Variation in guideline-based prenatal care in a commercially insured population

Who is your prenatal care provider? An algorithm to identify the predominant prenatal care provider with claims data

BACKGROUND

Using claims data to identify a predominant prenatal care (PNC) provider is not always straightforward, but it is essential for assessing access, cost, and outcomes. Previous algorithms applied plurality (providing the most visits) and majority (providing majority of visits) to identify the predominant provider in primary care setting, but they lacked visit sequence information. This study proposes an algorithm that includes both PNC frequency and sequence information to identify the predominant provider and estimates the percentage of identified predominant providers. Additionally, differences in travel distances to the predominant and nearest provider are compared.

METHODS

The dataset used for this study consisted of 108,441 live births and 2,155,076 associated South Carolina Medicaid claims from 2015-2018. Analysis focused on patients who were continuously enrolled throughout their pregnancy and had any PNC visit, resulting in 32,609 pregnancies. PNC visits were identified with diagnosis and procedure codes and specialty within the estimated gestational age. To classify PNC providers, seven subgroups were created based on PNC frequency and sequence information. The algorithm was developed by considering both the frequency and sequence information. Percentage of identified predominant providers was reported. Chi-square tests were conducted to assess whether the probability of being identified as a predominant provider for a specific subgroup differed from that of the reference group (who provided majority of all PNC). Paired t-tests were used to examine differences in travel distance.

RESULTS

Pregnancies in the sample had an average of 7.86 PNC visits. Fewer than 30% of the sample had an exclusive provider. By applying PNC frequency information, a predominant provider can be identified for 81% of pregnancies. After adding sequential information, a predominant provider can be identified for 92% of pregnancies. Distance was significantly longer for pregnant individuals traveling to the identified predominant provider (an average of 5 miles) than to the nearest provider.

CONCLUSIONS

Inclusion of PNC sequential information in the algorithm has increased the proportion of identifiable predominant providers by 11%. Applying this algorithm reveals a longer distance for pregnant individuals travelling to their predominant provider than to the nearest provider.

Group prenatal care successes, challenges, and frameworks for scaling up: a case study in adopting health care innovations

BACKGROUND

Group prenatal care enhances quality of care, improves outcomes, and lowers costs. However, this healthcare innovation is not widely available. Using a case-study approach, our objectives were to (1) examine organizational characteristics that support implementation of Expect With Me group prenatal care and (2) identify key factors influencing adoption and sustainability.

METHODS

We studied five clinical sites implementing group prenatal care, collecting qualitative data including focus group discussions with clinicians (n = 4 focus groups, 41 clinicians), key informant interviews (n = 9), and administrative data. We utilized a comparative qualitative case-study approach to characterize clinical sites and explain organizational traits that fostered implementation success. We characterized adopting and non-adopting (unable to sustain group prenatal care) sites in terms of fit for five criteria specified in the Framework for Transformational Change: (1) impetus to transform, (2) leadership commitment to quality, (3) improvement initiatives that engage staff, (4) alignment to achieve organization-wide goals, and (5) integration.

RESULTS

Two sites were classified as adopters and three as non-adopters based on duration, frequency, and consistency of group prenatal care implementation. Adopters had better fit with the five criteria for transformational change. Adopting organizations were more successful implementing group prenatal care due to alignment between organizational goals and resources, dedicated healthcare providers coordinating group care, space for group prenatal care sessions, and strong commitment from organization leadership.

CONCLUSIONS

Adopting sites were more likely to integrate group prenatal care when stakeholders achieved alignment across staff on organizational change goals, leadership buy-in, and committed institutional support and dedicated resources to sustain it.

TRIAL REGISTRATION

The Expect With Me intervention's design and hypotheses were preregistered: https://clinicaltrials.gov/study/NCT02169024 . Date: June 19, 2014.

Variation in Preterm Birth Rates Across Prenatal Care Sites in New York

OBJECTIVE

To investigate variation in preterm birth rates by the site at which prenatal care was received.

DESIGN

Cross-sectional cohort study.

SETTING

New York State.

PARTICIPANTS

Claims and encounter data on singleton live births that were covered by New York Medicaid (N = 154,377).

METHODS

We analyzed data from New York Medicaid and the American Community Survey. We established sites of prenatal care using geocoded billing addresses for prenatal visits. We calculated descriptive statistics and conducted logistic regression analyses to determine variation in crude and risk-adjusted preterm birth rates by prenatal care site.

RESULTS

The crude preterm birth rates averaged 7.8% (range = 2.0%-18.7%) by prenatal care site. The adjusted preterm birth rate was 8.0% (range = 2.8%-18.5%) by prenatal care site. Risk-adjusted preterm birth site-level rates at the 90th percentile were 2.7 times higher than those in the 10th percentile. The variation in risk-adjusted preterm birth site-level rates was not fully explained by birth volume, rural site location, or racial and ethnic composition of the patients who received prenatal care at the site.

CONCLUSION

Wide variation in risk-adjusted preterm birth rates across prenatal care sites exists, and factors beyond known individual demographics and medical factors contribute to the variation. Further research is warranted to identify why receiving care at some prenatal sites is associated with higher risk of preterm birth than receiving care at others.

On the geographic access to healthcare, beyond proximity

This study examined the incongruence of travel distance between the nearest provider and the provider that pregnant woman actually chose to visit. Using a dataset of South Carolina claims including rural and urban areas for the period 2014-2018 based on live births of 27,290 pregnant women, we compared the travel distance and travel time for two providers of health: the nearest facility and the main one for the area in question. The number of the former type was counted for every case. The mean travel distance/time to the nearest provider was 3.2 miles (5.2 km) and 5.0 minutes, while that to the main (predominant) provider was 23.0 miles (37.0 km) and 31.7 minutes. Only 21.6% of pregnant women chose one of the closest facilities as their provider. The mean travel distance and time to the nearest provider for women in rural areas were more than twice that for urban women but only 1.2 times for the main provider. Rural women had one third fewer providers situated closer than the main in comparison to number available for urban women. Thus, we conclude that proximity is not the only factor associated with access to healthcare. While evaluating geographic access, the number of available health providers within the mean travel distance or time would be a better indicator of proximate access.

Home Visits With A Registered Nurse Did Not Affect Prenatal Care In A Low-Income Pregnant Population

There is an urgent need to improve maternal and neonatal health outcomes and decrease their racial disparities in the US. Prenatal nurse home visiting programs could help achieve this by increasing the use and quality of prenatal care and facilitating healthy behaviors during pregnancy. We conducted a randomized controlled trial of 5,670 Medicaid-eligible pregnant people in South Carolina to evaluate how a nurse home visiting program affected prenatal health care and health outcomes. We compared outcomes between the treatment and control groups and found little evidence of statistically significant differences in the intensity of prenatal care use, receipt of guideline-based prenatal care services, other health care use, or gestational weight gain. Nor did we find treatment effects in subgroup analyses of socially vulnerable participants (46.9 percent of the sample) or non-Hispanic Black participants (52.0 percent of the sample). Compared with the broader Medicaid population, our trial participants had more health and social risk factors, more engagement with prenatal care, and similar pregnancy outcomes. Delivering intensive nurse home visiting programs to the general Medicaid population might not be an efficient method to improve prenatal care for those who need the most support during pregnancy.

Understanding categories of postpartum care use among privately insured patients in the United States: a cluster-analytic approach

The postpartum period is critical for the health and well-being of birthing people, yet little is known about the range of health care services and supports needed during this time. Maternity care patients are often targeted for clinical interventions based on "low risk" or "high risk" designations, but dichotomized measures can be imprecise and may not reflect meaningful groups for understanding needed postpartum care. Using claims data from privately insured patients with childbirths between 2016 and 2018, this study identifies categories and predictors of postpartum care utilization, including the use of maternal care and other, nonmaternal, care (eg, respiratory, digestive). We then compare identified utilization-based categories with typical high- and low-risk designations. Among 269 992 patients, 5 categories were identified: (1) low use (55% of births); (2) moderate maternal care use, low other care use (25%); (3) moderate maternal, high other (8%); (4) high maternal, moderate other (7%); and (5) high maternal, high other (5%). Utilization-based categories were better at differentiating postpartum care use and were more consistent across patient profiles, compared with high- and low-risk dichotomies. Identifying categories of postpartum care need beyond a simple risk dichotomy is warranted and can assist in maternal health services research, policymaking, and clinical practice.

Using Modernized Medicaid Data to Advance Evidence-Based Improvements in Maternal Health

Medicaid is the primary payor for nearly half of all births in the United States and plays a disproportionate role in covering maternity care for low-income people, rural people, and minoritized racial groups. Newly available, modernized Medicaid claims data-the Transformed Medicaid Statistical Information System Analytic Files (TAF)-offer a significant opportunity to conduct novel research that can drive the development of evidence-based programs and policies for Medicaid beneficiaries before, during, and after pregnancy. Yet, the public health research community has so far underused the TAF for maternal health research. We provide an overview of the TAF and how they compare to other major data sets available to study maternal health. We highlight some major limitations of the TAF and offer strategies to maximize the potential of these novel data to accelerate timely, rigorous research to improve maternal health and health equity. (Am J Public Health. 2023;113(7):805-810. https://doi.org/10.2105/AJPH.2023.307287).

The impact of birth settings on pregnancy outcomes in the United States

In the United States, 98.3% of patients give birth in hospitals, 1.1% give birth at home, and 0.5% give birth in freestanding birth centers. This review investigated the impact of birth settings on birth outcomes in the United States. Presently, there are insufficient data to evaluate levels of maternal mortality and severe morbidity according to place of birth. Out-of-hospital births are associated with fewer interventions such as episiotomies, epidural anesthesia, operative deliveries, and cesarean deliveries. When compared with hospital births, there are increased rates of avoidable adverse perinatal outcomes in out-of-hospital births in the United States, both for those with and without risk factors. In one recent study, the neonatal mortality rates were significantly elevated for all planned home births: 13.66 per 10,000 live births (242/177,156; odds ratio, 4.19; 95% confidence interval, 3.62-4.84; P<.0001) vs 3.27 per 10,000 live births for in-hospital Certified Nurse-Midwife-attended births (745/2,280,044; odds ratio, 1). These differences increased further when patients were stratified by recognized risk factors such as breech presentation, multiple gestations, nulliparity, advanced maternal age, and postterm pregnancy. Causes of the increased perinatal morbidity and mortality include deliveries of patients with increased risks, absence of standardized criteria to exclude high-risk deliveries, and that most midwives attending out-of-hospital births in the United States do not meet the gold standard for midwifery regulation, the International Confederation of Midwives' Global Standards for Midwifery Education. As part of the informed consent process, pregnant patients interested in out-of-hospital births should be informed of its increased perinatal risks. Hospital births should be supported for all patients, especially those with increased risks.

Rural Maternal Health Care Outcomes, Drivers, and Patient Perspectives

Rural communities are a vital segment of the US population; however, these communities are shrinking, and their population is aging. Rural women experience health disparities including increased risk of maternal morbidity and mortality. In this article, we will explore these trends and their determinants both within and external to the health care system. Health care providers, public health professionals, and policymakers should be aware of these social and structural factors that influence health outcomes and take action to reduce generational cycles of health disparity. Opportunities to improve the health and pregnancy outcomes for rural women and rural populations are highlighted.

A systematic review of the qualitative literature on barriers to high-quality prenatal and postpartum care among low-income women

OBJECTIVE

To examine the qualitative literature on low-income women's perspectives on the barriers to high quality prenatal and postpartum care.

DATA SOURCES AND STUDY SETTING

We performed searches in PubMed, Web of Science, Embase, SocIndex, and CINAHL for peer-reviewed studies published between 1990 to 2021.

STUDY DESIGN

Systematic review of qualitative studies with participants who were currently pregnant or had delivered within the past two years and identified as low-income at delivery.

DATA COLLECTION / EXTRACTION METHODS

Two reviewers independently assessed studies for inclusion, evaluated study quality, and extracted information on study design and themes.

PRINCIPLE FINDINGS

We identified 34 studies that met inclusion criteria, including 23 focused on prenatal care, 6 on postpartum care, and 5 on both. The most frequently mentioned barriers to prenatal and postpartum care were structural. These included delays in gaining pregnancy-related Medicaid coverage, challenges finding providers who would accept Medicaid, lack of provider continuity, transportation and childcare hurdles, and legal system concerns. Individual-level factors, such as lack of awareness of pregnancy, denial of pregnancy, limited support, conflicting priorities, and indifference to pregnancy also interfered with timely use of prenatal and postpartum care. For those who accessed care, experiences of dismissal, discrimination, and disrespect related to race, insurance status, age, substance use, and language were common.

CONCLUSIONS

Over a period of 30 years, qualitative studies have identified consistent structural and individual barriers to high-quality prenatal and postpartum care. Medicaid policy changes including expanding presumptive eligibility, increased reimbursement rates for pregnancy services, payment for birth doula support, and extension of postpartum coverage may help overcome these challenges.