Association Between In-hospital Mortality and the Institutional Factors of Intensive Care Units with a Focus on the Intensivist-to-bed Ratio: A Retrospective Cohort Study

J Intensive Care Med. 2024 Oct;39(10):958-964. doi: 10.1177/08850666241245645. Epub 2024 Apr 3.

Abstract

Purpose: To elucidate the relationship between in-hospital mortality and the institutional factors of intensive care units (ICUs), with a focus on the intensivist-to-bed ratio. Methods: A retrospective cohort study was conducted using a Japanese ICU database, including adult patients admitted between April 1, 2020 and March 31, 2021. We used a multilevel logistic regression model to investigate the associations between in-hospital mortality and the following institutional factors: the intensivist-to-bed ratios on weekdays or over weekends/holidays, different work shifts, hospital-to-ICU-bed ratio, annual-ICU-admission-to-bed ratio, type of hospital, and the presence of other medical staff. Results: The study population comprised 46 503 patients admitted to 65 ICUs. The in-hospital mortality rate was 8.1%. The median numbers of ICU beds and intensivists were 12 (interquartile range [IQR] 8-14) and 4 (IQR 2-9), respectively. In-hospital mortality decreased significantly as the intensivist-to-bed ratio at 10 am on weekdays increased: the average contrast indicated a 20% (95% confidence interval [CI]: 1%-38%) reduction when the ratio increased from 0 to 0.5, and a 38% (95% CI: 9%-67%) reduction when the ratio increased from 0 to 1. The other institutional factors did not present a significant effect. Conclusions: The intensivist-to-bed ratio at 10 am on weekdays had a significant effect on in-hospital mortality. Further investigation is needed to understand the processes leading to improved outcomes.

Keywords: human resource allocation; in-hospital mortality; institutional factors; intensive care unit; quality of care.

MeSH terms

  • Adult
  • Aged
  • Bed Occupancy / statistics & numerical data
  • Female
  • Hospital Mortality*
  • Humans
  • Intensive Care Units* / statistics & numerical data
  • Japan / epidemiology
  • Logistic Models
  • Male
  • Middle Aged
  • Personnel Staffing and Scheduling / statistics & numerical data
  • Retrospective Studies