Challenge: Gaining Deeper Insight into Excessive Hospital Length of Stay

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A healthcare researcher approached us with a focused objective: to analyze patterns of excessive Length of Stay (LOS) in hospitalized patients. Standard LOS metrics often fail to account for outliers, which can skew interpretations and limit the usefulness of findings in operational or policy planning.

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To conduct a more meaningful analysis, the client requested two key metrics:

• Case Mix Adujusted - Length of Stay (CMA-LOS)

• Geometrical Mean Length of Stay (GMLOS)

 

These measurements would provide both contextual benchmarking and statistical balance.

Our team extracted and prepared CMA-LOS and GMLOS data, using the APR-DRG grouping methodology to ensure clinically meaningful comparisons.

• CMA-LOS provided a weighted average based on case severity, aligning the research with expected resource use and patient acuity.

• GMLOS, by contrast, offered a statistically robust measure that reduces the impact of outlier cases, yielding a more precise picture of typical LOS values.

 

This dual approach allowed the client to identify systemic inefficiencies, understand where care durations exceeded expectations, and guide further inquiry into underlying causes.

• Enhanced precision in identifying excessive LOS patterns

• Improved ability to compare LOS across patient groups and services

• Robust foundation for data-driven recommendations

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Key Deliverables:

• Case Mix Adjusted - LOS (CMA-LOS)

• Geometrical Mean LOS (GMLOS)

• APR-DRG-based segmentation

• Clean, research-ready datasets

 

By combining clinical relevance with statistical accuracy, we helped transform a focused research inquiry into a platform for strategic improvement.