Infant to staff ratios and risk of mortality in very low birthweight infants

Arch Dis Child Fetal Neonatal Ed. 2003 Mar;88(2):F94-7. doi: 10.1136/fn.88.2.f94.

Abstract

Objectives: To assess the effect that infant to staff ratios, in the first three days of life, have on the survival to hospital discharge of very low birthweight infants (<1500 g), having adjusted for initial risk and unit workload.

Design: In a retrospective analysis of a cohort of patients, the number of infants per nurse per shift were averaged for the first three days after admission and related to risk of mortality by logistic regression analysis. Infant to staff ratio was divided into terciles of low (1.16-1.58), medium (1.59-1.70), and high (1.71-1.97) infants per staff member.

Subjects: 692 very low birthweight infants admitted to the Intensive Care Nursery, Royal Women's Hospital, Brisbane over a four year period from January 1996 to December 1999.

Main outcome measures: Survival to hospital discharge, adjusted for initial risk using the Clinical Risk Index for Babies (CRIB) score, and adjusted for unit workload using dependency scores.

Results: There were 80 deaths among the 692 babies analysed for the study period. The odds of mortality, adjusted for initial risk and infant dependency scores (unit workload), were improved by 82% when an infant/staff ratio of greater than 1.71 occurred, suggesting improved survival with the highest infant/staff ratio. The low and medium staffing levels corresponded with similar odds ratios for mortality.

Conclusions: Infants exposed to higher infant to staff ratios have an improved adjusted risk of survival to hospital discharge.

MeSH terms

  • Birth Weight
  • Female
  • Health Services Research
  • Hospital Mortality
  • Humans
  • Infant, Newborn
  • Infant, Premature
  • Infant, Very Low Birth Weight*
  • Intensive Care Units, Neonatal / standards*
  • Logistic Models
  • Male
  • Odds Ratio
  • Outcome Assessment, Health Care
  • Personnel Staffing and Scheduling / standards*
  • Prognosis
  • Queensland / epidemiology
  • Retrospective Studies
  • Survival Rate
  • Workforce
  • Workload