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. 2025 Jan 28;29(1):67–77. doi: 10.1007/s10995-024-04028-9

Center-Based Childcare Access to Health Screenings and Developmental Assessments in U.S. Children from Birth to Five

Sabrin Rizk 1,✉, Brian Barger 2
PMCID: PMC11805720  PMID: 39873936

Abstract

Objective

To examine the odds of children aged 0-5 in center-based childcare programs receiving referrals for health screenings and developmental assessments, controlling for children’s races/ethnicities and provider and program factors.

Methods

We conducted secondary analyses using the 2019 National Survey for Early Care and Education (NSECE) Center-based Provider survey. We used multivariate logistic regression models to estimate referral odds for health screenings and developmental assessments from centers without these services onsite. We adjusted for provider (e.g., language spoken when working with children) and program factors (e.g., staff mentorship, regulatory agency visits, and the teacher-to-child ratio).

Results

The sample included U.S. center-based childcare providers (n = 1,306) whose programs did not offer onsite health screenings or developmental assessments. The findings suggest that programs providing staff mentorship (OR = 2.15, 95% CI [1.36–3.41], P =.001) and regulatory oversight (OR = 1.85, CI [1.13 = 3.02], P =.014) had greater odds of making referrals for children under 5 years old. After adjusting for various provider and program factors, Hispanic children had lesser odds of being referred compared to other racial groups (OR = 0.99, 95% CI [0.98–0.99], P =.030).

Conclusions

Mentorship and regulatory oversight in center-based childcare programs were associated with greater odds of referral for health screenings and developmental assessments for children under five years old. Mentoring and regulatory oversight may facilitate the provision of timely referrals for screenings and assessments for children and their families in center-based childcare programs.

Keywords: Medical home, Early child development, Day care health and safety, Preschool education, Developmental delay and disabilities

Developmental disabilities are diagnosed in 16.7% of U.S. children, with prevalence increasing among those aged 3 to 17, reaching 8.56% in 2021 (Zablotsky et al., 2023). Inadequate screening and assessment often mean many children with developmental delays go undetected until age five, delaying early intervention (EI) (Centers for Disease Control and Prevention (CDC), 2024). Despite the shift in Autism Spectrum Disorder (ASD) prevalence, data from the Autism and Developmental Monitoring (ADDM) Network reported that Black, non-Hispanic children with ASD remained at higher risk for co-occurring intellectual disability, with 50.8% having an intellectual impairment. This was in comparison to White, non-Hispanic, Asian, and mixed race children with ASD among the 11 surveillance states (Maenner et al., 2023). The narrowing racial/ethnic disparity in ASD prevalence suggests progress in early ASD identification over time.The narrowing racial and ethnic gap in ASD prevalence implies improvements in the timing of ASD detection (CDC, 2023a, b).

The American Academy of Pediatrics (AAP) advises regular developmental screening from birth to age five in the medical home (AAP, 2002). While around 76% of primary care providers (PCPs) reported conducting screenings, only about 12% used a standardized screening tool (Tumaini et al., 2024). PCPs faced several challenges when itthe came to screening, including inadequate reimbursement for screening and interventions and parental hesitation to discuss their circumstances. PCPs were also uncertain about their role in screening and lacked tools integrated into their electronic record workflow. Doubts about the effectiveness of the available screening tools were common. Finding time to conduct screenings amidst other responsibilities was another hurdle. Furthermore, the limited evidence base on what works best in these screenings posed a challenge (Lipkin et al., 2020b; Coker et al., 2024). Variations in PCP referral practices can result in uneven detection rates. Research by Wallis et al. (2021, 2023) showed that among children with a positive developmental screen, 17.5% were already referred to EI, 39.9% received a referral during the visit, and 42.5% had not been referred. Before a positive screen, EI referrals were more common among males, older children, and White, non-Hispanics. New EI referrals were more likely among Black, non-Hispanic, male children from lower-income families. A later study found that Asian, Black, non-Hispanic, and publicly insured children were less likely to schedule and complete referrals. The referral process was slower for publicly insured Black, non-Hispanic children who spoke a language other than English (Srinivasan et al., 2023).

Leveraging Center-Based Childcare for Early Identification

The U.S. early care and education system (ECE), including center-based childcare, Early Head Start/Head Start, and preschool, plays a vital role in connecting families with essential health screenings and developmental assessments for young children (Administration for Children & Families, n.d.). In 2019, over half of children aged 5 and younger were in non-parental care at least weekly, with 62% of those in center-based programs highlighting the importance of these programs in facilitating access to health services (Cui & Natzke, 2021). The National Association for the Education of Young Children advocates for developmental screenings for children under five, and childcare providers play a critical role in early detection of developmental disabilities. ECE programs also focus on establishing healthy habits like nutrition, physical activity, and hygiene to promote healthier outcomes for children and families (Donoghue et al., 2017).

The medical home can utilize early childhood programs to link low-income families with beneficial learning opportunities. Integrating health screenings into these programs enables quick identification of potential issues, facilitating timely interventions and promoting healthy habits from an early age. This approach supports pediatric health systems’ goals of early detection and intervention (Grant et al., 2019). Hearing screenings are a prime example of the power of early detection, identifying previously undetected hearing loss in children.While some states mandate school-based screenings, this can be a burden on low-income districts. Preschool programs offer an opportunity for early screening and support of deaf and hard-of-hearing children. Teachers often first notice speech, language, and hearing issues, triggering further evaluations and timely diagnoses to ensure children receive necessary interventions. Preschool hearing screenings can reveal how hearing loss may impact a child’s education, facilitate discussions on customized education plans, and reduce the stress of additional healthcare appointments for parents (Brodie et al., 2022).

This study aims to explore how provider and program factors, including children’s races/ethnicities, affect the likelihood of referrals for health screenings and developmental assessments within center-based childcare settings. By identifying the factors that influence referral practices, we can improve child outcomes and the complex factors involved in access to screenings, assessments, and services.

Method

Data Source

We conducted secondary analyses using the 2019 National Survey of Early Care and Education (NSECE), a cross-sectional, nationwide survey supported by the Office of Planning, Research, and Evaluation (OPRE) within the Administration of Children and Families (ACF). The University of Chicago’s National Opinion Research Organization (NORC) carries out the survey for the U.S. Department of Health and Human Services. The NSECE team conducted the center-based childcare provider survey among representative classrooms from January to July 2019. The NSECE examines both provider and program-level factors that are closely associated with childcare quality. The data used in this study came from the 2019 NSECE center-based child provider dataset (NORC, 2021a, b).

Sample

In 2019, the NSECE conducted a survey involving classroom staff including lead teachers, teachers, assistants, and aides (n = 1,306). The survey explored their teaching methods, work environment, qualifications, and other professional responsibilities as center-based providers. Data were collected either through an online survey or an interviewer-led phone or in-person survey (NORC, 2021a, b).

Dependent Variable

The dependent variable was whether center-based programs helped families get referrals for off-site services (i.e., health screenings and developmental assessments) on-site and/or paid for or referred children and families to services, with response options of Yes or No. Health screenings encompassed medical, dental, vision, hearing, and speech screening, while developmental assessments involved tracking children’s physical, emotional, or social development. We created a combined measure for referrals for off-site health screenings and developmental assessments using the survey question: “Does your program provide referrals to this service?” (NORC, 2021a, b). Only center-based programs with positive and valid responses to making referrals for these off-site services were included in the analyses (see Fig. 1).

Fig. 1.

Fig. 1

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2019 NSECE center-based provider question stem

Independent Variable

The NSECE uses percentages to depict the demographic makeup of children within various subgroups. Children are categorized into one of four racial/ethnic groups: White non-Hispanic, Black non-Hispanic, Asian, and Other (i.e., mixed race or belonging to multiple racial/ethnic groups).

Covariates

The Andersen’s Behavioral Model of Health Services Use (BMSHU) (Andersen et al., 2014) provides a framework for understanding the various factors impacting individuals’ use of health services. We aim to enhance its predictive utility to examine the factors associated with the odds of getting referrals for screenings and assessments in center-based childcare programs. This expanded functionality represents a significant step towards the early identification of potential health or developmental concerns in children under 5 years old. This not only expedites the referral process but also improves the likelihood of successful outcomes by ensuring timely access to evaluation and services.

The Andersen (BMSHU) is a health service use framework that groups determinants of health service use into three categories: predisposing, enabling, and need factors. Predisposing factors affect the probability of using services and can include demographic attributes such as age, gender, and race, and social structure variables like education, occupation, and social relationships. Enabling factors can either facilitate or hinder the use of services. Personal resources like income and health insurance, or community resources like the availability and accessibility of health facilities, fall under this category. Need factors are related to an individual’s actual health status. The use of services is determined based on the health and functional issues that require them (von Lengerke et al., 2014).

Predisposing Factors

We considered the children’s race/ethnicity and the language used by the center-based child care providers when interacting with them (English, Spanish, Other, or combination). This information offers significant insights into the linguistic environment of children’s care.

Enabling Factors

Staff composition, including the number of lead teachers, teachers, assistant teachers, aides, and program specialists, were identified as facilitators. Maintaining appropriate staff-to-child ratios is vital for proper supervision and encouraging children’s development. We also included center-based programs that reported they provide staff mentoring, coaching, or consulting services and those that partner with other schools for extra resources and professional development opportunities, as enabling factors.

Need Factors

Quality Rating and Improvement Systems (QRIS) assess center-based programs’ adherence to quality care standards (Office of Child care, n.d.a, b). QRIS are used in over 75% of states to measure childcare program quality. Funding shortages, staff deficits, and inconsistent regulation contribute to low-quality early childhood education. Strategies like evidence-based standards, state quality rating systems, and enhanced regulations have been implemented to improve quality. Class size is crucial for identifying children needing extra support (Branson & Bingham, 2017). Smaller class sizes are linked to improved early literacy in preschool children (Francis & Barnett, 2019). The number of children in a program with physical conditions can be used to assess their developmental status and suggest referrals. Referrals can also be limited by center-based programs that deny care to children based on behavioral issues reported by center-based providers in the past three months. Additionally, center-based programs can limit referrals if behavioral issues reported to centers in the last three months prevent a child from receiving care.

Analyses

We used bivariate methods to examine potential associations between health screening and developmental assessment referrals in center-based child care programs, children’s races/ethnicities, and provider and program characteristics. Factors found significant in bivariate analyses were then included in multivariate analyses. Results are presented as percentages with a 95% confidence interval (CI). We calculated averages from percentages for the four different racial/ethnic groups, class size, and children with physical conditions, along with a 95% CI (see Table 1). Finally, we conducted multivariate analyses to obtain adjusted odds ratios (ORs), 95% CIs, and P < .05. Stata 17 (StataCorp, 2017) was used to handle the complexity of the NSECE survey design for analysis.

Table 1.

Characteristics of center-based programs working with children aged 0–5, not yet in kindergarten by referrals provided (n = 1,306)

Estimate (%) 95% CI
LL UL
Predisposing factors
Child race/ethnicity (Independent variable)
 White, Non-Hispanic 55.2 50.2 60.1
 Black, Non-Hispanic 24.5 19.9 29.1
 Hispanic 0.69 0.62 0.75
 Asian 3.8 2.4 5.3
 Other 9.9 7.6 12.2
Language spoken by center-based providers
 English only 68.2 62.7 73.3
 English, Spanish, Other or combination 31.8 26.7 37.3
Enabling factors
 Teachers/lead teachers in program 83.4 a 79.9 86.9
 Aides/assistant teachers in program 3.8 a 3.35 4.20
 Specialists 9.6 a 6.8 12.4
Provides staff with mentors/coaches/consultants
 No 57.9 52.3 63.4
 Yes 42.1 36.6 47.7
Relationships-other schools for resources/pro-dev
 No 50.3 45.3 55.4
 Yes 49.7 44.7 54.7
Need factors
Class size 10.8 a 10.0 11.7
Refused care-behavioral problems in the last 3 months
 No 83.1 79.7 86.1
 Yes 16.9 13.9 20.3
Children with physical condition 1.8 1.26 2.26
Visit reg agency: non-health/safety qual monitoring
 No 20.0 16.5 24.0
 Yes 80.0 76.0 83.5
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Note.a Mean, number; CI = confidence interval; LL = lower limit; UL = upper limit

Results

Sample Demographic Characteristics

Approximately 70% of center-based child care providers spoke English with children, and 83.4% had multiple lead teachers, showing robust educational support. About 58% had a mentorship or consultative support system, promoting ongoing development. Over half (50.3%) had ties with other schools for additional resources and professional development. The average class size was 10–11 students, with 2% having physical conditions. Many programs accommodated versus refusing care to children with behavioral issues (83.1%). In the past year, 80% underwent quality monitoring inspections unrelated to safety issues (see Table 1).

Bivariate Analyses

English-speaking providers had a higher referral rate (68.1%) than those speaking Spanish or multiple languages (31.9%). Significant differences were observed in the provision of mentors or consultants among different center-based child care programs. Many programs partnered with other schools for resource sharing and professional development. Some underwent quality checks by regulatory agencies beyond health and safety inspections. Initiatives involving mentors, coaches, and consultants (52.1%), collaborations with other schools (55.3%), and center-based programs subject to quality oversight (84.4%) were more likely to recommend health screenings and developmental assessments. Programs that refused care due to children’s behavioral issues had lower referral rates (15.3%). Child care centers that received quality-specific regulatory agency visits, not related to health or safety, were significantly more likely to provide referrals than those centers that did not undergo such visits (See Table 2).

Table 2.

Bivariate analyses for center-based referrals for health screenings and developmental assessments and predisposing, enabling, and need factors

Variables Referrals (no) Referrals (yes) p
Estimate 95% CI Estimate 95% CI
LL UL LL UL
Predisposing factors
Child race/ethnicity (independent variable)
 White, non-hispanic 51.7 a 46.4 57.0 58.1 a 51.4 64.7
 Black, non-hispanic 24.3 a 19.8 28.8 24.6 a 18.8 30.5
 Hispanic 13.5 a 14.6 23.8 13.5 a 10.6 16.3
 Asian 3.1 a 2.2 7.1 3.1 a 2.4 3.9
 Other 10.3 a 7.7 11.1 10.3 a 6.4 14.2
Language spoken by providers
 English only 68.4 c 59.9 75.8 68.1c 61.6 74.0 0.950
 English, Spanish, other/combination 31.6 c 24.2 40.1 32.0 c 26.0 38.4
Enabling factors
 Teachers/lead teachers in program 82.6 b 78.0 87.2 84.1 b 79.0 89.1
 Aides/assistant teachers in program 3.4 b 2.8 3.9 4.1 b 3.6 4.7
 Specialists 6.8 b 4.4 9.3 12.0 b 7.4 16.5
Provides staff with mentors/coaches/consultants
 No 69.8 c 63.4 75.4 48.0 c 40.0 56.2 < 0.0001***
 Yes 30.2 c 24.6 36.6 52.1 c 43.8 60.1
Relationships-other schools for resources/pro-dev
 No 57.1 c 50.1 63.7 44.7 c 37.8 51.8 < 0.05*
 Yes 43.0 c 36.3 49.9 55.3 c 48.2 62.2
Need factors
Class size 10.4 b 9.6 11.2 11.2 b 10.0 12.5
Refused care-behavioral problems- last 3 months
 No 81.2 c 75.9 85.6 84.7 c 80.1 88.3 0.255
 Yes 18.8 c 14.5 24.1 15.3 c 11.7 19.8
Children with physical condition 1.6 b 0.86 2.3 1.9 b 1.2 2.6
Visit reg agency: non-health/safety qual monitoring
 No 25.2 c 19.7 31.6 15.6 c 11.1 21.5 < 0.01**
 Yes 74.6 c 68.4 80.3 84.4 c 78.6 89.0
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Note. CI = confidence interval; LL = lower limit; UL = upper limit; * < 0.05; *; < 0.01 ** < 0.01; *** < 0.001; a Mean, %; b Mean, number; c odds ratio

Multivariate Analyses

Predisposing Factors

Multivariate analyses began with Model 1, which included the predisposing factors of children’s race/ethnicity and staff language use. After adjusting for children’s races/ethnicities and the language used by center-based providers in their interactions, Hispanic children had lower odds of being referred for off-site health screenings and developmental assessments compared to White, non-Hispanic, Black, non-Hispanic, Asian, and other racial groups (OR = 0.99, 95% CI [0.98–0.99], P = .030) (see Table 3).

Table 3.

Multivariate analyses for center-based referrals for health screenings and developmental assessments and predisposing, enabling, and need factors

Variable OR SE 95% CI p
LL UL
Predisposing factors
Child race/ethnicity (independent variable)
 White, non-hispanic 1.01 0.004 1.00 1.02 0.046*
 Black, non-hispanic 1.01 0.004 1.00 1.01 0.17
 Hispanic 0.99 0.004 0.972 1.00 0.030*
 Asian 0.988 0.008 0.972 1.00 0.121
 Other 1.01 0.007 0.992 1.02 0.389
Language spoken by center-based providers
 English only Reference Reference Reference
 English, Spanish, Other or combination 1.27 0.305 0.80 2.04 0.313
Enabling factors
 Teachers/lead teachers in program 1.00 0.004 0.994 1.01 0.845
 Aides/assistant teachers in program 1.01 0.022 0.966 1.05 0.671
 Specialists 1.71 0.493 0.972 3.02 0.063
Provides staff with mentors/coaches/consultants
 No Reference Reference Reference
 Yes 2.15 0.503 1.36 3.41 0.001
Relationships-other schools for resources/pro-dev
 No Reference Reference Reference
 Yes 1.85 0.462 1.13 3.02 0.014
Need factors
Class size 1.00 0.016 0.973 1.04 0.822
Refused care-behavioral problems- last 3 months
 No Reference Reference Reference
 Yes 0.694 0.156 0.46 1.08 0.106
Children with physical condition 1.00 0.014 0.98 1.03 0.915
Visit reg agency: non-health/safety qual monitoring
 No Reference Reference Reference
 Yes 1.85 0.461 1.13 3.02 0.014
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Note. OR = odds ratio; SE = standard error; CI = confidence interval; LL = lower limit; UL = upper limit; * < 0.05; *; < 0.01 ** < 0.01; *** < 0.001

Enabling Factors

Model 2 revealed that center-based providers who received mentorship, coaching, or consulting support through their program were significantly more likely to refer children for health screenings and developmental assessments. This association remained after controlling for predisposing factors, staffing composition, and access to professional development resources through school partnerships (OR = 2.15, 95% CI [1.36–3.41], P = .001) (see Table 3).

Need Factors

In Model 3, we identified a positive association between center-based providers who reported visits from health and safety agencies within the past year and a higher likelihood making referrals for screenings and assessments (OR = 1.85, 95% CI [1.13–3.02], P = .014) (See Table 3).

Discussion

Our analyses showed key factors that significantly shape referral practices in center-based programs. Children’s races/ethnicities were a key predisposing factor; Hispanic children had lower referral odds for health screenings and developmental assessments compared to other racial/ethnic groups, after adjusting for provider language use. One enabling factor, provision of mentorship, coaches, or consultants significantly increased referrals, adjusting for other staff and resource factors. Notably, regulatory oversight emerged as the only need factor positively associated with programs actively facilitating referrals. This relationship remained significant when controlling for predisposing and enabling factors, as well as other need factors such as class size, care refusal due to behavioral issues, and the percentage of children with physical conditions in the program.

Referral Patterns for Health Screenings and Developmental Assessments in Hispanic Children

In our study, we found that only about 7% of children under 5 in center-based programs were Hispanic. This suggests a missed opportunity to support these families. Low-income Hispanic families often face barriers to accessing care. The availability of limited program options, cumbersome paperwork, and cultural preferences for home-based care can present barriers to families. (Mendez Smith, 2020; Gallegos et al., 2021). They may need help navigating the ECE systems and understanding its benefits. For example, while they prioritize enrichment when selecting preschools for older children, they are less likely to enroll their younger children in center-based programs (Mendez & Crosby, 2021), which may explain why Hispanic children have lower referral rates screenings and assessments. For instance, Hispanic children tend to perform more poorly on visual acuity tests. This may be because astigmatism, which strikes this demographic at a far higher rate than other racial/ethnic groups. Research has found that while Hispanic, White, non-Hispanic, and Black, non-Hispanic children show similar rates of ASD, Hispanic children often face delays in getting ASD services. This is due to several barriers: limited English proficiency, cultural beliefs that may lead parents to overlook developmental issues, a shortage of bilingual providers, and a lack of information available in Spanish (Guerrero & Sobotka, 2022). These barriers contribute to the underuse of center-based programs by Hispanic families, especially those with lower incomes.

Optimizing Growth: Understanding Mentorship, Coaching, and Consultation

Several barriers impede effective developmental screening. Professionals often lack ongoing training, particularly regarding ASD (Shahidullah et al., 2020; Chödrön et al., 2020, 2021a). Many centers do not provide regular staff training, and few professionals utilize available online learning opportunities. A significant gap exists in training pertaining to the administration of screening tools and the communication of concerns to families. Although professionals express a strong desire to enhance these skills, the availability of in-service days are limited, rendering attendance at daytime training sessions problematic. Professionals seek training on the identification of ASD characteristics, the explanation of concerns to parents, and the administration of screenings, yet access to such training is not readily available. Due to the challenges of attending daytime sessions and concerns regarding training expenses, on-site training and train-the-trainer models are preferred (Uzonyi et al., 2022).

Surveilling developmental milestones in early childhood education requires educators to navigate documenting observations and identifying potential concerns. Although center-based programs may use a mix of assessments, there is a gap in referring children at risk for developmental delays across different service sectors, such as primary care providers, EI, or special education (Chödrön et al., 2020, 2021b). This gap exists despite providers recognizing issues, often due to barriers like parental concerns and lack of awareness about referral options. Some educators proactively recognize red flags and conduct screenings, while others are reluctant, fearing overstepping into diagnostic roles (Uzonyi et al., 2022). This hesitance is often linked to concerns about screening program costs and complexities, as evidenced by critical feedback from certain centers.

The effective use of data is becoming increasingly important in ECE. However, providers need support to understand how to collect and use data to improve teaching practices and outcomes for children. This includes professional development focused on assessment data, data processes, and evidence-based strategies. A survey of 1,258 ECE practitioners across 13 states highlighted this need, showing that while most consistently collected data, childcare providers were the least confident in using data compared to providers in Head Start and prekindergarten. These findings underscore the need for better training and tools to help ECE practitioners use data to inform their teaching and support children’s development (de Monsabert et al., 2022).

Ensuring Adherence: The Importance of Robust Regulatory Oversight

QRIS provide a framework for enhancing center-based childcare quality. While QRIS standards differ by state, they typically encompass structural and process indicators. For instance, Maryland recommends that licensed providers screen children aged 6 weeks to 5 years, share results with families, and connect families with free resources if concerns emerge. Beginning in July 2023, Delaware will mandate annual developmental and social-emotional screenings for children under 5 in all childcare programs. Despite these efforts and the benefits of QRIS and developmental screening, systemic issues persist in accessing EI services. Traube and Mamey (2021) found no significant link between state-level developmental screening rates and the receipt of IDEA Part C services, despite White, non-Hispanic children being screened and receiving services more often than non-White children. There were substantial variations in developmental screening rates across states, ranging from 58.8% in Oregon to 17.2% in Mississippi.

This variability may stem from states setting their own eligibility criteria, influencing access to and use of services. The drop in federal IDEA Part C funding (U.S. Department of Education, n.d.a.) from 2004 to 2015 may strain early intervention services if increased screening overwhelms current resources. To improve early intervention outcomes for children with developmental delays, it’s essential to address these disparities and provide sufficient funding and resources. By harnessing QRIS and tackling systemic access issues, these may ensure all children can benefit from high-quality ECE and the EI services if or when they need them.

The Synergistic Relationship Between Medical Home Care and Center-Based Childcare Programs

Routine screenings in the medical home and center-based programs can significantly boost referral rates. By recognizing developmental delays and disabilities early, these screenings ensure children get the supports they need. Serving disadvantaged children underscores the need for greater collaboration and coordination of services. Effective communication and collaboration between PCPs, center-based providers, parents, caregivers, and other health professionals are vital for ensuring children receive the necessary screenings and supports. However, privacy laws and communication gaps can hinder the sharing of important information (Donoghue et al., 2017), perpetuating disparities in which children are regularly screened, and which may fall through the cracks. Strengthening partnerships between healthcare and ECE systems can better support the healthy development and well-being of all young children. Coordinated community resources are key to preventing service access delays and avoiding service duplication. National initiatives seek to improve the early detection of developmental disorders and bridge the gap between detection, referral, and service initiation. These evolving initiatives focus beyond screening, on family involvement, results interpretation, assessment and intervention referrals, and service connections. They include quality improvement projects, home visiting programs, an screening within center-based programs (Lipkin et al., 2020a). Medical homes and Head Start have partnered to establish links with pediatric clinics and local early learning programs, integrate a referral system into electronic medical records, educate medical providers about early learning access, and connect families with programs that meet their needs (Horm et al., 2024; Grant et al., 2019).

Center-based programs have made strides in providing comprehensive services by integrating education with health and other supports. However, the outcomes of young children and their families living in poverty continue to be hindered by significant stressors (Horm et al., 2024). To meaningfully address these challenges, it is essential to strengthen partnerships between pediatric health systems and educational environments. Yet, these systems often struggle to reach those most in need, and inequities persist in service access and delivery. Improving outcomes for children requires enhanced cross-system collaboration, particularly between ECE programs, like EHS, and medical homes.

Medical homes, public health programs, and comprehensive services must adopt prevention-focused frameworks. Investing in training and professional development across service platforms can foster a shared understanding of relational health. Systematically incorporating family input can enhance screening tools and reduce biases in diagnostic care. Partnerships between medical homes and Head Start programs can standardize referral processes, increasing screening and referral rates. Despite these opportunities, barriers persist. Lack of contact from agencies and transportation challenges can hinder enrollment in programs for referred children. To enhance ECE access and address systemic barriers, it is crucial to improve communication and collaboration between healthcare and education sectors.

Incorporating pediatric care into EHS settings and enhancing service integration can expand delivery models. Increasing training and awareness of biases can help combat racism within these systems. Recommendations for optimizing health services for young children must address systemic barriers and improve collaboration between health and education sectors, which include center-based childcare programs. For example, Black, non-Hispanic families face significant barriers to the early diagnosis of ASD with systemic delays often overshadowing the effectiveness of existing screening procedures (Weitlauf et al., 2022). PCPs need to actively engage in discussions about developmental risks, as referrals for follow-up care are more likely when both parents and providers express concerns. Current screening models may not adequately reflect the needs of diverse groups, as they have primarily been developed based on input from White, non-Hispanic families.

Limitations

While this study provides insights into center-based childcare referral practices, it has limitations. Consolidating health screening and developmental assessment referral data may introduce uncertainty about each type’s effectiveness. Future research should disaggregate these data. Another limitation is that we cannot determine if referrals led to evaluations and service access. Future studies must track the entire care continuum. The NSECE included EHS/HS programs, which may report more developmental tracking and impact referral rates (U.S. Department of Education, n.d.b.). In most states, these programs are mandated by the U.S. Department of Health and Human Services to screen and monitor child development. The precision of our estimates regarding Hispanic children may affect interpretations. Future research should oversample racial and ethnic minority groups. Finally, uncertainties in estimates analyzing referral rate differences for Hispanic children could impact conclusions’ validity (Martin et al., 2020).

Conclusions

Our study findings revealed a positive association between center-based childcare programs offering staff mentorship and their propensity to make referrals for health screenings and developmental assessments. This suggests tremendous potential for enhancing the delivery of these essential health and developmental referrals. However, Hispanic children exhibited marginally lower odds of receiving these referrals, highlighting a crucial disparity that must be addressed. Moving forward, it is imperative that we keep our overarching goal in mind: supporting the healthy development and well-being of all young children, irrespective of their racial or ethnic background. By strengthening the capacity of center-based childcare programs to facilitate referrals for health screenings and developmental assessments, we can help ensure that every child has access to the timely interventions and supports they need to succeed. Achieving this vision will necessitate ongoing research, collaboration, and a shared commitment to providing every child with the strong start in life they deserve. The findings of this study represent an important step in that direction, illuminating the critical role that center-based childcare programs can play in connecting families with vital services and setting children on a path towards lifelong health and well-being.

Authors’ contributions

Dr. Rizk conceptualized and designed the study, conducted data analyses, drafted the initial manuscript, and reviewed and revised the manuscript. Dr. Barger and critically reviewed and revised the manuscript for important intellectual content. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Funding

This study was supported by the University of Illinois Chicago Institute for Research on Race and Public Policy Faculty Fellowship Program (PI: S. Rizk) and the Bridge to Faculty Postdoctoral Research Scholars Program (S. Rizk). We thank the University of Illinois Chicago Clinical and Translational Sciences (M. Berbaum) and the Children’s Participation in Environment Research Lab (M. Khetani) for their input on design and analyses.

Data Availability

The dataset analyzed is publicly available through the Office of Planning, Research, & Evaluation. An Office of the Administration for Children & Families https://www.icpsr.umich.edu/web/ICPSR/studies/37941/datadocumentation or available upon request from United States Department of Health & Human Services. Administration for Children and Families. Office of Planning, Research and Evaluation, andNSECE Project Team (National Opinion Research Center). National Survey of Early Careand Education (NSECE) Public-Use Files, [United States], 2019. Inter-university Consortium for Political and Social Research [distributor], 2023-11-01. 10.3886/ICPSR3791.v6

Code Availability

Code available from corresponding author upon request.

Declarations

Ethics Approval

This study was exempt by the University of Illinois Chicago Institutional Review Board.

Consent to Participate

Not applicable.

Consent for Publication

Not applicable.

Conflict of Interest

The authors have no conflicts of interest relevant to this article to disclose.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The dataset analyzed is publicly available through the Office of Planning, Research, & Evaluation. An Office of the Administration for Children & Families https://www.icpsr.umich.edu/web/ICPSR/studies/37941/datadocumentation or available upon request from United States Department of Health & Human Services. Administration for Children and Families. Office of Planning, Research and Evaluation, andNSECE Project Team (National Opinion Research Center). National Survey of Early Careand Education (NSECE) Public-Use Files, [United States], 2019. Inter-university Consortium for Political and Social Research [distributor], 2023-11-01. 10.3886/ICPSR3791.v6

Code available from corresponding author upon request.

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