Variation in Acute Medicine Units: Measuring it, understanding it, and reducing it

Area of Science:

• Health Services Research
• Hospital Management
• Clinical Operations

Background:

• National recommendations exist for Acute Medicine Units (AMUs), but a standardized model of care is lacking.
• Robust data is often unavailable to evaluate the impact of system changes in AMUs.
• Assessing the effectiveness of different care models requires reliable patient outcome metrics.

Purpose of the Study:

• To develop a system for real-time data collection in AMUs.
• To investigate the association between consultant continuity and patient outcomes.
• To provide a tool for unit governance and quality improvement initiatives.

Main Methods:

• An Excel file was designed to interface with a hospital patient management system.
• Real-time data on Acute Medicine Unit Length of Stay (AMULOS), mortality, and readmissions were collected.
• Data analysis focused on the impact of consultant continuity on AMULOS.

Main Results:

• Improved consultant continuity of care was linked to a reduction in AMULOS.
• Enhanced consultant continuity also led to reduced variation in AMULOS.
• The Excel tool provided timely access to patient-level and consultant data.

Conclusions:

• Real-time data collection is vital for Acute Medicine Unit governance and quality improvement.
• Standardized datasets can facilitate comparisons between AMUs and improve understanding of care models.
• Developing similar data systems is encouraged for all AMUs to enhance patient outcomes.