We study whether hospitals that exhibit systematically higher bed occupancy rates are associated with lower quality in England over 2010/11–2017/18. We develop an economic conceptual framework to guide our empirical analysis and run regressions to inform possible policy interventions. First, we run a pooled OLS regression to test if high bed occupancy is associated with, and therefore acts as a signal of, lower quality, which could trigger additional regulation. Second, we test whether this association is explained by exogenous demand–supply factors such as potential demand, and unavoidable costs. Third, we include determinants of bed occupancy (beds, length of stay, and volume) that might be associated with quality directly, rather than indirectly through bed occupancy. Last, we use a within-between random-effects specification to decompose these associations into those due to variations in characteristics between hospitals and variations within hospitals. We find that bed occupancy rates are positively associated with overall and surgical mortality, negatively associated with patient-reported health gains, but not associated with other indicators. These results are robust to controlling for demand–supply shifters, beds, and volume. The associations reduce by 12%-25% after controlling for length of stay in most cases and are explained by variations in bed occupancy between hospitals.

Many OECD countries consider waiting times as a significant health policy issue (Siciliani et al., 2013 ). Publicly-funded health systems, with excess demand due to capacity constraints and limited or no co-payments, rely on waiting times as a form of non-price rationing to reach equilibrium between the demand for and the supply of health services (Martin & Smith, 1999).The main justification for rationing public healthcare by waiting times, rather than price, is that access to health services should not depend on ability to pay. Instead, patients in equal need, severity or complexity should wait the same, irrespective of their ability to pay or geographic and social characteristics such as distance from the hospital and socioeconomic status (SES).