Established Evidence Results

Intervention Components (click on component to see a list of all articles that use that intervention): PAYER, Expanded Insurance Coverage, HEALTH_CARE_PROVIDER_PRACTICE, Public Insurance (Health Care Provider/Practice), Educational Material (Provider), Collaboration with Local Agencies (State), Collaboration with Local Agencies (Health Care Provider/Practice), Nurse/Nurse Practitioner, PROFESSIONAL_CAREGIVER, Patient Navigation (Assistance), Care Coordination, STATE, Multicomponent Approach

Intervention Description: The Healthy Beginnings system of care in Atlanta, GA connects children and their families to health insurance and a medical home model of care to support children’s health and development. The main components are care management + education and parent engagement + collaborative partnerships. A registered nurse, known as the health navigator, supports parents and helps them learn how to work with health care professionals on behalf of their children; they also connect parents to the Center for Working Families to ensure that they receive public benefits for which they are eligible.

Intervention Results: Healthy Beginnings coordinated care approach has ensured that participating children and families have health insurance (97%) and receive regular immunizations (92%), ongoing health care from a primary care physician and dental health provider, and regular developmental screenings (98%) and follow-up care. Healthy Beginnings has dramatically increased children’s access to health care and forms the basis for a cost-effective approach that can be replicated in other communities.

Conclusion: By building upon the partnerships formed through the foundation’s community change effort, Healthy Beginnings has dramatically increased neighborhood children’s access to health care and forms the basis for a cost-effective approach that can be replicated in other communities.

Study Design: Program evaluation

Setting: Community (Community-based organizations in Atlanta, Georgia)

Population of Focus: Low-income young children and families

Data Source: Questionnaire data

Sample Size: 279 children

Age Range: 0-10 years

Intervention Components (click on component to see a list of all articles that use that intervention): Multicomponent Approach, Office Systems Assessments and Implementation Training, Data Collection Training for Staff,

Intervention Description: The intervention implemented in the study aimed to improve the process of referring patients to early intervention (EI) services. The multifaceted intervention included several components: 1. Patient and provider activation: The improvement team met with local EI staff to review eligibility criteria and best practices in motivating families to connect with EI. An EI brochure was developed to educate families on EI's services and evaluation process. 2. Centralizing and tracking referrals through an EI registry: The referral routes were streamlined by encouraging the use of an electronic order form within the electronic medical record (EMR) to direct the referral into the database after an intake visit had been scheduled. An EI registry was utilized to track referrals and facilitate follow-up for patients. 3. Plan-Do-Study-Act (PDSA) cycles: The team conducted a series of PDSA cycles regarding communication with EI sites to refine the intervention and address any identified barriers. The intervention was designed to address the identified drivers of successful EI referral and to streamline the referral process, ensuring that patients were connected with EI in a timely manner. The multifaceted approach aimed to improve the connection of patients to EI services and to track the effectiveness of the intervention.

Intervention Results: The percentage of patients evaluated by EI within 120 days increased from a baseline median of 50% to a median of 72% after implementation of the systems (N = 309). After implementation, the centralized referral system was used a median of 90% of the time. Tracking of referral outcomes revealed decreases in families refusing evaluations and improvements in exchange of information with EI.

Conclusion: Yes, the study reported statistically significant findings related to the evaluation of patients referred to early intervention (EI) services. The study found that the percentage of patients evaluated by EI within 120 days of referral increased from a baseline median of 50% to a median of 72% after the implementation of the new referral process. Additionally, the study identified demographic and clinical predictors of successful evaluation, with insurance status and specific diagnoses being statistically significant factors associated with timely evaluation. Furthermore, the study used t tests, χ2 testing, and multivariate logistic regression to identify these predictors and assess the statistical significance of the findings. The results of the study demonstrated the effectiveness of the intervention in improving the timely connection of patients to EI services.,

Study Design: The study design used in this research is a quality improvement (QI) initiative. The authors engaged in a quality improvement study to redesign the early intervention (EI) referral process with the goal of ensuring that 70% of patients referred to EI were evaluated by the program. The QI initiative involved implementing a multifaceted referral process, including a centralized electronic referral system used by providers, patient navigators responsible for processing all EI referrals, and a tracking system post-referral to facilitate identification of patients failing to connect with EI. The study utilized a QI approach to address the issue of timely connection to early intervention for young children with developmental delays.,

Setting: The quality improvement initiative was implemented at an academic hospital-based primary care clinic that cares for approximately 16,000 patients, with 17% of them being under 3 years of age and potentially eligible for early intervention services. The families primarily reside in urban neighborhoods, and 68% of them are Medicaid insured. The pediatric provider team consists of attending physicians, nurse practitioners, and resident physicians. The clinic serves a low-income population, and 20% of well-child visits are billed as having a developmental-behavioral concern. The study was conducted in this setting to improve the connection of patients to early intervention services.

Population of Focus: The target audience for the study includes healthcare professionals, particularly those involved in pediatric primary care, early intervention programs, and quality improvement initiatives. Additionally, policymakers and researchers interested in early childhood development, developmental services, and interventions for children with developmental delays would also find the study relevant. The findings and recommendations from the study are likely to be of interest to professionals and organizations involved in improving the coordination of early intervention referrals and services for young children with developmental delays.

Sample Size: The sample size for the study was 309 patients who were referred to early intervention services from the academic primary care clinic. Of these patients, 219 were evaluated within 120 days of referral. The study analyzed the demographic and diagnostic characteristics of the patients and their associations with timely referral to early intervention services.

Age Range: The article discusses early intervention for children under the age of 3 years who are experiencing or at risk for developmental delays.

Intervention Components (click on component to see a list of all articles that use that intervention): PAYER, Expanded Insurance Coverage, HEALTH_CARE_PROVIDER_PRACTICE, Public Insurance (Health Care Provider/Practice), PROFESSIONAL_CAREGIVER, Education/Training (caregiver), Collaboration with Local Agencies (State), Educational Material (caregiver), STATE, Multicomponent Approach

Intervention Description: In New York, to maximize comprehensive insurance coverage for CYSHCN, a Service Integration Model was formed between the Office of Health Insurance Services and the Early Intervention Program. The 3 key components include educational messaging (jointly prepared messages about health insurance benefits and enrollment assistance offered by the Office of Health Insurance Services through the Early Intervention Program) + data from program databases (data matching with the Early Intervention Program) + individual counseling using program staff (incorporation of the Office of Health Insurance Services program staff—child benefit advisors—to work directly with parents of children in the Early Intervention Program to facilitate enrollment and renewal. The model overcomes enrollment barriers by using consumer friendly enrollment materials and one-on-one assistance, and shows the benefits of a comprehensive and collaborative approach to assisting families with enrollment into public health insurance.

Intervention Results: Since 2008, more than 5,000 children in the Early Intervention Program have been successfully enrolled and coverage renewed in Medicaid through the Service Integration Model. In 2008, the study team found that children in the Early Intervention Program had a 34% churning rate for Medicaid because of enrollment barriers and misconception of the Early Intervention Program as a replacement for Medicaid. By 2010, the churning rate for clients assisted through Office of Health Insurance Services was reduced from 34% to 8%. The Office of Health Insurance Services will modify the Service Integration Model to respond to New York State’s implementation of the Health Insurance Exchange required by the 2010 ACA. Partnerships across government programs and agencies offer opportunities to enroll hard-to-reach populations into public health insurance. The model reflects how government programs can work together to improve rates of enrollment and retention in public health insurance. The key elements of integration of program messages, data matching, and staff involvement allow for the model to be tailored to the specific needs of other government programs.

Conclusion: The model overcomes enrollment barriers by using consumer-friendly enrollment materials and one-on-one assistance, and shows the benefits of a comprehensive and collaborative approach to assisting families with enrollment into public health insurance.

Study Design: Program evaluation

Setting: Community (New York City Department of Health and Mental Hygiene's Office of Health Insurance Services and the Early Intervention Program)

Population of Focus: Uninsured and underinsured young children with special health care needs in New York City participating in the Early Intervention Program

Data Source: Evaluation data

Sample Size: 6,500 children in early intervention with a Medicaid number

Age Range: 0-3 years

Intervention Components (click on component to see a list of all articles that use that intervention): Multicomponent Approach, Care Coordination, Family-Based Interventions,

Intervention Description: The intervention in the study was the addition of a community health worker (CHW) to the HealthySteps (HS) care team. The HS model consists of different tiers of service, and the most intensive tier (tier 3) is called comprehensive services. It includes ongoing collaborative team–based well-child visits, care coordination, and systems navigation, which are provided to families determined to be most at risk according to screenings, clinical judgment, and caregiver concerns. Through this program, behavioral health treatment for concerns related to development, behavior, parent-child relationship, and parental mental health is also provided to families. When social determinants of health (SDOH) concerns are identified by pediatric primary care providers, HS Specialists work with families to address their needs. In this study, families were directed to meet with a separate health care worker, similar to a CHW, to receive referrals to address their SDOH needs. The study showed that the overall referral success rate for HS families participating in this study was 88%, and having an HS + CHW team resulted in a successful referral rate of 100% for food services and 89% for childcare services.

Intervention Results: Medical charts with documentation of HS comprehensive services between January and June 2018 were reviewed at 3 primary care clinics: 2 with an HS Specialist (HSS Only) and 1 with an HS Specialist and CHW (HSS + CHW). Eighty-six referrals were identified, 78 of which had documented outcomes. Outcomes were categorized as successful, unsuccessful, and not documented. The HSS + CHW group had a higher rate of successful referrals (96%) than the HSS Only group (74%). Statistical analysis (χ2 = 8.37, P = .004) revealed a significant association between the referral outcome and having a CHW on a primary care team with an HS Specialist.

Conclusion: Yes, the study reported statistically significant findings related to the success of referrals when comparing the HSS Only group with the HSS + CHW group. The referral success rate was 74% for the HSS Only group compared with 96% for the HSS + CHW group, and this difference was statistically significant (χ2 = 8.37, P = .004). Additionally, a logistic regression analysis showed that participation in HSS + CHW compared with HSS Only related to an increased likelihood of a successful referral. The logistic regression model was statistically significant (χ21 = 8.0, P < .001), explaining 19.0% of the variance in successful referrals and correctly classifying 88.5% of cases. These findings indicate that the inclusion of a community health worker on the HealthySteps care team was associated with a significantly higher likelihood of successful referrals to community resources.

Study Design: The study design was a retrospective chart review. Data for the study were collected through retrospective chart reviews of all 192 families who received HealthySteps (HS) comprehensive services over a 6-month period. The chart reviews were conducted to identify the documentation of referrals to community resources or community health workers (CHWs) by HS Specialists. The study also included descriptive analyses of the demographics of study participants and conducted comparisons between the HSS Only group and the HSS + CHW group to assess potential confounding variables.

Setting: The study took place in a large urban city and was conducted in three pediatric primary care practices. The city where the study was conducted had a significant percentage of individuals living below the poverty threshold, with many families facing numerous hardships simultaneously, such as limited access to health care and medical insurance.

Population of Focus: The target audience for the study is likely healthcare professionals, policymakers, and researchers interested in improving access to social determinants of health resources for families with young children living in low-income, underserved urban settings. The study provides insights into the effectiveness of a community health worker (CHW) within a primary care team with a HealthySteps (HS) Specialist in increasing successful connections to community resources for pediatric patients. The findings of the study may be useful for healthcare professionals and policymakers seeking to improve the health outcomes of children living in poverty by addressing social determinants of health.

Sample Size: The study included a total of 192 participants, with 96 participants in the combined HSS Only group and 96 participants in the HSS + CHW group. The demographic data from the two HSS Only sites were combined to form a single HSS Only group due to the small sample size at each site.

Age Range: The age group of the children in the study varied, with ages ranging from birth to 53 months in the combined HealthySteps Specialist (HSS) Only sample, and from birth to 48 months in the HealthySteps Specialist + community health workers (HSS + CHW) group. The study included children from birth to early childhood, encompassing a critical developmental period.

Intervention Components (click on component to see a list of all articles that use that intervention): Policy/Guideline (State), Multicomponent Approach,

Intervention Description: Housing Assistance Programs; Medical-Legal Partnerships; Supportive Housing Programs; Subsidized Housing

Intervention Results: A total of 88 862 births to 45 122 mothers (mean [SD] age, 26.26 [5.76] years) who experienced 99 517 evictions were identified during the study period, including 10 135 births to women who had an eviction action during pregnancy and 78 727 births to mothers who had experienced an eviction action when not pregnant. Compared with mothers who experienced eviction actions at other times, eviction during pregnancy was associated with lower infant birth weight (difference, −26.88 [95% CI, −39.53 to 14.24] g) and gestational age (difference, −0.09 [95% CI, −0.16 to −0.03] weeks), increased rates of LBW (0.88 [95% CI, 0.23-1.54] percentage points) and prematurity (1.14 [95% CI, 0.21-2.06] percentage points), and a nonsignificant increase in mortality (1.85 [95% CI, −0.19 to 3.89] per 1000 births). The association of eviction with birth weight was strongest in the second and third trimesters of pregnancy, with birth weight reductions of 34.74 (95% CI, −57.51 to −11.97) and 35.80 (95% CI, −52.91 to −18.69) g, respectively.

Conclusion: Eviction during pregnancy, particularly during the second and third trimester, was associated with reductions in infants’ weight and gestational age at birth compared with maternal eviction at any other time.

Study Design: case-control study

Setting: Georgia

Population of Focus: Pregnant women facing eviction

Sample Size: 88 862 births

Age Range: 26 yrs

Intervention Components (click on component to see a list of all articles that use that intervention): Multicomponent Approach, Funding Support, Community Health Workers (CHWs),

Intervention Description: This multi-component intervention included patient education about health conditions (hypertension, gestational diabetes, and depression), important health behaviors (nutrition and exercise), and common postpartum symptoms; taught self-management skills; enhanced social support; and connected patients with community resources and health care services, including transportation needs. The intervention also addressed specific psychosocial needs of enrollees. A payment reform component included a cost-sharing arrangement between the health care system and the Medicaid payer to cover costs related to employing a social worker and community health worker, and financial incentives for completed postpartum visits.

Intervention Results: Compared with women in the control group, program participants had higher rates of postpartum visits in the HEDIS-defined time period (66.9% vs 56.0%; P < .001) and higher rates of all postpartum outpatient or gynecologic care up to 90 days after delivery (90.2% vs 83.4%; P= .002). Similarly, program participants were more likely to be enrolled with the Medicaid plan than mothers in the matched comparison group at six months after delivery (79.1% [400/506] vs 73.3% [742/1012]; P= .015) and at one year after delivery (71.0% [359/506] vs 66.3% [671/1012]; P= .067), although this was not statistically significant at one year after delivery.

Conclusion: This novel partnership between a health care system and a Medicaid payer increased postpartum visits among high-risk, low-income mothers. The follow-up rate was higher for visits that occurred within 90 days after delivery, a period consistent with current recommendations for postpartum care from the American College of Obstetricians and Gynecologists. This is one of few initiatives that have integrated health care systems, payers, physicians, and social workers to address access to care and social determinants of health for underserved women.

Study Design: Propensity scoring of Medicaid claims data from 2014 to 2017 was used to compare timely postpartum visits for mothers enrolled in the intervention program versus a similar group of mothers enrolled in the same Medicaid plan who gave birth in 2015 and 2016.

Setting: Mount Sinai Hospital, a large tertiary hospital in New York City

Population of Focus: Women insured by Healthfirst who delivered between April 2015 and October 16 who spoke Spanish or English and had at least 1 of the following: gestational diabetes, hypertension, positive screen for depression, late registration for prenatal care (> 20 weeks), or residence in neighborhoods considered at high risk for diabetes or hypertension.

Sample Size: 506

Age Range: ≥18

Intervention Components (click on component to see a list of all articles that use that intervention): Referrals, Nurse/Nurse Practitioner, Multicomponent Approach,

Intervention Description: The intervention described in the article is an innovative program for the care of children with incontinence and dysfunctional elimination. This program is unique in that it combines subspecialty services (urology, gastroenterology, and psychiatry) in a single point of care for this population. It is also the first reported independent nurse practitioner (NP)-run specialty referral practice in a free-standing pediatric ambulatory subspecialty setting. The program involves the operation of a Continence Clinic, staffed by nurse practitioners, registered nurses, and medical assistants, and equipped with specialized clinical space and testing capabilities, including urodynamics and uroflow systems, anorectal manometry systems, and innovative treatment options such as animated pelvic floor biofeedback using a pediatric pelvic floor biofeedback system. The intervention aims to provide comprehensive care for children with incontinence and dysfunctional elimination, with the goal of achieving continence and improving the overall health and well-being of the affected children. The program also seeks to address the fragmentation of care that currently exists across traditional subspecialties and to demonstrate the effectiveness of non-physician provider reconfiguration of health care delivery in subspecialty practice. Overall, the intervention involves a multidisciplinary approach to the assessment, diagnosis, and management of incontinence and dysfunctional elimination in children, with a focus on integrating subspecialty services and utilizing nurse practitioners to deliver care in a specialized clinic setting.

Intervention Results: Analysis indicates that this model is fiscally sound, has similar or higher patient satisfaction scores when measured against physician-run subspecialty clinics, and has an extensive geographic referral base in the absence of marketing.

Conclusion: The article does not explicitly mention statistically significant findings in the context of hypothesis testing or inferential statistics. However, it reports on various outcome measures such as financial performance, patient/family satisfaction, and geographic referral base data. The study primarily utilizes descriptive statistics to measure and compare these outcomes. While the article provides data on revenue generation, cost per relative value unit, patient satisfaction scores, and geographic referral patterns, it does not explicitly state whether these findings were analyzed for statistical significance. Therefore, the presence of statistically significant findings is not clearly indicated in the article.

Study Design: The study design used in the article is not explicitly stated. However, the article mentions that retrospective data on financial, patient satisfaction, and patient referral base were compiled to assess the program. Additionally, the article discusses the use of descriptive statistics to measure and compare patient/family satisfaction and geographic referral base data. Furthermore, the article refers to the use of a Logic Model, which provides a pictorial representation of how a program is expected to achieve its results and corresponding process and outcome measures for determining the extent to which the intervention was implemented as planned. This suggests that the study may have utilized a program evaluation design based on a Logic Model, which is often used to evaluate the effectiveness and efficiency of unique programs.

Setting: The setting for the study was Nemours Children’s Specialty Care, an outpatient clinic in Jacksonville, Florida. The NP-run Continence Clinic is an independent program within Nemours, which offers 17 pediatric subspecialty services staffed by approximately 100 physicians and 20 NPs. The Continence Clinic is not embedded in any other division and is treated no differently from the physician-run divisions within the organization. It shares the same operations infrastructure as the rest of the subspecialty clinics, including the EPIC electronic medical record with associated registration, scheduling, and billing functions. Corporate services furnish materials and supplies, maintenance, housekeeping, legal, and risk management services.

Population of Focus: The target audience for the study includes healthcare professionals, administrators, and policymakers involved in pediatric subspecialty care, particularly those with an interest in innovative models of care delivery and workforce configurations. Additionally, the study may be of interest to nurse practitioners, as the program described in the article is nurse practitioner-run and represents a novel approach to subspecialty care. Furthermore, the findings of the study may be relevant to researchers and professionals interested in pediatric incontinence and dysfunctional elimination, as well as those focused on improving access to care and patient/family satisfaction in pediatric subspecialty settings.

Sample Size: The article does not explicitly mention the sample size for the study. However, it describes the program as the first reported independent nurse practitioner–run specialty referral practice in a free-standing pediatric ambulatory subspecialty setting. The study reports retrospective data on financial, patient satisfaction, and patient referral base to assess the program. Therefore, the sample size may be related to the patient population served by the NP-run Continence Clinic at Nemours Children’s Specialty Care in Jacksonville, Florida.

Age Range: The age range of the study is not explicitly mentioned in the provided document. However, since the program focuses on providing care for children with incontinence and dysfunctional elimination, it can be inferred that the study likely includes pediatric patients, encompassing a wide age range from infancy to adolescence. For specific details on the age range of the study, it may be necessary to refer to additional sources or contact the authors of the study directly.

Intervention Components (click on component to see a list of all articles that use that intervention): Multicomponent Approach, Quality Improvement/Practice-Wide Intervention, Motivational Interviewing/Counseling,

Intervention Description: From 2015 to 2018 we convened 2 learning collaboratives, named the Quality Improvement Network for Contraceptive Access, with 17 teams (representing 40 sites) from New York City-based hospitals and health centers using an adaptation of the Institute for Healthcare Improvement's Breakthrough Series Learning Collaborative model. Participating teams sought to implement evidence-informed recommendations to increase access.

Intervention Results: Learning collaborative teams successfully implemented all 4 of the recommendations in 95% of the participating sites. Patients who chose and received a most or moderately effective method increased from 22% to 38% in primary care, and from 0% to 17% in the immediate postpartum period. Patients who chose and received a long-acting-reversible contraceptive increased from 5% to 11% in primary care, and from 0% to 3% in immediate postpartum. Facilitating factors included the involvement of interdisciplinary teams, consideration of costs, utilization of peers to demonstrate change, and champions to drive change.

Conclusion: The application of evidence-informed recommendations using a structured quality improvement initiative increases contraceptive access.

Study Design: Pre-post intervention

Setting: New York City, NY

Sample Size: 17 organization representing 40 care delivery sites

Age Range: NA