Established Evidence Results

Intervention Components (click on component to see a list of all articles that use that intervention): Health Insurance Coverage, Access, Educational Material, Targeting Interventions to Focused Groups

Intervention Description: N/A

Intervention Results: Refugees with interrupted healthcare coverage were more likely to have an inadequate USC. Refugees who were young (age 10-19), resettled into the western region of the US, and highly educated were less likely to have an inadequate USC. Refugees with an education level higher than secondary had a significantly lower likelihood of having a severely deficient USC, while refugees with interrupted healthcare were more than twice as likely to have a severely deficient USC.

Conclusion: Considering these results alongside our previous healthcare coverage findings provides a more comprehensive understanding of sociodemographic predictors of poor healthcare access among refugees resettled into the US. This improved understanding has the potential to assist early refugee contacts toward more effective healthcare resource allocation and aid policymakers attempting to improve programs linked to refugee healthcare access.

Study Design: We used multiple binary logistic regression methods to identify sociodemographic predictors of inadequate USCs. In addition, we used multinomial logistic regression to further assess predictors of inadequate USCs with a particular focus on severely deficit USCs (i.e., emergency department dependence and USC absence).

Setting: 2016 Annual Survey of Refugees; United States

Population of Focus: Refugees

Sample Size: 4037

Age Range: 16-75

Intervention Components (click on component to see a list of all articles that use that intervention): Assessment (Provider), Access, Care Coordination, Targeting Interventions to Focused Groups

Intervention Description: N/A

Intervention Results: Fifty-three percent (n = 107) of the children received care within a medical home. Low socioeconomic status (young caregiver: risk ratio [RR] = 0.73; 95% CI 0.55, 0.97; low education: RR= 0.69; 95% CI 0.49, 0.98) and delayed language (RR = 0.63; 95% CI 0.42, 0.95) were associated with a lower likelihood of receiving care within a medical home. Degree of prematurity and neonatal clinic follow-up participation were unrelated to receipt of care within a medical home.

Conclusion: Receipt of care within a medical home was lacking for nearly one-half of preterm toddlers, especially those with lower socioeconomic status and poorer developmental status. Discharge from a neonatal intensive care unit may be an optimal time to facilitate access to a primary care medical home and establish continuity of care.

Study Design: Participants were 202 caregivers of children born at <35 weeks of gestation. At 10-16 months of corrected age, caregivers completed the National Survey of Children's Health (2011/2012) medical home module and a sociodemographic profile. Care within a medical home comprised having a personal doctor/nurse, a usual place for care, effective care coordination, family-centered care, and getting referrals when needed. Gestational age and neonatal follow-up clinic attendance were abstracted from the medical record. The Bayley Scales of Infant and Toddler Development, Third Edition assessed developmental status. Log-binomial regression examined factors related to receiving care within a medical home.

Setting: NSCH Survey; United States

Population of Focus: Caregivers of children born pre-term

Sample Size: 202

Age Range: Caregivers vary in age. Babies born before 35 weeks.

Intervention Components (click on component to see a list of all articles that use that intervention): Adult-led Support/Counseling/Remediation, Mentor Engagement, Targeting Interventions to Focused Groups

Intervention Description: formal mentoring programs, with a focus on comparing targeted, skills-based mentoring programs to non-specific, relational mentoring programs. The unique aspect of the targeted programs was that they explicitly matched specific interventions to mentees’ presenting problems.

Intervention Results: results showed that targeted, problem-focused mentoring programs had a significantly larger effect size (0.25) compared to non-specific programs (0.11).

Conclusion: The conclusion was that while relationship-building is important in mentoring, targeted, skills-based interventions may be necessary for helping mentees achieve change.

Study Design: meta-analysis of formal mentoring programs

Setting: formal mentoring programs for youth

Population of Focus: youth

Sample Size: 48 studies and 535 effect sizes

Age Range: youth

Intervention Components (click on component to see a list of all articles that use that intervention): Adult-led Support/Counseling/Remediation, Targeting Interventions to Focused Groups

Intervention Description: The intervention described is a school-based, mixed-delivery mentoring program where undergraduate students enrolled in a service learning course at the University of Auckland mentor youth in their final year of middle school. The program uses a mixed-delivery format where dyads are matched, but meet as a group in a shared space every week. Mentors meet weekly with their mentees for two hours after school, and all sessions take place at the mentee’s school under the supervision of a program staff member.

Intervention Results: The results of the study identified several features of mentoring relationship quality, including mentor-mentee bond, shared purpose, positive partnership in action, and positive mentee change. The study also identified mentor characteristics that influence relationship quality, including attunement, critical self-reflection, self-efficacy, holistic view of mentee, and language and culture.

Conclusion: The conclusion of the study is that mentors are crucial to establishing high-quality mentoring relationships, and that program staff have the potential to be valuable data sources for understanding relationship quality. The study also suggests that mentoring programs should consider integrating a focus on mentor attunement, self-efficacy, critical self-reflection, and consideration of the holistic needs and wellbeing of mentees into their mentor training.

Study Design: case study paradigm

Setting: school-based, mixed-delivery mentoring program in Auckland, New Zealand.

Population of Focus: youth

Sample Size: nine mentor-mentee dyads and two program staff members.

Age Range: 12

Intervention Components (click on component to see a list of all articles that use that intervention): Policy/Guideline (State), Prenatal Care Access, Targeting Interventions to Focused Groups

Intervention Description: The intervention in this study was Pennsylvania's criminal sentencing reform policy, which aimed to reduce the state's prison population by implementing revised sentencing guidelines and increasing investments in community-based services. The policy was implemented in 2012 and was expected to reduce the number of people admitted to state prisons in Pennsylvania. The study aimed to evaluate the impact of this policy on early and adequate prenatal care utilization among birthing people in Pennsylvania, with a focus on effect heterogeneity across birthing person race/ethnicity and educational attainment. The study found that the benefits of the policy for prenatal care were largely limited to counties where prison admission rates declined the most after the policy, and improvements were primarily observed among groups that are more likely to be affected by prison admissions, Black birthing people and those with lower levels of education

Intervention Results: The study found that in counties where prison admissions declined the most after the policy, early prenatal care increased from 69.0% to 73.2%, and inadequate prenatal care decreased from 18.1% to 15.9%. By comparison, improvements in early prenatal care were smaller in counties where prison admissions increased the most post-policy (73.5 to 76.4%) and there was no change to prenatal care inadequacy (14.4% pre and post). The study found this pattern of improvements to be particularly strong among Black birthing people and those with lower levels of educational attainment. The study concluded that Pennsylvania's sentencing reforms were associated with small advancements in racial and socioeconomic equity in prenatal care. However, the study also noted that incremental changes to criminal justice policy are unlikely to have broad effects for health equity, and transformative policy changes in the areas of healthcare, social welfare, and criminal justice together will be necessary to see dramatic shifts in preventative healthcare inequities.

Conclusion: The study concluded that Pennsylvania's criminal sentencing reform policy was associated with small advancements in racial and socioeconomic equity in prenatal care utilization. The study found that the benefits of the policy for prenatal care were largely limited to counties where prison admission rates declined the most after the policy, and improvements were primarily observed among groups that are more likely to be affected by prison admissions, Black birthing people and those with lower levels of education. The study also noted that incremental changes to criminal justice policy are unlikely to have broad effects for health equity, and transformative policy changes in the areas of healthcare, social welfare, and criminal justice together will be necessary to see dramatic shifts in preventative healthcare inequities. The study highlights the importance of contextual conditions of incarceration for preventative healthcare access and utilization and sheds light on how criminal justice reforms may have spillover effects for healthcare utilization and health equity.

Study Design: The study design was an interrupted time series analysis using individual-level birth certificate data linked to county-level rates of prison admissions in Pennsylvania from 2009 to 2015. The study aimed to evaluate the impact of Pennsylvania's criminal sentencing reform policy on early and adequate prenatal care utilization, with a focus on effect heterogeneity across birthing person race/ethnicity and educational attainment. The study used Poisson regression models with robust error variance to estimate changes in prenatal care utilization after the policy, stratified by quartiles of county-level pre-post difference in mean monthly prison admission rates. The study design allowed for the assessment of changes in prenatal care utilization over time, before and after the policy, and across different subgroups of the population.

Setting: The setting for this study is Pennsylvania, focusing on the period from 2009 to 2015. The researchers linked individual-level birth certificate data to monthly county-level rates of prison admissions in Pennsylvania during this time frame. By examining the effects of Pennsylvania's criminal sentencing reform on prenatal healthcare access and equity, the study provides valuable insights into the impact of policy changes on healthcare utilization in the context of the criminal justice system

Population of Focus: The target audience for this study is likely researchers, policymakers, and healthcare professionals interested in understanding the impact of criminal justice policies on healthcare access and equity, particularly in the context of prenatal care. The study provides important insights into the potential benefits of reducing incarceration rates for improving early and adequate prenatal care, particularly for marginalized communities. The findings may be of interest to those working in public health, criminal justice reform, and healthcare policy.

Sample Size: Thestudy used individual-level birth certificate microdata on births in Pennsylvania from 2009 to 2015, totaling 999,503 births. This large sample size allowed the researchers to assess the effects of Pennsylvania's criminal sentencing reform on prenatal healthcare access and equity across a significant number of births in the state. The substantial sample size contributes to the robustness of the study's findings.

Age Range: The study did not report a specific age range for the birthing people included in the sample. However, the study did collect data on self-reported age (< 19, 20–29, 30–39, 40 + years) as an individual-level covariate in their statistical analysis. Therefore, the study likely included birthing people across a range of ages, from under 19 to over 40 years old.

Intervention Components (click on component to see a list of all articles that use that intervention): Prenatal Care Access, Social Supports, Targeting Interventions to Focused Groups

Intervention Description: The augmented care intervention included educationally oriented peer groups, additional appointments, extended time with clinicians, and other supports. The Mother and Family Specialty Center was created to provide augmented care, which sought to minimize risk conditions and improve pregnancy outcomes. The center provided transportation, child care, and a physical environment designed to provide welcoming, positive messages. Discussion groups were held as an integral part of each center visit to increase both social support and knowledge. Information was compiled and distributed to mothers-to-be in both video and easy-to-read print formats. The intervention also included home visits, weekend clinic hours, and direct provision of additional books and equipment

Intervention Results: Women in augmented care rated all aspects of their prenatal care significantly more favorably than did those in usual care. Participating in the Mother and Family Specialty Center was associated with highly positive appraisals of helpfulness, a belief among multiparous women that care was better this time, increased amounts of time spent with their regular nurse, and an almost universal perception that their nurse was “very helpful”. In contrast, those in usual care had more mixed evaluations of their prenatal care, although 80% judged their overall care to be “very helpful”. The number of prenatal visits was significantly greater in augmented care than in usual care. A dramatic difference between the 2 groups was self-report of participation in prenatal or childbirth classes: 79% for augmented care and 17% for usual care. Informing women about their own risk conditions and about pregnancy and delivery was an important feature of augmented care. Significantly more women in augmented care than in usual care reported that they were told they or their baby were “at risk,” although most still reported that they were not informed of their own specific risks. This self-report is at odds with the documented nurse records, which indicated that particular risks were discussed on multiple occasions. However, 69% of those aware of their risk conditions in augmented care reported positive behavior change as a result of prenatal care information, compared with 48% in usual care. Pregnancy outcomes did not differ significantly between the groups; however, among patients in augmented care, rates of preterm births were lower and cesarean deliveries and stays in neonatal intensive care units occurred in smaller proportions. Both groups had lower-than-predicted rates of low birthweight

Conclusion: High-quality prenatal care, emphasizing education, health promotion, and social support, significantly increased women’s satisfaction, knowledge of risk conditions, and perceived mastery in their lives, but it did not reduce low birthweight. The study found that augmented care did not significantly improve pregnancy outcomes, but it did improve women’s perceptions of their care and their knowledge of risk conditions. The study suggests that providing additional support and education to high-risk pregnant women can improve their satisfaction with care and their knowledge of risk conditions, which may lead to positive behavior change. The study also suggests that providing additional support and education to high-risk pregnant women may reduce rates of preterm births, cesarean deliveries, and stays in neonatal intensive care units .

Study Design: The study design was a randomized controlled trial . All pregnant women who sought prenatal care from the Jefferson County (Alabama) Department of Health from March 1994 to June 1996 were screened for eligibility. Women were eligible if they met the following criteria: (1) African American, (2) eligible for Medicaid, (3) less than 26 weeks’ gestation, (4) at least 16 years old, and (5) score of 10 or higher on a risk assessment scale. The scale was based on multiple analyses of a computerized database that included all Medicaid-eligible pregnancies in the area during 1993 and 1994 and a prospective study of high-risk pregnancies . The eligible women were randomly assigned to augmented care or usual care

Setting: The study was conducted in Jefferson County, Alabama, and specifically focused on the Mother and Family Specialty Center, which provided the augmented prenatal care program for high-risk African American women . The center offered a supportive environment with culturally appropriate and individualized care, emphasizing health promotion and education . The setting included features such as transportation assistance, child care, and a welcoming physical environment designed to provide positive messages and cultural appropriateness .

Population of Focus: The target population of the study was high-risk African American women who were eligible for Medicaid, scored 10 or higher on a risk assessment scale, were 16 years or older, and had no major medical complications . The study aimed to improve pregnancy outcomes and patients’ knowledge of risks, satisfaction with care, and behavior for this specific population . The study sample included 656 African American women who enrolled in the trial, with outcome data available for 619 who delivered in area hospitals

Sample Size: The sample size for the study was 656 African American women who enrolled in the trial. Outcome data were available for 619 who delivered in area hospitals, where 318 received augmented care and 301 received usual care . The sample size of 285 women in the experimental group and a similar number of controls were considered adequate to detect a reduction in the rate of low birthweight from 20%–25% to 10%–12%

Age Range: The sample size for the study was 656 African American women who enrolled in the trial. Outcome data were available for 619 who delivered in area hospitals, where 318 received augmented care and 301 received usual care . The sample size of 285 women in the experimental group and a similar number of controls were considered adequate to detect a reduction in the rate of low birthweight from 20%–25% to 10%–12%

Intervention Components (click on component to see a list of all articles that use that intervention): Family-Based Interventions, Targeting Interventions to Focused Groups

Intervention Description: N/A

Intervention Results: There were 62,965 respondents. After survey weighting, Asians (OR 1.78, 95% CI 1.19-2.66) as an aggregate group were more likely to report discrimination than non-Hispanic Whites. When Asians were disaggregated, Japanese (3.12, 1.36-7.13) and Koreans (2.42, 1.11-5.29) were more likely to report discrimination than non-Hispanic Whites. Self-reported discrimination was marginally associated with not having a usual source of care (1.25, 0.99-1.57). Koreans were the only group associated with not having a usual source of care (2.10, 1.23-3.60). Foreign-born Chinese (ROR 7.42, 95% CI 1.7-32.32) and foreign-born Japanese (ROR 4.15, 95% CI 0.82-20.95) were more associated with self-reported discrimination than being independently foreign-born and Chinese or Japanese.

Conclusion: Differences in self-reported discrimination in a healthcare setting and not having a usual source of care were observed among Asian ethnic subgroups. Better understanding of these differences in their sociocultural contexts will guide interventions to ensure equitable access to healthcare.

Study Design: Using the California Health Interview Survey (CHIS) 2015-2017, we used logistic regression models to assess associations among Asian ethnic subgroup, self-reported discrimination, and not having a usual source of care. Interactions between race and self-reported discrimination, foreign-born status, poverty level, and limited English proficiency were also analyzed.

Setting: California Health Interview Survey (CHIS) 2015-2017; California

Population of Focus: Respondents represented adults age 18 + residing in California who identified as White, Black, Hispanic, American Indian/Alaska Native, Asian (including Chinese, Filipino, Japanese, Korean, Vietnamese, and Other Asian), and Other.

Sample Size: 62965

Age Range: 18+

Intervention Components (click on component to see a list of all articles that use that intervention): Care Coordination, Telemedicine Systems (Inter-Hospital Systems), Quality Improvement, Targeting Interventions to Focused Groups

Intervention Description: N/A

Intervention Results: Those with No USC and Facility USCs increased 10 and 18 percent, respectively, while those with Person USCs decreased by 43 percent. Compared to those in the lowest income bracket, those in the highest income bracket were less likely to have a Facility USC. Among those with low incomes, individuals with No USC, Person, in Facility, and Facility USCs were more likely to have ED visits than those with Person USCs.

Conclusion: A growing number are reporting facilities as their USCs or none at all. The impact of these trends is uncertain, although we found that some USC types are associated with ED visits and hospital admissions. Tracking USCs will be crucial to measuring progress toward enhanced care efficiency.

Study Design: We stratified each USC category, by age, region, gender, poverty, insurance, race/ethnicity, and education and used regression to determine the characteristics associated with USC types, ED visits, and hospital admissions.

Setting: 1996-2014 Medical Expenditure Panel Surveys

Population of Focus: Low income individuals, those with no USC

Sample Size: 559762

Age Range: All ages, five categories

Intervention Components (click on component to see a list of all articles that use that intervention): Family-Based Interventions, Provider Training/Education, Health Insurance Coverage, Targeting Interventions to Focused Groups

Intervention Description: N/A

Intervention Results: Fifty percent of adolescents experienced PCMH care, with little change between 2004 and 2013. Adolescents with MH need (N = 3,794) had significantly lower odds of experiencing PCMH care compared with those without MH need (odds ratio, .78; 95% confidence interval, .69-.87). Among adolescents with MH needs, being uninsured and living with a parent who did not graduate high school were negatively associated with PCMH care, whereas parental usual source of care was positively associated (odds ratio, 1.69; 95% confidence interval, 1.28-2.22).

Conclusion: Increasing care accessibility, integrating MH services into primary care settings, and targeting socioeconomically disadvantaged subgroups could improve rates of PCMH care among adolescents with MH needs.

Study Design: This was a secondary analysis of Medical Expenditure Panel Survey data (2004-2013). The sample included adolescents aged 12-17 years with ≥1 office-based visits in the past year (N = 18,717). Questions assessing a usual source of care and care that is accessible, comprehensive, family-centered, and compassionate were used to define PCMH care. For adolescents with MH needs, multivariable logistic regression was used to describe the association between PCMH care and sample characteristics.

Setting: Medical Expenditure Panel Survey

Population of Focus: Adolescents

Sample Size: 3794

Age Range: 12/17/2024

Intervention Components (click on component to see a list of all articles that use that intervention): , EMR Reminder, Targeting Interventions to Focused Groups, Educational Material, Mobile Apps, Online Material/Education/Blogging

Intervention Description: The study primarily focuses on developing a data-driven primary intervention approach using machine learning and electronic health records (EHR) data to identify pregnant women at risk for postpartum depression (PPD) . The intervention aligns with a discernible strategy of leveraging machine learning algorithms to predict PPD risk based on EHR data, with the potential for early prevention, diagnosis, and intervention . The study does not analyze a multicomponent intervention; rather, it focuses on the development and validation of a machine learning algorithm for PPD risk prediction using EHR data. The intervention strategy is centered around leveraging data-driven approaches to identify at-risk individuals and potentially tailor therapeutic interventions, screening timelines, and preventive strategies for PPD

Intervention Results: The study analyzed a total of 15,197 deliveries from January 2015 to June 2018, and the prevalence of depression was 6.7% (N=1,010) and 6.5% (N=3,513) in the WCM and NYC-CDRN datasets, respectively . The machine learning algorithm was able to predict PPD risk with an area under the receiver operating characteristic curve (AUC-ROC) of 0.83 (95% CI: 0.81-0.85) in the training dataset and 0.80 (95% CI: 0.77-0.83) in the validation dataset . The study found significant differences in age, the number of emergency department visits, and racial distribution between PPD and non-PPD groups in the training and validation data . The study demonstrates that a data-driven primary intervention approach using machine learning and EHR data may be leveraged to reduce the healthcare provider burden of identifying PPD risk.

Conclusion: Machine learning-based models incorporating EHR-derived predictors, could augment symptom-based screening practice by identifying the high-risk population at greatest need for preventive intervention, before development of PPD.

Study Design: The study design was a prospective cohort study that used electronic health records (EHR) data to develop and validate a machine learning algorithm for predicting the risk of postpartum depression (PPD) among pregnant women . The study used two EHR datasets containing data on 15,197 women from 2015 to 2018 at a single site and 53,972 women from 2004 to 2017 at multiple sites as development and validation sets, respectively . The study included all pregnant women with fully completed antenatal care procedures who had live births of infants, and the exclusion criteria were maternal age below 18 or above 45, or lack of outpatient, inpatient, or emergency room encounter information in the EHR data within 1 year following childbirth . The study was approved by the Institutional Review Board at Weill Cornell Medicine (IRB protocol# 1711018789), and data extraction and analysis were performed in 2019 . The study used a well-defined outcome measure of PPD diagnosis within 1 year following childbirth, and the machine learning algorithm was able to predict PPD risk with a high degree of accuracy

Setting: The study setting for the development dataset was a single site, and the validation dataset included data from multiple health systems across New York City affiliated with the Patient-Centered Outcomes Research Institute funded New York City Clinical Data Research Network data (NYC-CDRN) . Therefore, the study setting primarily involved healthcare institutions and systems in New York City, USA.

Population of Focus: The target audience for the study includes healthcare professionals, researchers, and policymakers involved in maternal and mental health, as well as professionals working with electronic health records (EHR) and machine learning applications in healthcare. Additionally, the findings of the study may be of interest to organizations and institutions involved in developing and implementing predictive models for identifying and addressing the risk of postpartum depression among pregnant women.

Sample Size: The study included a total of 15,197 deliveries from January 2015 to June 2018 in the development dataset, and 53,972 deliveries from August 2004 to October 2017 in the validation dataset . These datasets were used to develop and validate a machine learning algorithm for predicting the risk of postpartum depression among pregnant women.

Age Range: The study included pregnant women within a specific age range. The exclusion criteria for the study were maternal age below 18 or above 45 . Therefore, the age range of the included pregnant women in the study was 18 to 45 years old.