This dissertation studies the regulation of hospitals. Hospitals are firms that produce an important service whose quality we would like to regulate. Given a myriad of regulatory options, the choice over regulatory design depends intricately on an understanding of hospital production and behavior – to which this dissertation contributes.
The first chapter was published as "How Do Hospitals Respond to Input Regulation? Evidence from the California Nurse Staffing Mandate" in the Journal of Health Economics (2023, 92, 102826). In this first chapter, I estimate the causal effects of minimum nurse-to-patient ratio regulation on California hospitals. Mandated minimum nurse-to-patient ratios for hospitals were legislated in California in 1999 and implemented in the early 2000s. Despite the magnitude of the regulation's impact and the growing interest in similar regulation worldwide, we lack conclusive evidence on the effects of the mandate.
To address this gap in the literature, I estimate the causal effects of ratio regulation on California hospitals. I construct a dataset linking data on hospital financials with patient-level discharge records. I make the code for the construction of the hospital financial data and notes on variable measurement available on my website for other researchers (https://chandniraja.com/datasets/). Using an event study research design, I find the mandate led to a 58 min increase in nursing time per patient day and 9 percent increase in the wage bill per patient day in the general medical/surgical acute care unit among treated hospitals. Hospitals responded on several margins: increased use of lower-licensed and younger nurses, reduced capacity by 16 beds (14 percent), and increased bed utilization rates by 0.045 points (8 percent). Focusing on heart attack patients, I find a significant reduction in length of stay (5 percent) and no effect on the 30-day all-cause readmission rate. Finding no evidence of premature ("quicker and sicker") discharge from the readmission rate, I conclude that patients recovered more quickly due to an improvement in care quality per day.
Given the regulation's stated objective to improve care quality at hospitals, a natural next question for an economist is whether the regulation is efficient at doing so. That is: In a setting where regulation targets a single input (nurses) but production is multi-input, is the chosen input allocation under the regulation equal to the cost-minimizing allocation? And in a setting where hospitals are heterogeneous in productivity and the patients they admit, is the regulated input (nurses) being allocated to where it is productive?
The second chapter focuses on answering these questions. I specify a structural value-added model of hospital quality production that allows labor productivity to vary with observed patient type and unobserved hospital productivity. I bring this model to a dataset that allows me to measure quality in terms of clinical outcomes and to measure input use. I find nurses and physicians to be highly complementary (near Leontief) in production. I show that minimum nurse-to-patient ratios that do not account for these complementarities increase healthcare labor costs by 1.4 percent holding quality constant amounting to $24 million in costs across hospitals affected by the mandate. I recover hospital productivities and I show that on average there was no across-hospital misallocation of nurses to low productivity hospitals due to the ratio regulation – low staffing hospitals are as productive as their high staffing neighbors. However, I find efficiency gains can be made by reallocating nurses to hospitals with higher severity patients where they are more valuable.
