Effectiveness of an Analytics-Based Intervention for Reducing Sleep Interruption in Hospitalized Patients: A...

Area of Science:

• Clinical Informatics
• Patient Safety
• Sleep Medicine

Background:

• Hospitalized patients frequently experience sleep disruptions due to iatrogenic causes.
• Reducing these sleep interruptions can positively impact patient well-being.
• Existing evidence suggests that sleep interruptions can be safely minimized.

Purpose of the Study:

• To evaluate a clinical decision support (CDS) tool utilizing real-time data and a predictive algorithm.
• To determine if the CDS tool can help physicians identify stable patients for discontinuing overnight vital sign checks.
• To assess the safety and efficacy of reducing routine vital sign monitoring.

Main Methods:

• A randomized clinical trial (RCT) involving 1699 patients on a general medical service.
• Intervention group received CDS notifications to discontinue vital sign checks for stable patients.
• Primary outcome was delirium incidence; secondary outcomes included vital sign checks and adverse events.

Main Results:

• The intervention group showed a significant decrease in mean nighttime vital sign checks (0.97 vs 1.41, P<.001).
• No significant increase in intensive care unit transfers or code blue alarms was observed.
• The incidence of delirium was not significantly different between the intervention and control groups (11% vs 13%, P=.32).

Conclusions:

• A CDS tool with a real-time prediction algorithm can safely reduce routine vital sign checks in stable hospitalized patients.
• This reduction provides patients with more opportunities for sleep.
• The approach may be applicable to other aspects of hospital care dependent on clinical stability.