Evaluation of Community Programs for Early Childhood Development: Parental Perspectives and Recommendations.

Objectives Optimal early childhood development is crucial for promoting positive child health outcomes. Community programs supporting child development are available throughout the United States but general parental perceptions of such programs are not well understood. This study aimed to examine parental perceptions of community programs for early childhood development in a semi-urban city of the US. Methods Data were collected from focus groups (n = 4) composed of English-fluent parents from the local community with at least one child aged 0-5 years. After generation of verbatim transcripts, data were analyzed by two independent coders in order to identify themes. Results Parental perceptions were categorized into four areas: (1) Utilization of community services, (2) Helpful aspects of community services, (3) Negative aspects of community services and (4) Parental recommendations for improved resource utilization. Helpful aspects identified included social and economic support, provision of parental education, and developmental screening and medical support. Negative aspects included utilization of standardized assessment tools, awareness of agencies and resources, and access to services. In order to improve resource utilization, parents suggested improved communication with parents and the child's medical home, transparency, and translation of program information into other languages. Conclusions For Practice Overall, participants felt that community programs that support early childhood development and parenting were helpful. However, community agencies can improve on communication with parents and medical providers as well as translation of program information.

Parents' adverse childhood experiences and mental health screening using home visiting programs: A pilot study.

BACKGROUND: Adverse childhood experiences (ACEs) are associated with adult high-risk behaviors and diseases. There is value in screening parents for ACEs given the repercussions parental ACEs may have on parenting behaviors and child development. The primary aim of this study was to assess the feasibility of parental ACE screening in the home setting. A secondary aim was to evaluate whether or not maternal ACEs correlated with maternal mental health measures. METHODS: Two home visiting programs that support early childhood development and conduct parental mental health screening implemented ACE screening for parents of infants <1 year of age. Descriptive statistics were produced for population surveillance of ACEs as well as standard practice screens for depression, anxiety, substance use, and intimate partner violence. Logistic models were used to examine associations between ACE score and mental health measures. RESULTS: A total of 110 parents completed the ACE screen. All possible ACE score outcomes were represented (0-10). A trend toward association of positive prenatal maternal depression screen with ACE score was identified (p = .05). CONCLUSION: This novel prospective home-based screening program for parental ACEs was feasible and identified a trend toward increasing ACE score association with positive prenatal maternal depression screen.

Adverse family experiences and obesity in children and adolescents in the United States.

While exposure to adverse family experiences (AFEs), subset of adverse childhood experiences (ACEs), has been associated with childhood obesity, less is known about the impact of exposures to each type of AFE. Using 2011-2012 National Survey of Children's Health data, we evaluated associations between exposure to individual AFEs and overweight/obesity status in children 10years or older, adjusting for socio-demographic factors. Caregivers reported their child's height, weight, and exposure to nine AFEs; body mass index (BMI) was classified by Center for Disease Control and Prevention's (CDC) guidelines. At Mayo Clinic, we calculated frequencies and weighted estimates of socio-demographic factors and AFEs. Unadjusted and adjusted weighted multinomial logistic regression models were employed to assess the independent associations of each AFE and the different AFE composite scores with BMI category. Exposure to two or more AFEs was independently associated with increased odds of overweight (odds ratio [OR], 1.33; 95% confidence interval [CI], 1.13, 1.56) and obese (OR, 1.45; 95% CI, 1.21, 1.73) status after adjustment for age, household income, parents' education-level, race and sex. Death of parent (OR, 1.59; 95% CI, 1.18, 2.15) and hardship due to family income (OR, 1.26; 95% CI, 1.06, 1.50) were independently associated with obesity status with adjustment for other AFEs and socio-demographic factors. Our results suggest that, in addition to cumulative exposure to AFEs, exposure to certain childhood experiences are more strongly associated with childhood obesity than others. Death of parent and hardship due to family income are individual AFEs, which are strongly predictive of obesity.

Effect of Electronic Health Record Prompts on the Frequency of Blood Lead Tests.

INTRODUCTION/OBJECTIVES: Elevated blood lead levels can cause impaired cognition and behavioral problems in children. Screening is important for identifying children with elevated blood lead levels, but many children who qualify for screening do not get tested. We aimed to see if the addition of prompts in the electronic health record (EHR) would lead to differences in blood lead tests ordered for children with government insurance. METHODS: In May 2018, a prompt was added to our institutional EHR that reminded primary care practitioners to recommend lead testing for patients with government insurance. For this retrospective observational pre-post comparative study, we reviewed the rate of blood lead test orders and completed collection before and after the prompt was introduced. RESULTS: The number of blood lead tests ordered did not increase after prompts were introduced in the EHR; rather, the lead screening rates at 12-month well-child visits decreased from 63.6% to 53.8% (P = .008). The 24-month visit data did not change significantly for the number of lead tests ordered before and after the prompt was introduced in the EHR. The number of lead tests completed showed a significant decrease after the prompt was introduced for the 12-month visit (P < .001) but no significant change for the 24-month visit (P = .70). CONCLUSIONS: This study showed that the addition of prompts in the EHR was not associated with an increase in the number of blood lead level tests ordered. Further research is needed to determine factors that could affect lead screening rates.

Development and Early Experience of a Primary Care Learning Collaborative in a Large Health Care System.

INTRODUCTION: Primary care clinicians are presented with hundreds of new clinical recommendations and guidelines. To consider practice change clinicians must identify relevant information and develop a contextual framework. Too much attention to information irrelevant to one's practice results in wasted resources. Too little results in care gaps. A small group of primary care clinicians in a large health system sought to address the problem of vetting new information and providing peer reviewed context. This was done by engaging colleagues across the system though a primary care learning collaborative. METHODS: The collaborative was a grass roots initiative between community and academic-based clinicians. They invited all the system's primary care clinicians to participate. They selected new recommendations or guidelines and used surveys as the principal communication instrument. Surveys shared practice experience and also invited members to give narrative feedback regarding their acceptance of variation in care relate to the topic. A description of the collaborative along with its development, processes, and evolution are discussed. Process changes to address needs during the COVID-19 pandemic including expanded information sharing was necessary. RESULTS: Collaborative membership reached across 5 states and included family medicine, internal medicine, and pediatrics. Members found involvement with the collaborative useful. Less variation in care was thought important for public health crises: the COVID pandemic and opioid epidemic. Greater practice variation was thought acceptable for adherence to multispecialty guidelines, such as diabetes, lipid management, and adult ADHD care. Process changes during the pandemic resulted in more communications between members to avoid practice gaps. CONCLUSION: An internet-based learning collaborative in a health system had good engagement from its members. Using novel methods, it was able to provide members with feedback related to the importance of new practice recommendations as perceived by their peers. Greater standardization was thought necessary when adopting measures to address public health crisis, and less necessary when addressing multispecialty guidelines. By employing a learning collaborative, this group was able to keep members interested and engaged. During the first year of the COVID pandemic the collaborative also served as a vehicle to share timely information.

Use of Community Based Participatory Research to Design Interventions for Healthy Lifestyle in an Alternative Learning Environment.

INTRODUCTION/OBJECTIVES: Childhood obesity develops as the result of the interplay between individual and environmental factors. Community based participatory research (CBPR) is an effective tool for improving health of communities. There is limited research on CBPR for facilitating healthy lifestyle in community schools with an alternative learning environment. The objective of the study was to explore student and staff perspectives via focus groups on barriers and facilitators for healthy eating and physical activity in a community school with alternative learning environment and to prioritize, design, and implement suggested interventions to improve healthy lifestyle. METHODS: We conducted qualitative research through 8 focus groups of middle and high school students (n = 40) and 2 focus groups of school staff (n = 8). The school community and research team subsequently identified and implemented interventions for facilitating healthy lifestyle in students within the school environment. RESULTS: Barriers identified for healthy lifestyle included lack of motivation, lack of healthy food options at school, inadequate knowledge about healthy lifestyle and insufficient opportunities for physical activity. Facilitators for healthy lifestyle were support and motivation from mentors and knowledge about healthy nutrition. Key strategies implemented were addition of healthier food options, educational materials for healthy eating, creation of a walk path, standing desks in classrooms and additional equipment in the school gymnasium. CONCLUSIONS: Formative feedback from students and staff was helpful in the implementation of strategies for facilitating healthy lifestyle among students within a community school with an alternative learning environment.

Impact of Point-of-Care Decision Support Tool on Laboratory Screening for Comorbidities in Children with Obesity.

BACKGROUND: Childhood obesity is associated with dyslipidemia, fatty liver disease, and type 2 diabetes. Expert guidelines recommend screening for these conditions in children with obesity. AIMS AND OBJECTIVES: The objective of the study was to compare rates of laboratory screening for dyslipidemia, fatty liver disease, and type 2 diabetes in children with obesity prior to and following implementation of a point-of-care decision support tool. METHODS: We performed a retrospective record review of children with body mass index (BMI) ≥95th percentile for age and gender (age 7-18 years) undergoing well-child/sports examination visits. Multivariable logistic regression models were used to adjust for patient and provider confounders. RESULTS: There was no increase in the rates of screening following implementation of the point-of-care decision support tool. Tests were more likely to be recommended in children with severe obesity and in females. CONCLUSIONS: The implementation of a point-of-care decision support tool was not associated with improvement in screening rates for dyslipidemia, fatty liver disease, and type 2 diabetes for children with obesity. Further strategies are needed to improve rates of screening for obesity-related comorbid conditions in children with obesity.

Temporal trends in lipid testing among children and adolescents: A population based study.

Unfavorable lipid levels during childhood are associated with subsequent development of atherosclerotic cardiovascular disease. The American Academy of Pediatrics and National Heart, Lung and Blood Institute in 2011 recommended universal lipid screening for children between ages 9-11 years and between ages 17-21 years. The objective of the study was to determine temporal trends in lipid testing among children and young adults in a mid-western population. The Rochester Epidemiology Project database was used to identify lipid testing in ages 2-21 years (n = 51,176) in the Olmsted County population from January 1, 2008 through December 31, 2014. Generalized estimating equations with Poisson distribution were used to test for temporal trends in lipid testing across the age groups. There was modest increase in lipid testing in children in the age groups, 9-11 years and 17-21 years (1.5% in 2008 to 2.2% in 2014, P < 0.001 and 4.4% in 2008 to 4.6% in 2014, P = 0.02, respectively). There was a significant decrease in proportion of 17-21 year olds with elevated total cholesterol (16.2% in 2008 to 11.6% in 2014; P = 0.01) and non-high density lipoprotein cholesterol (22.6% in 2008 to 12.6% in 2014; P < 0.001). In this population-based study, rates of lipid testing increased minimally only in the last six years. Further longitudinal studies are warranted to improve guideline dissemination and address attitudes, practices and barriers to lipid testing in children and young adults.

The effect of an automated point of care tool on diagnosis and management of childhood obesity in primary care.

BACKGROUND: Childhood obesity is underdiagnosed in primary care practices. Our study aimed to compare rates of documentation of diagnosis of obesity and counselling for nutrition and physical activity at an academic primary care practice prior to and following implementation of a body mass index (BMI)-based electronic point of care clinical reminder tool. METHODS: We performed a retrospective record review of children aged 2-18 years undergoing well child visits during any of three calendar years (2009, 2011 and 2013). The electronic clinical reminder tool was implemented in September 2010. Records of children with BMI > 95th percentile were electronically searched for terms of documentation of diagnosis of obesity and nutrition and physical activity counselling. Multivariable logistic regression models were used to adjust for potential patient and provider confounders. RESULTS: Among those with BMI ≥ 95th percentile, there was a statistically significant increase in documentation of diagnosis of obesity (45.5% in 2009 vs. 52.4% in 2011; P < 0.001; adjusted odds ratio 1.36; 95% CI 1.13-1.65) and in counselling for physical activity and nutrition (66.8% in 2009 vs. 75.2% in 2011; P < 0.001; adjusted odds ratio 1.33; 95% CI 1.06-1.66) following implementation of the tool. Compared with 2011, there was no statistically significant increase in documentation of obesity (50.4%) or nutrition and physical activity counselling (77.9%) in 2013. CONCLUSIONS: The implementation of a point of care clinical reminder tool was associated with improvement in documentation of diagnosis of obesity and counselling for nutrition and physical activity. Further studies are needed to determine the impact of these automated tools on weight outcomes in children.