C-sections and hospital characteristics: a long term analysis on low-risk deliveries

Abstract

Background Policymakers aim to reduce C-section (CS) rates, due to well documented overtreatment. However, little is known about how hospital characteristics relate to their c-section rates on low-risk deliveries (CSR-LRD). Methods CSR-LRD were computed using inpatient data from all Portuguese National Health Service hospitals (2002-2011). Linear and Fractional Response Models were estimated to quantify the relationship between CSR-LRD and a set of hospital characteristics: hospital size, type (exclusively obstetrics or not), Neonatal Intensive Care Unit (NICU) availability, obstetrician-to-obstetric bed ratio, and teaching status. Results CSR-LRD increased from 11.7% (2002) to 14.1% (2008), declining to 12.5% in 2011. While larger hospitals and hospitals with NICU had higher CSR-LRD rates, teaching status and obstetrician-to-obstetric bed ratio had no significant effect. Adjusted estimates, controlling for those four characteristics, indicate 91% of the variation in the CSR-LRD is left unexplained. Conclusion Hospital characteristics do not explain variation in CSR-LRD rates. Further studies considering medical practice, financial incentives to hospitals and/or physicians, and patient education are needed.

Efficiency of Obstetric Services in Germany—The Role of Variation and Overheads

“…While the impact of overheads on the break-even point was demonstrated before, the relevance of the variation in demand requires a stochastic simulation, which is more complex and not frequently performed. For instance, Markov models of hospital departments focus on averages and steady-states, so variation in demand can hardly be studied [ 19 , 20 ]. Another approach was chosen by van den Berg et al [ 26 ], who developed a Linear Program (LP) to determine the most cost-effective mode of delivering obstetric and pediatric services in a region in Northeast Germany.…”

“…However, these bigger institutions are usually also on a higher level with more severe cases. Both effects are difficult to discriminate, so some studies indicate that bigger hospitals have a higher CS rate [ 19 ];…”

“…All patients will be accepted (∞), and the first patients will receive first services (FIFO). Contrary to other authors [ 19 , 20 ], this model does not develop a traditional Markov model as the focus of this paper is on the variation, not the average in the steady state equilibrium [ 21 ].…”