Patient Outcomes and Unit Composition With Transition to a High-Intensity ICU Staffing Model: A Before-and-After Study

Jennifer L Proper; David A Wacker; Salma Shaker; Jamie Heisdorffer; Rami M Shaker; Larissa T Shiue; Kathryn M Pendleton; Lianne K Siegel; Ronald A Reilkoff

doi:10.1097/CCE.0000000000000864

Patient Outcomes and Unit Composition With Transition to a High-Intensity ICU Staffing Model: A Before-and-After Study

Crit Care Explor. 2023 Feb 6;5(2):e0864. doi: 10.1097/CCE.0000000000000864. eCollection 2023 Feb.

Authors

Jennifer L Proper¹, David A Wacker², Salma Shaker³, Jamie Heisdorffer⁴, Rami M Shaker⁵, Larissa T Shiue⁶, Kathryn M Pendleton², Lianne K Siegel¹, Ronald A Reilkoff²

Affiliations

¹ Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN.
² Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Minnesota Medical School, Minneapolis, MN.
³ Department of Surgery, North Memorial Health Hospital, Robbinsdale, MN.
⁴ Department of Nursing Education, Normandale Community College, Bloomington, MN.
⁵ University of Minnesota Medical School, Minneapolis, MN.
⁶ Department of Emergency Medicine, Mayo Clinic, Rochester, MN.

Abstract

Provider staffing models for ICUs are generally based on pragmatic necessities and historical norms at individual institutions. A better understanding of the role that provider staffing models play in determining patient outcomes and optimizing use of ICU resources is needed.

Objectives: To explore the impact of transitioning from a low- to high-intensity intensivist staffing model on patient outcomes and unit composition.

Design setting and participants: This was a prospective observational before-and-after study of adult ICU patients admitted to a single community hospital ICU before (October 2016-May 2017) and after (June 2017-November 2017) the transition to a high-intensity ICU staffing model.

Main outcomes and measures: The primary outcome was 30-day all-cause mortality. Secondary outcomes included in-hospital mortality, ICU length of stay (LOS), and unit composition characteristics including type (e.g., medical, surgical) and purpose (ICU-specific intervention vs close monitoring only) of admission.

Results: For the primary outcome, 1,219 subjects were included (779 low-intensity, 440 high-intensity). In multivariable analysis, the transition to a high-intensity staffing model was not associated with a decrease in 30-day (odds ratio [OR], 0.90; 95% CI, 0.61-1.34; p = 0.62) or in-hospital (OR, 0.89; 95% CI, 0.57-1.38; p = 0.60) mortality, nor ICU LOS. However, the proportion of patients admitted to the ICU without an ICU-specific need did decrease under the high-intensity staffing model (27.2% low-intensity to 17.5% high-intensity; p < 0.001).

Conclusions and relevance: Multivariable analysis showed no association between transition to a high-intensity ICU staffing model and mortality or LOS outcomes; however, the proportion of patients admitted without an ICU-specific need decreased under the high-intensity model. Further research is needed to determine whether a high-intensity staffing model may lead to more efficient ICU bed usage.

Keywords: hospital mortality; intensive care unit; intensive care unit triage; intensivist staffing; length of stay.