Infant mortality rates are used as an indicator for the health of a community. To prevent infant deaths, mothers need to be healthy, live in a safe environment, and have access to quality care. Reducing low birth weight (LBW) and premature births has been identified as a key strategy to decrease infant mortality [1]. While infant mortality rates in the US have improved over the past decades, they have been stagnant in Ohio. In fact, Ohio ranked second worst for black infant mortality among all states, and fourth worst for overall infant mortality in 2010 [2, 3]. Nationally, despite overall improvements, the 2011 Centers for Disease Control (CDC) Health Disparities and Inequalities Report showed that large disparities in infant mortality rates persist [4].

Strategies that incorporate the community and directly reach out to women at greatest risk for poor birth outcomes may help communities move towards health equality. Home visiting services are one strategy used to improve birth outcomes and have received increased attention and focus on providing evidence-based services to vulnerable children and families through the Affordable Care Act and the Maternal, Infant, and Early Childhood Home Visiting (MIECHV) program [5]. Although home visiting has been shown to be effective in impacting parent behaviors, child cognitive outcomes and maternal life course, the impact on birth outcomes is not as clearly evident [6, 7].

The Community Health Access Project (CHAP) is a nonprofit, community based organization that has been providing care coordination services in Richland County, Ohio since 1999. CHAP utilizes community health workers (CHWs) to identify women at risk of having poor birth outcomes, connect them to health and social services, and track each identified issue to a measurable completion. CHAP’s intensive home visiting model uses an accountability tool called Pathways [8, 9]. A Pathway addresses clearly defined actions towards problem resolution and is not considered complete until a measurable outcome is achieved. One participant may be assigned to many different Pathways depending on the problems identified during the initial interview and subsequent home visits [10]. As in most communities, Richland County had geographic areas of health inequality. CHAP used a mapping strategy to determine the census tracts where the unfavorable birth outcomes were disproportionately occurring. The infant mortality rates in Richland County from 2001 to 2005 were 6.7 infant deaths per 1,000 live births for white women, and 17.3 for African-American women [2].

The impact of CHWs has been difficult to document. The Agency for Healthcare Research and Quality (AHRQ) released a report on the outcomes of CHW interventions in 2009, based on 15 different programs, which showed minimal impact on birth outcomes [11]. The CHAP model differs from those programs previously studied in that an accountability measurement tool—Pathways—was used to track each health or social issue a pregnant client faced through to a measurable completion. Additionally, contracts were developed with funders to pay for completed Pathways or outcomes [8, 9].

We evaluated if LBW would be reduced when women at risk of having a LBW infant were provided with intensive home visiting and community based care coordination by CHWs, and Pathways were used to document outcomes. The primary objective was to compare the adjusted odds of LBW between CHAP recipients and non-CHAP recipients. Secondary objectives were a comparison of adequacy of prenatal care and a cost savings evaluation.

Characteristics of CHAP participants and non-participant controls are summarized in Table 1. The CHAP and non-CHAP groups did not differ significantly (p < 0.05) in any of the propensity score variables; the groups are within 2.6 % points for all levels of all propensity score variables with the exception of age, which had a 5.2 % point difference. There were no reported cases of incompetent cervix, uterine bleeding, or renal disease in either group.Table 1

Characteristics of community health access project (CHAP) clients, all non-CHAP mothers* identified from birth certificates, and matched controls

A total of 653 Pathways were initiated for the CHAP participants, and all 115 women in this study finished a Pregnancy Pathway (7 were finished incomplete due to LBW). Including the Pregnancy Pathway, CHAP participants had an average of 5.6 Pathways tracked for health and social issues that were identified during the pregnancy and postpartum period. 102 Postpartum and Family Planning Pathways were completed for participants, confirming that 89 % of women attended their postpartum appointments and were using a family planning method. The most common non-medical Pathways initiated were Employment (52 %), Adult Education (50 %), Smoking Cessation (39 %), Food Security (30 %), and Housing (27 %). Two major barriers that were identified to completion of Pathways included transportation and limited community resources for non-medical issues.

Women enrolled in CHAP care coordination from 2001 through 2004 had significantly lower adjusted odds of experiencing a low-birth weight delivery than non-CHAP women [adjusted odds ratio = 0.36, 95 % CI (0.12, 0.96)] (Table 2). There were no significant differences between the adjusted odds of the adequacy of prenatal visits or the timing of the first prenatal visit between CHAP participants and non-CHAP mothers. This finding is different from other home visiting studies that have shown a dosage effect of prenatal home visiting in at-risk women [19, 20].Table 2

Odds ratios and 95 % confidence intervals for pre-term birth

Fifty-six percent of clients in this study entered CHAP in the first trimester of pregnancy, 20 % in the second trimester and 24 % in the third trimester. The estimated cost to provide Pathways community care coordination by CHAP in the time period studied averaged $751 per pregnant client. An estimated 10 LBW births (1 prevented per 11.5 participants) were prevented by participation in the CHAP program from 2001 through 2004 (95 % CI = 1, 17). The cost savings in the first year of life, for each dollar invested in Pathways based community care coordination was $3.36, and the long term cost savings was $5.59 for each dollar invested.

Pregnant women who participated in CHAP, a structured community-based care coordination program provided by CHWs and coupled with Pathways tracking and payment for outcomes, had a significantly lower probability of delivering a LBW infant. CHAP participants living in the targeted census tracts were at an increased risk for poor birth outcomes compared to the general population—67.8 % African-American, 25.2 % age 18 or younger, 85.2 % unmarried, and 39.1 % tobacco users. A challenge to determining the effectiveness of CHW interventions has been identifying a valid control group that effectively accounts for social determinants and their impact on outcomes [21, 22]. Use of an optimal matching algorithm using propensity scores allowed each CHAP recipient to be matched with one control and supported estimation of the number of LBW births prevented.

Areas of health inequalities—whether related to birth outcomes or chronic diseases—can be easily mapped in communities. This study demonstrates the value of identifying communities with disparately poor health outcomes and directly reaching out to individuals within those communities, engaging them through care coordination, connecting them to health and social service interventions, and measuring the results through an accountable measurement tool.

Community health workers perform their work by approaching the whole person—and take into consideration their social, environmental, psychological and health needs in order to impact health outcomes. This is evidenced by the additional Pathways initiated by CHWs in this study for issues related to food security, housing, transportation, employment, and education. These additional Pathways had to be addressed in coordination with preventive health care needs and consideration of the client’s priorities of care. Health and social service siloes exist in communities, and individuals living in poverty often face barriers in accessing these critical services. The community-based care coordinator serves an important role on the healthcare team because of their trusted relationship with the client. They are able to identify key non-medical issues and are skilled in navigating the fragmented health and social service systems.

Some social determinants of health can be addressed at the population level—such as safe drinking water, smoking in public places, elimination of food deserts and safe sidewalks—but individually addressable social determinants also represent a significant intervention opportunity. Housing, education, employment, food security, and many other critical issues can be identified and addressed with effective and accountable care coordination to improve individual progress, reduce stress, and improve health for those individuals at greatest risk.

The CHAP Pathways Model provided the measurement tool to monitor successful connections to both health and social services. Pathways were developed as the pay-for-performance model for CHAP’s contracts and were an important part of the care plan, documentation, and reporting in this study.

There were several limitations in this study. First, although data was collected over a 4-year time period, the total number of women in the CHAP intervention group was small, reflecting the size of program enrollment within the targeted census tracts over the time period studied. A larger sample size would have provided more precise estimates of odds ratios and more power to detect significant differences in all models. Second, there was no random assignment to CHAP intervention or control. Although we attempted to control for bias as much as possible through propensity score matching and covariate adjustment, some selection bias may remain. Additional evaluations, with randomized group assignments, larger numbers of participants, and in different locations are needed to replicate and confirm our findings. Third, the evaluation was limited by the vital statistics records on what cofounders and outcomes we could study. For example, prenatal smoking is potentially modifiable through CHAP with a Pathway that included specific education and support to help patients reduce or quit smoking; however smoking status by trimester was not standard documentation on the Ohio birth certificate. Future work should control for first trimester smoking status and other factors related to low birth weight. Finally, the evaluation was limited by the quality of birth certificate data, which is shown to generally be specific, but not sensitive, as a source of maternal complications [23, 24]. In contrast, birth weight data from the birth certificate has been shown to be more reliable [25].

CHAP may reduce LBW delivery among high risk women through multiple mechanisms. As there were no differences in prenatal care initiation between groups, improvement in early prenatal care does not appear to be one, and this finding is consistent with other studies [26]. However, factors besides medical care are known to impact health outcomes and models of care that address both medical and social factors show promise in reducing LBW [27–30].

This study represents our initial experience with using the Pathways Model to quantify and track care coordination provided to high risk pregnant women. Since the model’s inception, effort has been placed on refining the measurement and tracking process of the Pathways. It was not possible in this study to identify which Pathways specifically led to improved birth outcomes. Newer technology for Pathway tracking has remedied that and can support future research. CHAP participants were initially identified as being at increased risk by where they lived (identified census tracts), but now we have the capability to monitor risk throughout the care coordination period. Our preliminary study can be incorporated into the larger movement to create a national home visiting research network that works to promote the translation of research findings into policy and practice [31].

Starting from an American Academy of Pediatrics—Community Access to Child Health (CATCH) Grant in 2001—the Pathways Model was further developed to embrace multiple care coordination agencies within a service region. The Pathways Community HUB Model is designed to identify the most at-risk individuals in a community, connect them to evidence-based interventions, and measure the results [8, 10]. The HUB Model was developed and piloted by CHAP in 2004 in Richland County, Ohio based on the success of these initial findings. The model was recognized by the Agency for Healthcare Research and Quality (AHRQ) Innovations Exchange and a learning network was established to further study the model [8, 9]. The Pathways Community HUB does not directly provide care coordination services, but subcontracts with care coordination agencies serving vulnerable populations in the community. The community HUB works to coordinate and track progress for all of the agencies within a community providing care coordination. The HUB serves to register and collect focused data on each client served using common Pathways to track quality and outcomes. This model eliminates duplication of care coordination and provides standard quality measurements, allowing care coordination agencies to focus on the most vulnerable community members and strive towards improving overall health outcomes. The Kresge Foundation has recently supported an initiative to develop a standard approach for certification of communities utilizing the Pathways Community HUB Model to assure consistent quality of care coordination.

As stated by CDC, health disparities “must be addressed with intervention strategies related to both health and social programs” [1]. This study shows that structured community-based care coordination coupled with standardized and accountable tracking tools and payment for outcomes may reduce LBW delivery among high-risk pregnant women. The Pathways Model allows for targeting the diversity of needs across racial, ethnic and other sociodemographic distinctions. Identifying communities with disparately poor health outcomes and ensuring the connection of residents to health and social programs can potentially reduce persistent inequalities in health.