ITS is a well-established method for evaluating the outcomes of population-level interventions at specific time points [20]. Korea is undergoing rapid population aging, resulting in an increased incidence of stroke among older adults. This demographic shift complicates the assessment of COVID-19’s impact using traditional before-and-after analyses. Therefore, this study adopted the ITS methodology to explore the effects of COVID-19 on stroke.

A simple comparison conducted before and after an intervention merely indicates a disparity, whereas ITS analysis provides a more precise assessment by capturing changes over time. Relying on conventional comparisons similar to those used in previous studies could result in either an overestimation or underestimation of fluctuations in hospitalization rates and mortality. To avoid this potential issue, we employed ITS analysis.

Instead of using basic pre-intervention and post-intervention comparisons, this study utilized ITS, a well-established method for evaluating the outcomes of population-level interventions at specific time points. The monthly patient count varied from approximately 4000 to 6000 individuals. When averaged daily, this translates to about 13 to 20 individuals per day. A decrease in the number of patients could lead to greater variability in daily counts, which may reduce the reliability of the findings. As a reviewer pointed out, it is possible that these fluctuations are due to monthly characteristics. However, the marked decrease observed in February 2020 and January of 2020, compared to previous years, indicates that the effects of COVID-19 were more significant than typical monthly variations.

This study is the first in Korea to use ITS methods to assess the impact of COVID-19 on ischemic and hemorrhagic stroke over time, utilizing national-level data. The research findings revealed that the pandemic’s effects varied among different demographic groups, such as sex, age, and socioeconomic status. Notably, individuals covered by MA had lower admission rates for both ischemic and hemorrhagic stroke compared to those insured under NHI.

Numerous international studies have examined the impact of COVID-19 on stroke, indicating a decrease in hospitalization rates for ischemic stroke [21–35], while also noting an increase in in-hospital mortality rates [28–35]. However, the mortality rate observed in this study was lower compared to those reported in global studies.

Several factors are responsible for the decrease in stroke admission rates. The surge of COVID-19 patients in emergency departments has reduced the use of these facilities and delayed treatment for time-sensitive conditions such as stroke [10,36–38]. Additionally, the implementation of stringent social distancing measures and triage protocols to curb COVID-19 transmission has overwhelmed emergency departments. The government has vigorously promoted these policies to keep individuals away from the infection. Limited medical resources and the absence of adequate quarantine facilities may also discourage patients from seeking care in emergency rooms. Moreover, the widespread fear of contracting COVID-19 may prevent individuals from seeking medical attention when they exhibit symptoms, potentially delaying treatment. Our study defined in-hospital mortality as death occurring within 30 days of hospitalization, excluding individuals who died from stroke outside of a hospital setting. This limitation underscores the necessity for a more comprehensive follow-up study that includes patients who succumbed to strokes outside of hospitals.

However, in-hospital mortality within 30 days of ischemic stroke initially increased after the outbreak, then subsequently decreased. This change in in-hospital mortality due to ischemic stroke suggests that the mortality rate rose as hospitals primarily admitted severely ill patients, which then normalized over time. Additionally, this could indicate that patients with ischemic stroke experienced longer delays in treatment, as evidenced by the extended duration from symptom onset to arrival at emergency departments.

Despite the lack of statistical significance in the power analysis, we observed a distinct pattern that suggested an effect on in-hospital mortality for hemorrhagic stroke when we segregated the population based on NHI and MA status. The COVID-19 outbreak led to fewer hospitalizations, potentially increasing the availability of medical resources and facilitating more rapid treatment. This improvement might have disproportionately benefited the MA group. Conversely, it is possible that severely ill MA patients experienced reduced access to emergency departments compared to NHI patients. This could have led to an increase in out-of-hospital deaths, contributing to a relative decrease in in-hospital mortality.

Although we investigated the impact of the COVID-19 outbreak on stroke admission and in-hospital mortality according to socioeconomic status, this study has several limitations. Firstly, it is possible that additional deaths from hemorrhagic stroke occurred that were not accounted for. In this study, patients with MA experienced fewer hospitalizations and lower in-hospital mortality rates for ischemic stroke, yet they had higher in-hospital mortality rates for hemorrhagic stroke. It is hypothesized that some deaths in the MA group may not have been captured in the hospitalization data. To confirm this, further analysis is required, involving matching mortality data from Statistics Korea. Secondly, our study assumed that the COVID-19 outbreak was the sole factor affecting stroke admission rates and in-hospital mortality. However, we cannot discount the possibility that other factors also played a role. Numerous variables can influence stroke outcomes, making it impractical to adjust for all potential confounders. Nevertheless, when comparing stroke patient data from February 2020 to January 2020 during the COVID-19 pandemic, the reduction in hospitalizations was significantly greater than in previous years, suggesting that no other factor had as widespread and significant an impact as COVID-19. Therefore, our study focused on the effects of COVID-19, assuming that other confounding variables remained constant throughout the 5-year study period before and after the onset of the pandemic. Having a control group of patients with other diseases, such as cancer, is essential when comparing health insurance patients to those on medical aid. However, when establishing such a control group, it is crucial to ensure that the characteristics of the disease groups are comparable, especially when using a 30-day in-hospital mortality rate as a measurable outcome. Analyzing cancer patients, for instance, poses practical challenges, and it is important to decide whether to group them by all cancer types or by specific cancers, considering the diverse epidemiological traits associated with different types and stages of cancer. We believe this can be addressed in a follow-up study that links health insurance claims data with national cancer registries.

This study concluded that the COVID-19 outbreak resulted in decreased admission rates for ischemic and hemorrhagic stroke among individuals over 75 and MA beneficiaries. Additionally, the outbreak has impacted in-hospital mortality rates associated with these strokes. In Korea, the increasing population of older adults is expected to lead to a higher incidence of stroke in the upcoming years. It is crucial to implement appropriate health policies to provide marginalized populations with the necessary resources to prevent the worsening of health disparities. Developing a healthcare infrastructure that delivers adequate medical services and high-quality acute care, tailored to specific demographics and socioeconomic statuses, is a proactive strategy to prepare for future infectious disease outbreaks.

Supplemental Materials

Notes

Conflict of Interest

The authors have no conflicts of interest associated with the material presented in this paper.

Funding

None.

Author Contributions

Conceptualization: Chang Y, Hwang SH, Lee H, Lee JY. Data curation: Hwang SH. Formal analysis: Hwang SH. Funding acquisition: None. Writing – original draft: Chang Y, Hwang SH. Writing – review & editing: Chang Y, Hwang SH, Bai H, Park S, Cho E, Kim D, Lee H, Lee JY.

Acknowledgements

Figure 1

Numbers of admitted and deceased patients with stroke from January 2017 to December 2021 by types of stroke and months. (A) Number of admssion. (B) Number of 30-day in-hospital death. COVID-19, coronavirus disease 2019.

Figure 2

Interrupted time series analysis of the monthly admission rate (A) ischemic stroke, (B) hemorrhagic stroke and 30-day in-hospital mortality (C) ischemic stroke, (D) hemorrhagic stroke by types of stroke before and after the coronavirus disease 2019 (COVID-19) outbreak in February 2020 (dotted line).

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Figure & Data

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