BACKGROUND: Given increased public reporting of the wide variation in hospital obstetric quality, we sought to understand how women incorporate quality measures into their selection of an obstetric hospital. METHODS: We surveyed 6141 women through Ovia Pregnancy, an application used by women to track their pregnancy. We used t tests and chi-square tests to compare response patterns by age, parity, and risk status. RESULTS: Most respondents (73.2%) emphasized their choice of obstetrician/midwife over their choice of hospital. Over half of respondents (55.1%) did not believe that their choice of hospital would affect their likelihood of having a cesarean delivery. While most respondents (74.9%) understood that quality of care varied across hospitals, few prioritized reported hospital quality metrics. Younger women and nulliparous women were more likely to be unfamiliar with quality metrics. When offered a choice, only 43.6% of respondents reported that they would be willing to travel 20 additional miles farther from their home to deliver at a hospital with a 20 percentage point lower cesarean delivery rate. DISCUSSION: Women's lack of interest in available quality metrics is driven by differences in how women and clinicians/researchers conceptualize obstetric quality. Quality metrics are reported at the hospital level, but women care more about their choice of obstetrician and the quality of their outpatient prenatal care. Additionally, many women do not believe that a hospital's quality score influences the care they will receive. Presentations of hospital quality data should more clearly convey how hospital-level characteristics can affect women's experiences, including the fact that their chosen obstetrician/midwife may not deliver their baby.

Obstetricians learned this lesson the hard way. A century ago, very little in obstetric practice was codified. Care was artisanal, variable, and sometimes dangerous. Based on a theory that childbirth is inherently "pathogenic," prominent American obstetricians recommended sweeping reforms. (DeLee, JB, Principles and Practice of Obstetrics, 1913, first edition). This article is protected by copyright. All rights reserved.

Childbirth is a complex clinical service requiring the coordinated support of highly trained healthcare professionals as well as management of a finite set of critical resources (such as staff and beds) to provide safe care. The mode of delivery (vaginal delivery or cesarean section) has a significant effect on labor and delivery resource needs. Further, resource management decisions may impact the amount of time a physician or nurse is able to spend with any given patient. In this work, we employ queueing theory to model one year of transactional patient information at a tertiary care center in Boston, Massachusetts. First, we observe that the M/G/∞ model effectively predicts patient flow in an obstetrics department. This model captures the dynamics of labor and delivery where patients arrive randomly during the day, the duration of their stay is based on their individual acuity, and their labor progresses at some rate irrespective of whether they are given a bed. Second, using our queueing theoretic model, we show that reducing the rate of cesarean section - a current quality improvement goal in American obstetrics - may have important consequences with regard to the resource needs of a hospital. We also estimate the potential financial impact of these resource needs from the hospital perspective. Third, we report that application of our model to an analysis of potential patient coverage strategies supports the adoption of team-based care, in which attending physicians share responsibilities for patients.

BACKGROUND: Health care costs are an important policy focus in the United States. The magnitude and drivers of variation in the costs of common operative procedures are not well understood. We sought to characterize variation in costs across hospitals. METHODS: We used data from the Nationwide Inpatient Sample from 2001-2011 for 5 elective operations: colectomy, coronary artery bypass graft, total knee arthroplasty, cesarean section, and lung resection. Hospitals were benchmarked for each using hierarchical risk- and reliability-adjustment methods to generate an observed-to-expected cost ratio, which was adjusted for patient demographics, comorbidity, wage index, and procedure complexity. Hospitals were divided into quintiles. Characteristics of high- and low-quintile hospitals and their adjusted outcomes were examined. RESULTS: Cost observed-to-expected ratios ranged widely for all 5 procedures: 14.9-fold for colectomy, 5.5-fold for coronary artery bypass graft, 12.5-fold for lung resection, 10.6-fold for total knee arthroplasty, and 28.0-fold for cesarean section. Comparing highest to lowest cost quintiles of hospitals, high-cost hospitals were more likely to serve minority and Medicaid patients. Mortality was elevated significantly in high-cost hospitals for colectomy, coronary artery bypass graft, and lung resection (adjusted odds ratio 1.99, 1.32, 2.57; respectively). Service lines were correlated at low-cost hospitals. There was a significant association between greater procedure volume and low-cost hospitals for colectomy, coronary artery bypass graft, and total knee arthroplasty. CONCLUSION: Despite robust adjustment, there is wide cost variation for common operative procedures in the United States. High-cost hospitals may need to focus on cost reduction at the hospital level to reduce cost across service lines. Benchmarking costs may identify significant opportunities to promote value, or the balance between cost and quality, in operative care in the United States.