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INTRODUCTION

Hospital performance is traditionally assessed through the positive correlation between admission volumes and bed occupancy rates. Moroccan hospital data for 2023 reveal a break with this paradigm, with a historic peak in admissions (1,211,765 patients) occurring alongside a sharp decline in the average bed occupancy rate (BOR) to 56.6%. In this context, this study aimed to econometrically analyze the determinants of this paradoxical “decoupling” in order to determine whether the decline in occupancy reflects inefficiency or a transformation of the production model, while also exploring the structural heterogeneity of the system.

METHODS

A retrospective longitudinal study (2016–2023) was conducted using inpatient hospitalization data from the Ministry of Health (Santé en Chiffres 2023). A multiple linear regression model based on standardized data was used to quantify the respective contributions of admissions, bed capacity, and average length of stay (ALOS) to variations in BOR.

RESULTS

The analysis confirms a major scissor effect in 2023. The model (R2 = 0.793) shows that ALOS is a key structural determinant (β = +0.79), and that its sharp reduction to 3.5 days offset the positive effect of increased admissions (β = +0.95). Disaggregated analysis revealed a two-tier system: university hospitals were approaching saturation (BOR > 70%; ALOS 6–8 days), while provincial hospitals exhibited underutilization of capacity and very rapid patient turnover (ALOS 1–3 days).

CONCLUSION

The Moroccan public hospital system appears to be shifting toward a “just-in-time” operational logic, rendering the traditional bed occupancy indicator less relevant for assessing overall performance. However, this apparent technical efficiency conceals substantial disparities and calls for increased vigilance regarding quality of care, particularly given the risk of readmissions associated with increasingly early clinical discharge.