www.mobilehealthmap.org 617‐442‐3200 New research shows that mobile health clinics improve health outcomes for hard to reach populations in cost‐effective and culturally competent ways . A Harvard Medical School study determined that for every dollar invested in a mobile health clinic, the US healthcare system saves $30 on average. Mobile health clinics, which offer a range of services from preventive screenings to asthma treatment, leverage their mobility to treat people in the convenience of their own communities. For example, a mobile health clinic in Baltimore, MD, has documented savings of $3,500 per child seen due to reduced asthma‐related hospitalizations. The estimated 2,000 mobile health clinics across the country are providing similarly cost‐effective access to healthcare for a wide range of populations. Many successful mobile health clinics cite their ability to foster trusting relationships. Qualitative research in such mobile health clinics has found that patients value the informal, familiar environment in a convenient location, with staff who “are easy to talk to,” and that the staff’s “marriage of professional and personal discourses” provides patients the space to disclose information themselves. A communications academic argued that mobile health clinics’ unique use of space is important in facilitating these relationships. Mobile health clinics park in the heart of the community in familiar spaces, like shopping centers or bus stations, which lend themselves to the local community atmosphere.

Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care

This paper reviews studies using empirical, data-driven methodologies, such as cluster analysis and latent class analysis, to identify clustering patterns of diet, physical activity and sedentary behavior among children or adolescents and their associations with socio-demographic indicators, and overweight and obesity.

The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review

Background: E-Learning is rapidly growing as an alternative way of delivering education in nursing. Two contexts regarding the use of e-learning in nursing are discussed in the literature: (1) education among nursing students and (2) nurses’ continuing education within a life-long learning perspective. A systematic review of systematic reviews on e-learning for nursing and health professional students in an academic context has been published previously; however, no such review exists regarding e-learning for registered nurses in a continuing education context. Objective: We aimed to systematically summarize the qualitative and quantitative evidence regarding the effects of e-learning on nursing care among nurses in a continuing education context. Methods: We conducted a systematic review of systematic qualitative, quantitative, and mixed-studies reviews, searching within four bibliographic databases. The eligibility criteria were formulated using the population, interventions, comparisons, outcomes, and study design (PICOS) format. The included population was registered nurses. E-Learning interventions were included and compared with face-to-face and any other e-learning interventions, as well as blended learning. The outcomes of interest were derived from two models: nursing-sensitive indicators from the Nursing Care Performance Framework (eg, teaching and collaboration) and the levels of evaluation from the Kirkpatrick model (ie, reaction, learning, behavior, and results). Results: We identified a total of 12,906 records. We retrieved 222 full-text papers for detailed evaluation, from which 22 systematic reviews published between 2008 and 2018 met the eligibility criteria. The effects of e-learning on nursing care were grouped under Kirkpatrick’s levels of evaluation: (1) nurse reactions to e-learning, (2) nurse learning, (3) behavior, and (4) results. Level 2, nurse learning, was divided into three subthemes: knowledge, skills, attitude and self-efficacy. Level 4, results, was divided into patient outcomes and costs. Most of the outcomes were reported in a positive way. For instance, nurses were satisfied with the use of e-learning and they improved their knowledge. The most common topics covered by the e-learning interventions were medication calculation, preparation, and administration. Conclusions: The effects of e-learning are mainly reported in terms of nurse reactions, knowledge, and skills (ie, the first two levels of the Kirkpatrick model). The effectiveness of e-learning interventions for nurses in a continuing education context remains unknown regarding how the learning can be transferred to change practice and affect patient outcomes. Further scientific, methodological, theoretical, and practice-based breakthroughs are needed in the fast-growing field of e-learning in nursing education, especially in a life-learning perspective. Clinical Trial: International Prospective Register of Systematic Reviews (PROSPERO) CRD42016050714; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=50714

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Effects of E-Learning in a Continuing Education Context on Nursing Care: Systematic Review of Systematic Qualitative, Quantitative, and Mixed-Studies Reviews

OBJECTIVES: We sought to evaluate the relationships between fetal growth restriction (FGR) (both severe and less severe) and assessments of cognitive, academic, and adaptive behavior brain function at age 10 years. METHODS: At age 10 years, the Extremely Low Gestational Age Newborns Cohort Study assessed the cognitive function, academic achievement, social-communicative function, psychiatric symptoms, and overall quality of life of 889 children born before 28 weeks’ gestation. A pediatric epileptologist also interviewed parents as part of a seizure evaluation. The 52 children whose birth weight z scores were z scores were between −2 and −1 were considered to have less severe FGR. RESULTS: The more severe the growth restriction in utero, the lower the level of function on multiple cognitive and academic achievement assessments performed at age 10 years. Growth-restricted children were also more likely than their extremely preterm peers to have social awareness impairments, autistic mannerisms, autism spectrum diagnoses, difficulty with semantics and speech coherence, and diminished social and psychosocial functioning. They also more frequently had phobias, obsessions, and compulsions (according to teacher, but not parent, report). CONCLUSIONS: Among children born extremely preterm, those with severe FGR appear to be at increased risk of multiple cognitive and behavioral dysfunctions at age 10 years, raising the possibility that whatever adversely affected their intrauterine growth also adversely affected multiple domains of cognitive and neurobehavioral development.

https://pediatrics.aappublications.org/content/pediatrics/140/5/e20170697.full.pdf

Neurodevelopment at Age 10 Years of Children Born <28 Weeks With Fetal Growth Restriction.

There is a lack of evidence regarding clusters of health-related behaviors among adolescents from low, lower-middle, and upper-middle income countries. This study aimed to identify clustering patterns of health-related behaviors (diet, physical activity [PA] and sedentary behavior [SB]) and association with sociodemographic variables among a population-based sample of Brazilian adolescents. Cross-sectional data from the 2015 National School-Based Health Survey (PeNSE). A total of 102,072 (females: 51.7%) students in ninth-grade (age: 14.3 ± 1.1 years-old) enrolled in public and private schools were investigated in this study. Healthy and unhealthy diet, PA and SB were measured using a validated questionnaire. Two-step cluster analysis was conducted to identify lifestyle patterns. The methodology for complex analysis and weighting was used to inferential statistical procedures. Multinomial logistic regression assessed associations between sociodemographic factors and the clusters. Three reliable and meaningful clusters were identified and labelled as follows: (1) health-promoting SB and diet (32.6%); (2) health-promoting PA and diet (44.9%), and (3) health-risk (22.5%). Compared to boys, girls were less likely to be in clusters 1 (OR = 0.85; 95% CI = 0.78–0.93, p < 0.001) and 2 (OR = 0.43; 95% CI = 0.40–0.46, p < 0.001) than the health-risk cluster. Higher socioeconomic status was positively associated with health-promoting PA and diet, and negatively related to health-promoting SB and diet. Older adolescents were more likely to be in cluster 1 than in cluster 3, compared to younger adolescents. Approximately one-quarter of the population (health-risk cluster) reported engaging in multiple risk behaviors. Interventions may need to be tailored to specific adolescent groups, especially considering sociodemographic differences.

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Clustering of diet, physical activity and sedentary behavior among Brazilian adolescents in the national school - based health survey (PeNSE 2015)

Early Initiation of Newborn Individualized Developmental Care and Assessment Program (NIDCAP) Reduces Length of Stay: A Quality Improvement Project

Background

Healthcare providers use continuing education (CE) to meet professional development requirements and to ensure optimal patient care. There has been a dramatic increase in computer-mediated CE (CMCE) programs.



Aims

To synthesize the literature regarding the current state of the science on the efficacy of CMCE for healthcare professionals, particularly as it relates to provider learning and patient outcomes. Specifically, this review assesses the methodological quality of existing systematic reviews and meta-analyses.



Methods

A literature search was conducted using Cochrane Library, PubMed, and CINAHL. Review articles evaluating the efficacy of CMCE for healthcare providers were included. Publications were searched between 2002 and 2013 and limited to those printed in English. An objective measurement tool, AMSTAR, was used to assess the methodological quality of each review. AMSTAR is an 11-item instrument, in which individual criteria were evaluated and a composite score of all 11 components was determined for each review. Outcomes of each review were also categorized based on Kirkpatrick's levels for summative evaluation: (i) Learner satisfaction, (ii) Learning outcomes, (iii) Performance improvement, (iv) Patient/health outcomes.



Results

Starting with 231 articles, 11 met the inclusion criteria for this evaluation. AMSTAR quality scores of the reviews ranged from 7 to 11, with 11 indicating the strongest quality. Although weak research design of many studies and heterogeneous topics covered make summative evaluations difficult, there were some common themes covered in the articles reviewed. Healthcare providers were largely satisfied with using CMCE programs. Overall, the studies comparing CMCE to traditional CE methods found the impact on learning outcomes to be comparable, with neither method necessarily superior. Additionally, all reviews lacked evaluation of practice outcomes.



Linking Evidence to Action

While results of this review show promise for CMCE, further evaluation and more rigorously conducted research is necessary. Particular focus is needed to determine the effects of CMCE on health outcomes.

A methodological quality synthesis of systematic reviews on computer-mediated continuing education for healthcare providers.

Using the Technology Acceptance Model to Develop StartSmart: mHealth for Screening, Brief Intervention, and Referral for Risk and Protective Factors in Pregnancy.

Characterization of Childhood Obesity and Behavioral Factors.

Objective The purpose of this study was to evaluate school-based health center (SHBC) provider adherence to guidelines for identification and assessment of childhood obesity after participation in a virtual Health Disparities Learning Collaborative with and without HeartSmartKids™, decision-support technology with tailored patient education.

Design and Setting A cluster randomized comparative effectiveness trial was conducted with 24 SBHCs from six states.

Participants The sample consisted of 33 SBHC providers and review of medical charts at three time points. Chart data were collected at baseline ( n = 850), after training ( n = 691) and 6 months after training ( n = 612).

Main Outcome Measures Charts from a random sample of youth 5–12 years making well-child visits were examined for the documentation of: BMI percentile, accurate weight diagnosis based upon BMI percentile, blood pressure percentile, and ordering appropriate laboratory assessment of obese youth ≥10 years old.

Results Percentage of overweight/obese children in this study was 40.4–47.2%. For both the HeartSmartKids™ and non-HeartSmartKids™ groups, provider adherence significantly improved after training for BMI percentile and blood pressure percentile documentation, as well as correct diagnosis for overweight and obese. Implementation of the HeartSmartKids™ was variable at the technology sites and differences in identification and assessment were not found between groups.

Conclusion The virtual collaborative approach to quality improvement resulted in improved adherence to guidelines for identification and assessment of overweight/obese children. The impact of the training with and without HeartSmartKids™ on patient outcomes needs to be evaluated. Coaching on implementation of technology needs to be included in future work.

Heather Aldrich

Papers

Early Initiation of Newborn Individualized Developmental Care and Assessment Program (NIDCAP) Reduces Length of Stay: A Quality Improvement Project

A methodological quality synthesis of systematic reviews on computer-mediated continuing education for healthcare providers.

Using the Technology Acceptance Model to Develop StartSmart: mHealth for Screening, Brief Intervention, and Referral for Risk and Protective Factors in Pregnancy.

Characterization of Childhood Obesity and Behavioral Factors.

Virtual obesity collaborative with and without decision-support technology