Objective:

To investigate whether hospital bed size is associated with length of stay (LOS) for acute ischemic stroke patients treated with intravenous alteplase.

Background:

Acute ischemic stroke is a leading cause of morbidity and mortality worldwide. Hospital bed size serves as a proxy for healthcare facility capacity to provide specialized stroke care. Larger hospitals typically possess advanced technologies, higher staff-to-patient ratios, and specialized stroke units, which may influence patient LOS. Understanding how hospital resources affect stroke care could guide how to optimize stroke treatment.

Design/Methods:

We analyzed acute stroke data examining the relationship between hospital bed size and LOS. Following Shapiro-Wilk testing (p less than 0.001), data showed a non-normal distribution. We used the Kruskal-Wallis test to compare median LOS across five hospital bed size categories: fewer than 5 beds, 100-199 beds, 200-299 beds, 300-499 beds, and 500 or more beds. Post-hoc pairwise comparisons were conducted between all groups.

Results:

The Kruskal-Wallis test revealed a statistically significant relationship between hospital bed size and LOS (H² equals 7268.560, p less than 0.001). Smaller hospitals (fewer than 5 beds) consistently demonstrated longer LOS compared to all other categories (all adjusted p less than 0.001). Medium-sized hospitals (100-199 beds versus 200-299 beds) showed minimal LOS difference (test statistic equals negative 5.953). LOS decreased as bed size increased from 100-199 beds to 300-499 beds (test statistic equals negative 23.412, p less than 0.001). However, the largest hospitals (500 or more beds) demonstrated longer LOS compared to 200-299 bed facilities (test statistic equals negative 34.878, p less than 0.001).

Conclusions:

Hospital bed size significantly impacts LOS for acute stroke patients treated with alteplase, with optimal efficiency observed in moderately large hospitals (200-299 beds). Beyond this threshold, increasing hospital size correlates with longer LOS, potentially reflecting decreased staff-to-patient ratios.