Intensive care unit availability indexed to patient complexity.

Area of Science:

• Healthcare Management
• Reliability Engineering
• Hospital Operations

Background:

• Clinical Unit availability is crucial for patient care and depends on resources and patient demands.
• Patient complexity and quantity significantly impact resource consumption and unit capacity.
• Existing methods lack a quantitative approach to estimate patient-driven demand on clinical units.

Purpose of the Study:

• To present a procedure for estimating Clinical Unit availability.
• To utilize Diagnosis Related Groups (DRG) as a metric for patient complexity and quantity.
• To determine the theoretical patient load limit that could overwhelm a clinical unit.

Main Methods:

• Proposed using Diagnosis Related Groups (DRG) to estimate patient complexity.
• Introduced Accumulated DRG (DRG(a)) to represent the combined patient complexity and quantity.
• Applied reliability theory to analyze 4 months of data from an adult Intensive Care Unit (ICU).

Main Results:

• Identified the theoretical patient combination that would lead to clinical unit collapse.
• Validated the findings with expert advisors, aligning with their practical experience.
• Reliability and availability results correlated with actual incident reports from the clinic.

Conclusions:

• The proposed DRG-based procedure effectively estimates Clinical Unit availability.
• This method provides a reasonable basis for understanding unit capacity and potential failure points.
• Recommendations are applicable for designing new units or managing existing ones.