Objective
We sought to analyze the association between hospital obstetric volume and perinatal outcomes in California.
Study Design
This was a retrospective cohort study of births occurring in California in 2006. Hospitals were divided into 4 obstetric volume categories. Unadjusted rates of neonatal mortality and birth asphyxia were calculated for each category, overall and among term deliveries with birthweight >2500 g. Multivariable logistic regression was used to control for confounders. Deliveries in rural hospitals were analyzed separately using different volume categories.
Results
Prevalence of asphyxia increased with decreasing hospital volume overall and among term, non-low-birthweight infants, from 9/10,000 live births at highest-volume hospitals to 18/10,000 live births at the lowest-volume hospitals ( P < .001). Similar trends were observed in rural hospitals, with rates increasing from 7-34/10,000 live births in low-volume rural hospitals ( P < .001).
Conclusion
These findings provide evidence for an inverse association between hospital obstetric volume and birth asphyxia.
While much evidence has documented the benefits of regionalization of high-risk obstetrics to high-volume hospitals with specialized care, there is not a similar consensus regarding the role of regionalization and hospital volume in low-risk or general obstetric practice. Some studies have found that perinatal outcomes such as neonatal mortality and asphyxia are less prevalent in high-volume hospitals, while others have reported a lack of association or suggested that lower-volume settings may be better for some outcomes in low-risk pregnancies.
For Editors’ Commentary, see Contents
Proposed mechanisms underlying the potential protective effect for high obstetric volume in lower-risk births are systems factors such as staffing, medical equipment, continuous presence of onsite anesthesia, availability of subspecialists, and readiness to handle fluctuations in patient flow. Among the studies of hospital obstetric volume on neonatal outcomes in lower-risk deliveries, most have been conducted outside the United States, mostly in Europe and Australia. Neonatal mortality is commonly analyzed as a marker of quality in obstetric/perinatal care. Additionally, birth asphyxia and intrapartum fetal death are also frequently used as indicators of quality of obstetric care, and some suggest that these outcomes may be sensitive markers of quality of obstetric care.
The effects of hospital volume and regionalization of obstetric care are complicated by geographical and socioeconomic factors, including variations in patient mix and the urban/rural character of a given region. When evaluating the ability of different-sized maternity units to provide high-quality care, we often make the assumption that patients could conceivably be referred to an alternative hospital with maternity services. In rural and frontier regions, that assumption may not hold.
In this paper, we analyze the role of obstetric volume in perinatal outcomes in California. We analyzed this association in the overall population of births, and in a lower-risk subpopulation of term births with birthweight >2500 g, to assess the impact of volume without the factors of prematurity and growth restriction, which may drive rates of some adverse outcomes. We studied neonatal mortality and birth asphyxia as primary outcomes, and considered the potential confounding roles of patient mix, academic hospital affiliation, and hospital geography (rural vs nonrural). We hypothesized that lower-volume hospitals would be characterized by higher rates of asphyxia. Because the rural setting is highly correlated with obstetric volume and mutually exclusive with academic affiliation in these data, we analyzed the role of obstetric volume in California’s rural hospitals separately, testing the hypothesis that the effect of obstetric volume on perinatal outcomes may differ between rural and nonrural locations.
Materials and Methods
This study employed a retrospective cohort design, analyzing linked birth/infant death certificates with hospital discharge diagnoses for births occurring in California in 2006. Data linkage of California Patient Discharge Data, Vital Statistics Birth Certificate Data, and Vital Statistics Death Certificate Data was conducted by the state Office of Statewide Health Planning and Development (OSHPD) Healthcare Information Resource Center, under the California Health and Human Services Agency. The linked dataset includes health information from maternal records for antepartum hospital admissions for the 9 months prior to delivery and postpartum admissions up to 1 year postdelivery. Also included are birth records and records for all infant admission and diagnoses in the first year of life. This linked dataset does not include information on outpatient visits. The record linkage number, a unique, encrypted alphanumeric code specific to each mother/baby pair, was employed to link records for mother and baby. The reporting of births and deaths in California is nearly 100% comprehensive, and California Health and Human Services Agency personnel code the data according to uniform specifications, perform rigorous quality checks, and review the birth cohort file before release. Human subjects approval was obtained from the institutional review board at Oregon Health and Science University; the Committee on Human Research at the University of California, San Francisco; and the California OSHPD Committee for the Protection of Human Subjects. Because the linked data set did not contain potential patient privacy and identification information, informed consent was exempted.
Births were linked to hospital of delivery in the dataset by a unique hospital code; births missing this code were excluded from analysis. Maternity hospitals were divided into 4 categories on the basis of obstetric volume, defined as the total number of deliveries occurring in the hospital during 2006. To minimize the incorporation of births at unintended locations such as emergency rooms or hospitals without designated labor and delivery units, hospitals with <50 deliveries in 2006 were excluded from analysis. The category cutoffs were selected to divide the hospitals into strata of varying obstetric volume for analysis, while maintaining a sufficient number of hospitals in each group. The categories were labeled numerically, increasing with volume. The lowest-volume category (category 1) included hospitals with up to 1200 deliveries in 2006; these hospitals had a monthly average of ≤100 deliveries. The category cutoffs preceded at intervals of 1200 deliveries: category 2 included smaller-to-intermediate facilities with between 1200-2399 deliveries; category 3 hospitals had between 2400-3599 deliveries; and the high-volume category (4) was made up of hospitals with ≥3600 deliveries in 2006.
Since prior research has demonstrated that obstetric practice differs between academic and community medical centers, and between rural and urban regions, we also stratified our analysis by teaching hospital status and geographic setting to explore institutional-level factors that might be associated with obstetric volume and also affect obstetric care. Maternity hospitals were designated as teaching hospitals if they had an obstetrics-gynecology residency program or had obstetric rotations for obstetrics-gynecology residents. The geographic distinction of interest was rural/nonrural, because gradations of urbanization/suburbanization within metropolitan regions have less bearing on access to multiple maternity hospitals. Rural regions of the state are served by fewer labor and delivery units located in expansive and sparsely populated regions, so regionalization of births occurring in these hospitals is less feasible, and standards of volume likely differ in rural regions. There is no universally agreed-upon definition of “rural,” so we employed a system relying on multiple sources, designating maternity hospitals as rural if they met one of the following criteria: hospitals designated as rural by the California OSHPD, hospitals in towns with a California Association of Rural Health Clinics member clinic, and hospitals located in rural ZIP codes according to the Rural-Urban Commuting Area-2 codes 4-10. After preliminary analysis indicated that rural hospitals should be analyzed separately, we devised 3 obstetric volume categories for rural hospitals, dividing the hospitals approximately into tertiles by volume: 50-599 deliveries (category R1), 600-1699 deliveries (R2), and ≥1700 deliveries (R3).
We examined the frequency of neonatal death (death in the first 28 days of life) and neonatal asphyxia among live births within obstetric volume categories, separately for rural and nonrural hospitals. Cases of neonatal asphyxia were identified using the International Classification of Diseases, Ninth Revision codes 768.5, 768.6, 768.7, and 768.9. In addition to overall rates of neonatal mortality and asphyxia, we calculated rates among the lower-risk population of births at full-term gestation (37-42 weeks) that were not low birthweight (>2500 g), because low birthweight and preterm birth are strongly predictive of neonatal death and are not equally distributed among high- and low-volume hospitals.
To adjust for patient mix and hospital characteristics among the lower-risk subpopulation, we employed multivariable logistic regression to calculate the odds of asphyxia associated with medium- and lower-volume maternity units. Regression models were run stratified by rural geography. Individual characteristics analyzed to account for patient mix were race/ethnicity, education (binary, ≥12 years or <12 years), and advanced maternal age (>35 years old). Teaching hospital status was controlled for in the nonrural analysis. Because of the nonindependence of outcomes within hospitals, the logistic regression accounted for clustering at the hospital level and calculated robust SE. All analyses excluded congenital anomalies as determined by diagnosis codes on the birth certificate and the infant’s medical record ( International Classification of Diseases, Ninth Revision codes 740-759.9). Analyses were conducted using Stata (version 12; StataCorp, College Station, TX) and R (version 2.13.1; R Foundation for Statistical Computing, Vienna, Austria).
Results
This study included a total of 268 hospitals performing at least 50 deliveries in 2006, for a total of 527,617 births. There were more hospitals in the lowest-volume category, category 1 ( Figure 1 ). The intermediate-volume categories included fewer hospitals but more deliveries, while category 4 included a relatively small number of hospitals delivering up to 7900 babies in 2006.
Institutional characteristics of the hospitals varied by hospital volume ( Table 1 ). Rural geography was highly correlated with low volume; almost half of the lowest-volume hospitals were rural, while none of the highest-volume hospitals were rural. Conversely, the proportion of teaching hospitals increased across volume categories. There was no overlap between rural hospitals and teaching hospitals; for these methodological reasons and the aforementioned practical considerations, we present the remainder of the results stratified by geography, nonrural (ie, urban and suburban) vs rural. The urban coastal regions of California had no rural hospitals, while the northern and eastern extremes of the state had only rural hospitals, and the central regions were characterized by a mixture of the two ( Figure 2 ).
| Hospital volume category (deliveries/year) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |||||||
| Overall (n = 268 hospitals) | 50-1199 (n = 98 hospitals) | 1200-2399 (n = 84 hospitals) | 2400-3599 (n = 55 hospitals) | ≥3600 (n = 31 hospitals) | ||||||
| Characteristic | n | % | n | % | n | % | n | % | n | % |
| Rural | 57 | 21 | 48 | 49 | 6 | 7 | 3 | 5 | 0 | 0 a |
| Teaching hospitals b | 26 | 10 | 2 | 2 | 6 | 7 | 9 | 16 | 9 | 29 a |
a P < .001 on Fisher exact test;
b No overlap between rural hospitals and teaching hospitals.
Demographic and clinical characteristics of the patient populations differed by hospital obstetric volume and by geography ( Table 2 ). For the nonrural hospitals, prevalence of preterm birth and low birthweight increased with increasing hospital volume. Category 3 and 4 hospitals had a patient mix comprising fewer white patients, as compared to hospitals with lower volume. In rural hospitals, middle- and higher-volume hospitals had a majority of Hispanic patients with lower educational attainment as compared to patients at the smallest rural hospitals, which had a majority of white patients.
| Nonrural | Rural | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Overall (N = 488,622 births; n = 211 hospitals) | Hospital volume (deliveries/year) | Overall (N = 38,995 births; n = 57 hospitals) | Hospital volume (deliveries/year) | ||||||
| Demographic | 1 50-1199 (N = 36,038; n = 50) | 2 1200-2399 (N = 139,548; n = 78) | 3 2400-3599 (N = 155,883; n = 52) | 4 ≥3600 (N = 157,153; n = 31) | R1 50-599 (N = 11,818; n = 36) | R2 600-1699 (N = 14,941; n = 16) | R3 ≥1700 (N = 12,236; n = 5) | ||
| LBW | 7.3 | 5.6 | 6.6 | 7.4 | 8.2 | 5.3 | 5.0 | 5.3 | 5.6 |
| PTB | 11.1 | 8.7 | 9.9 | 11.5 | 12.4 | 10.2 | 9.0 | 10.0 | 11.7 |
| Singleton birth | 96.7 | 97.9 | 97.2 | 96.6 | 96.2 | 98.1 | 98.1 | 97.8 | 98.4 |
| Nulliparous | 39.5 | 38.4 | 39.9 | 39.2 | 39.7 | 35.7 | 39.5 | 34.5 | 33.5 |
| Advanced maternal age | 18.2 | 18.9 | 18.1 | 17.2 | 19.2 | 10.4 | 11.1 | 10.5 | 9.7 |
| Prior cesarean | 15.0 | 14.9 | 14.3 | 14.8 | 15.7 | 15.1 | 12.4 | 17.4 | 14.9 |
| Education ≥12 y | 47.4 | 47.0 | 45.9 | 48.4 | 48.0 | 30.6 | 37.5 | 31.8 | 22.6 |
| Race/ethnicity | |||||||||
| White | 32.9 | 39.1 | 35.2 | 31.9 | 30.3 | 39.4 | 63.0 | 31.5 | 26.3 |
| Black | 5.5 | 4.8 | 4.6 | 5.9 | 6.2 | 2.6 | 2.6 | 1.9 | 3.6 |
| Hispanic | 46.5 | 42.2 | 46.9 | 46.3 | 47.4 | 51.9 | 25.5 | 62.0 | 64.9 |
| Asian American | 12.4 | 10.9 | 10.6 | 13.2 | 13.5 | 2.5 | 2.9 | 1.8 | 3.0 |
| Other | 2.7 | 3.0 | 2.7 | 2.7 | 2.6 | 3.6 | 6.0 | 2.8 | 2.2 |
Table 3 presents unadjusted prevalence of asphyxia and neonatal death per 10,000 nonanomalous live births, for all births and restricted to term births with birthweight >2500 g. Asphyxia decreased with increasing hospital volume among all births, from a high of 20/10,000 live births in category 1 to 11/10,000 in category 4 ( P < .001). When restricting to the lower-risk subpopulation, the trend was in the same direction and the differences remained significant, decreasing from 18/10,000 live births at lower-volume hospitals to 9/10,000 in category 4 hospitals. There appeared to be an increased rate of neonatal death ( P < .05) in medium- and higher-volume hospitals as compared to category 1, but the difference was not apparent when restricting to term births with birthweight >2500 g, where the risk was universally low (2-3/10,000 live births, P = .376).
