Heavy workloads facing health care providers may lead to changes in care procedures that, in turn, impact patient outcomes. In this study, we use data collected through direct observation of vaginal deliveries in three large Kenyan hospitals to explore how providers cope with busyness in the maternity ward – a high-stress environment where hard-to-schedule patient admissions and uncertainty around labor progression could result in unexpectedly high workloads. We begin by documenting variation in provider workload (measured as patient volume relative to nurse-midwife staffing) by the time of day and show that our identifying variation is uncorrelated with observed covariates. We then look at the relationship between workload and measures of quality including provider adherence to guidelines during routine labor & delivery and immediate maternal and newborn care, disrespectful care, and patient outcomes. We find that the relationship between workload and quality is weak. To explain the lack of a meaningful workload-quality association in this setting, we examine how providers cope with increased workload, including task delegation to less qualified team members and clinical interventions to speed up labor.

We study the effects of multi-state purchasing pools for Medicaid prescription drugs on drug rebates, utilization, and payment rates. These purchasing pools combine bulk purchasing with preferred drug lists to increase state bargaining power in negotiating supplemental rebates with drug manufacturers for Medicaid. Since 2003, over 30 states have participated in one of the three Medicaid-focused purchasing pools. Using data from the Medicaid Budget & Expenditure System and the State Drug Utilization Data, we find that entering a purchasing pool increases the probability of a state collecting supplemental drug rebates and the amount of these rebates. Utilization for generic drugs goes up while per-prescription payment decreases for both branded and generic drugs following a state’s participation in a purchasing pool. Our analysis suggests that both combined volume/negotiation and access to pricing information may be at play in driving these results.