Principles for Primary Care Screening in the Context of Population Health.

A key component of primary care pediatrics is health promotion through screening: applying a test or procedure to detect a previously unrecognized disease or disease risk. How do we decide whether to screen? In 1965, Wilson and Jungner published an influential set of screening principles focused on the health problem's importance, the screening tool's performance, and the evidence for treatment efficacy. However, if we want realistic estimates of the population effects of routine screening, we must also account for the health care system's real-world functioning and disparities in care. We offer revised principles to guide discussions about routine screening in the primary care setting. We add to Wilson and Jungner's principles: 1. A focus on life course epidemiology and its consequences for population health, 2. A need to screen for the early stages of chronic health problems, 3. A concern for screening's acceptability to providers and the community, 4. A recommendation for estimating the uncertainty in benefits and harms in evaluating screening, 5. Inclusion of systematic plans for population data collection and monitoring, and 6. Recognition that achieving population health improvement requires a high-performing system with sufficient throughput and monitoring to deliver accessible, affordable, and effective care, especially for the groups experiencing the greatest inequities in access. Above all, instead of assuming best practices in treatment delivery and monitoring after screening, we argue for realism about the health care system functioning in routine practice.

Learning competing risks across multiple hospitals: one-shot distributed algorithms.

OBJECTIVES: To characterize the complex interplay between multiple clinical conditions in a time-to-event analysis framework using data from multiple hospitals, we developed two novel one-shot distributed algorithms for competing risk models (ODACoR). By applying our algorithms to the EHR data from eight national children's hospitals, we quantified the impacts of a wide range of risk factors on the risk of post-acute sequelae of SARS-COV-2 (PASC) among children and adolescents. MATERIALS AND METHODS: Our ODACoR algorithms are effectively executed due to their devised simplicity and communication efficiency. We evaluated our algorithms via extensive simulation studies as applications to quantification of the impacts of risk factors for PASC among children and adolescents using data from eight children's hospitals including the Children's Hospital of Philadelphia, Cincinnati Children's Hospital Medical Center, Children's Hospital of Colorado covering over 6.5 million pediatric patients. The accuracy of the estimation was assessed by comparing the results from our ODACoR algorithms with the estimators derived from the meta-analysis and the pooled data. RESULTS: The meta-analysis estimator showed a high relative bias (∼40%) when the clinical condition is relatively rare (∼0.5%), whereas ODACoR algorithms exhibited a substantially lower relative bias (∼0.2%). The estimated effects from our ODACoR algorithms were identical on par with the estimates from the pooled data, suggesting the high reliability of our federated learning algorithms. In contrast, the meta-analysis estimate failed to identify risk factors such as age, gender, chronic conditions history, and obesity, compared to the pooled data. DISCUSSION: Our proposed ODACoR algorithms are communication-efficient, highly accurate, and suitable to characterize the complex interplay between multiple clinical conditions. CONCLUSION: Our study demonstrates that our ODACoR algorithms are communication-efficient and can be widely applicable for analyzing multiple clinical conditions in a time-to-event analysis framework.

Rural-urban differences in social and emotional protective factors and their association with child health and flourishing.

BACKGROUND: Children in rural communities experience higher mortality rates and less access to health care services than those in urban communities. Protective factors like social support also vary by geography, but their contribution to differences in child health is understudied. Understanding geographic variation in protective health factors could provide insight into their impact on health and guide future intervention strategies. RESEARCH OBJECTIVE: To examine protective factors' association with child flourishing and child health status in rural and urban communities. METHODS: Publicly available data from the National Survey of Children's Health, 2018-2021, with nonmissing geographic data (N = 150,493) were used to assess the relationship between protective factors and child flourishing and health by rurality. Multivariate survey-weighted probit models examined these relationships, adjusting for child and caregiver characteristics. FINDINGS: More than a third of children were not flourishing, according to parental report. An estimated 62% of rural children were flourishing compared to 66% of urban children (P<0.001). Urban caregivers also were more likely to report better adult mental and physical health status. Nevertheless, rural children were reported to receive more social support than urban children, while their caregivers reported more emotional support and living in supportive and safe neighborhoods (P<0.001). Rural caregivers reported more support from places of worship and less from counselors/other mental health care providers than urban caregivers. CONCLUSIONS: Despite higher reported caregiver emotional support and child social support, fewer rural children are flourishing. Health systems and community organizations able to leverage these existing social and emotional protective factors in rural communities could help close this gap.

Social Needs as a Risk Factor for Positive Postpartum Depression Screens in Pediatric Primary Care.

OBJECTIVE: The goal of this study was to examine the association between self-reported social needs and postpartum depression (PPD) symptoms of mothers screened in pediatric primary care clinics. METHODS: This retrospective cohort study used electronic health record data from 3616 pediatric patients (age 0-6 months), whose mothers completed the Edinburgh Postpartum Depression Scale (EPDS) and a social needs screening in a large pediatric primary care network between April 2021 and February 2022. Mothers were screened for four self-reported social needs (food, housing, transportation, and utilities). Logistic regression evaluated the association between the report of any social need and a positive EPDS screen (≥ 10), adjusting for demographic and clinical characteristics and ZIP code-level poverty. RESULTS: Overall, 8.6% of mothers screened positive for PPD and 10.0% reported any social needs. The odds of a positive depression screen were significantly higher among mothers who reported any social need compared to those not reporting a social need (OR 4.18, 95% CI 3.11-5.61). The prevalence of all depressive symptoms on the EPDS was significantly higher among those who reported any social need, relative to those reporting no needs. Mothers reporting any social needs were significantly more likely to report thoughts of self-harm (6.9% vs 1.5%, P < .005). CONCLUSIONS: Self-report of social need was significantly associated with positive PPD screens during infant well-child visits. Social needs may be a target of future interventions addressing PPD in pediatric settings. Improving care for social needs may have added benefit of alleviating the risk of PPD.

Collection of biospecimens from parent-child dyads in a community garden-based nutrition intervention: protocol and feasibility.

BACKGROUND: Non-invasive human biospecimens, including stool, urine, and hair, are important in understanding the relationship between diet and changes in human physiologic processes that affect chronic disease outcomes. However, biospecimen collection can be difficult when collecting samples for research studies that occur away from a centralized location. We describe the protocol and feasibility in collecting stool, urine, and hair biospecimens from parents and their children at a remote location as a part of a summer community garden-based intervention. METHODS: Stool, urine, and hair were collected as a part of the Summer Harvest Adventure (SHA) study, a randomized controlled, community garden-based intervention targeting children (ages 8-11 years) and their parents from low-resource neighborhoods. Biospecimens were collected from willing children and/or their parent/adult caregivers at baseline and post-intervention for evaluation of microbiome, metabolomics, and hair analyses among both intervention and control groups at a location distant from the academic laboratories conducting the analysis. The protocol used to assemble, deliver, collect, and process biospecimens are presented along with the frequencies with which specimens were successfully obtained. RESULTS: One hundred forty six participants (73 parent-child dyads) were part of the larger SHA study and thus eligible to provide a biospecimen. A total of 126 participants, 115 participants, and 127 participants consented to provide their hair, stool and urine samples, respectively. Of the participants that consented to provide a sample, 44 children (69.8%) and 38 parents (60.3%) provided at least one hair sample, 27 children (48.2%) and 37 parents (62.7%) provided at least one stool sample, and 36 children (57.1%) and 42 parents (65.6%) provided at least one urine sample. Sample collection at the offsite location, transport, and handling at the academic center were successful and all biospecimens were deemed adequate for analyses. DNA and metabolomics yield on a subset of stool samples obtained provided excellent results in terms of an abundance of species and metabolities, as would be predicted. Urine and hair analyses are underway. CONCLUSION: Our work is one of the first to describe the feasibility of collecting human biospecimens, specifically stool, urine, and hair, from both parents and their children from low-resourced neighborhoods in a non-traditional garden research setting. Future work will report findings related to mechanisms between diet, microbiome, metabolites, and clinical outcomes.