Identifying individual hospital levels of maternal care using administrative data

Factors associated with antepartum pilgrimage at a reference maternity hospital in Ceará

OBJECTIVE

To identify factors associated with antepartum pilgrimage in pregnant women in Fortaleza, Ceará, Brazil.

METHOD

A cross-sectional study with 300 postpartum women from a state reference maternity hospital, carried out from March 2020 to January 2021. The frequency of pilgrimage was estimated according to socioeconomic characteristics and prenatal care. Analysis with Pearson's chi-square test selected variables for adjusted Poisson regression.

RESULTS

The frequency of antepartum pilgrimage to more than one health service was 34.3%. Not knowing the reference maternity hospital (1.16; 95%CI: 1.04-1.30) and not living close to the reference maternity hospital (1.16; 95%CI: 1.03-1.31) were associated with the occurrence of pilgrimage among women. Personal characteristics and prenatal care were not associated.

CONCLUSION

There was an association between antepartum pilgrimage and lack of knowledge of the reference maternity hospital and residence far from that maternity hospital, which requires better team communication and the guarantee of easier access to obstetric care services, through effective implementation of regionalization of maternal care.

Validation of a measure of hospital maternal level of care for the United States

BACKGROUND

Lack of a validated assessment of maternal risk-appropriate care for use in population data has prevented the existing literature from quantifying the benefit of maternal risk-appropriate care. The objective of this study was to develop a measure of hospital maternal levels of care based on the resources available at the hospital, using existing data available to researchers.

METHODS

This was a secondary data analysis. The sample was abstracted from the American Hospital Association Annual Survey Database for 2018. Eligibility was limited to short-term acute general hospitals that reported providing maternity services as measured by hospital reporting of an obstetric service level, obstetric services, or birthing rooms. We aligned variables in the database with the ACOG criteria for each maternal level of care, then built models that used the variables to measure the maternal level of care. In each iteration, the distribution of hospitals was compared to the distribution in the CDC Levels of Care Assessment Tool Validation Pilot, assessing agreement with the Wilson Score for proportions for each level of care. Results were compared to hospital self-report in the database and measurement reported with another published method.

RESULTS

The sample included 2,351 hospitals. AHA variables were available to measure resources that align with ACOG Levels 1, 2, and 3. Overall, 1219 (51.9%) of hospitals reported resources aligned with Maternal Level One, 816 (34.7%) aligned with maternal level two, and 202 (8.6%) aligned with maternal level Three. This method overestimates the prevalence of hospitals with maternal level one compared to the CDC measurement of 36.1% (Mean 52.9%; 95% CI47.2%-58.7%), and likely includes hospitals that would not qualify as level one if all resources required by the ACOG guidelines could be assessed. This method underestimates the prevalence of hospitals with maternal critical care services (Level 3 or 4) compared to CDC measure of 12.1% (Mean 8.1%; 95%CI 6.2% - 10.0%) but is an improvement over hospital self-report (24.7%) and a prior published method (32.3%).

CONCLUSIONS

This method of measuring maternal level of care allows researchers to investigate the value of perinatal regionalization, risk-appropriate care, and hospital differences among the three levels of care. This study identified potential changes to the American Hospital Association Annual Survey that would improve identification of maternal levels of care for research.

Perinatal outcomes for rural obstetric patients and neonates in rural-located and metropolitan-located hospitals

OBJECTIVE

To compare rural obstetric patient and neonate characteristics and outcomes by birth location.

METHODS

Retrospective observational cohort study of rural residents' hospital births from California, Pennsylvania, and South Carolina. Hospitals in rural counties were rural-located, those in metropolitan counties with ≥10% of obstetric patients from rural communities were rural-serving, metropolitan-located, others were non-rural-serving, metropolitan-located. Any adverse obstetric patient or neonatal outcomes were assessed with logistic regression accounting for patient characteristics, state, year, and hospital.

RESULTS

Of 466,896 rural patient births, 64.3% occurred in rural-located, 22.5% in rural-serving, metropolitan-located, and 13.1% in non-rural-serving, metropolitan-located hospitals. The odds of any adverse outcome increased in rural-serving (aOR 1.27, 95% CI 1.10-1.46) and non-rural-serving (aOR 1.35, 95% CI 1.18-1.55) metropolitan-located hospitals.

CONCLUSION

One-third of rural obstetric patients received care in metropolitan-located hospitals. These patients have higher comorbidity rates and higher odds of adverse outcomes likely reflecting referral for higher baseline illness severity.

Patients in Iowa Counties Lacking Hospitals With Labor and Delivery Services Disproportionately Receive Care at Level III Maternal Care Hospitals When Undergoing Cesarean Delivery: A Retrospective Longitudinal Study

Introduction Many obstetrical patients from rural areas in the United States lack hospitals that provide labor and delivery care. Our objective was to examine the effects of such patients on caseloads of cesarean deliveries at Iowa hospitals with level III maternal care, as defined by the Iowa Department of Public Health (e.g., with obstetric anesthesiologists). Methods This retrospective longitudinal study included every discharge with cesarean delivery in the state of Iowa from October 2015 through June 2021. There were N=60,534 such deliveries from 76 hospitals, of which three were level III, and the rest were level I or II. Poisson regression models with robust variance estimation and controlling for geography, maternal risk factors, and insurance, were used to evaluate the binary outcome of whether patients received care at the university level III hospital in Eastern Iowa, or not. Similar models were also developed for care at the two private level III hospitals in Central Iowa, or not. Differences in the mean probabilities of receiving care at the level III hospitals were then estimated using logistic regression, with results reported in units of changes in cases per week at the hospitals. Results Statewide, the university level III hospital performed 7.4% of the cesarean deliveries, and the two private level III hospitals performed 23.4%. Patients from counties in which no cesarean deliveries were performed during the quarter of the year when they underwent a cesarean delivery disproportionately received care at level III hospitals versus levels I and II hospitals. Lower 99% confidence limits for incremental risk ratios were 1.46 and 4.20, respectively. Cesarean deliveries among patients residing in counties where no hospital had a labor and delivery ward were distributed unequally between the counties of the hospitals with level III maternal care. There were approximately 1.09 (standard error 0.10) extra cesarean deliveries per week at the university hospital versus 5.81 (standard error 0.11) at the private hospitals. The 1.09 vs 5.81 difference was caused, in part, by the effects of insurance and other hospitals with similar services. Conclusions Patients residing in counties without labor and delivery care disproportionately go to level III hospitals. These results can help anesthesiologists, obstetricians, and analysts at hospitals with large tertiary (level III) programs interpret their annual increases in total obstetric anesthesia activity.

Busy day effect on the use of obstetrical interventions and epidural analgesia during labour: a cross-sectional register study of 601 247 deliveries

Background

Daily delivery volume might affect the quality of obstetric care. We explored the busy day effect on selected obstetrical interventions and epidural analgesia performed during labour in different sized delivery hospitals and on the Finnish obstetric ecosystem.

Methods

We conducted a cross-sectional study on Finnish Medical Birth Register data of singleton pregnancies (N = 601,247) from 26 delivery hospitals from 2006 to 2016. Delivery hospitals were stratified by annual delivery volume: C (category) 1: < 1000, C2: 1000–1999, C3: 2000–2999, C4: ≥3000, and C5: university hospitals. The exposure variables were defined as quiet, optimal, and busy days determined based on daily delivery volume distribution in each hospital category. Quiet and busy days included approximately 10% of the lowest and highest delivery volume days, while the rest were defined as optimal. Outcome measures were unplanned caesarean section (CS), instrumental delivery, induction of labour, and epidural analgesia. We compared the incidence of outcomes in quiet vs. optimal, busy vs. optimal, and busy vs. quiet days using logistic regression. The statistical significance level was set at 99% to reduce the likelihood of significant spurious findings.

Results

In the total population, the incidence of instrumental delivery was 8% (99% CI 2–15%) lower on quiet than on optimal days. In smaller hospitals (C1 and C2), unplanned caesarean sections were performed up to one-third less frequently on busy than optimal and quiet days. More (27%, 99% CI 12–44%) instrumental deliveries were performed in higher delivery volume hospitals (C4) on busy than quiet days. In C1-C3, deliveries were induced (12–35%) less often and in C5 (37%, 99% CI 28–45%) more often on busy than optimal delivery days. More (59–61%) epidural analgesia was performed on busy than optimal and quiet days in C4 and 8% less in C2 hospitals.

Conclusions

Pooled analysis showed that busyness had no effect on outcomes at the obstetric ecosystem level, but 10% fewer instrumental deliveries were performed in quiet than on busy days overall. Furthermore, dissecting the data shows that small hospitals perform less, and large non-tertiary hospitals perform more interventions during busy days.