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1.
Appl Clin Inform ; 11(2): 210-217, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-32187633

RESUMO

BACKGROUND: Primary care providers are tasked with the increasingly difficult job of addressing childhood obesity during clinic visits. Electronic medical record (EMR)-enabled decision-support tools may aid providers in this task; however, information is needed regarding whether providers perceive such tools to be useful for addressing nutrition and physical activity lifestyle behaviors. OBJECTIVES: This study aimed to evaluate the usefulness and usability of FitTastic, an EMR-enabled tool to support prevention and management of childhood obesity in primary care. METHODS: In this mixed-method study, we implemented the FitTastic tool in two primary-care clinics, then surveyed and conducted focused interviews with providers. Validated Technology Acceptance Model perceived usefulness and National Aeronautics and Space Administration (NASA) perceived usability survey questions were e-mailed to 60 providers. In-depth provider interviews with family medicine and pediatric physicians (n = 12) were used to further probe adoption of FitTastic. RESULTS: Surveys were completed by 73% of providers (n = 44). The mean score for FitTastic's usefulness was 3.3 (standard deviation [SD] = 0.54, scale 1-5, where 5 is strongly agree) and usability, 4.8 (SD = 0.86, scale 1-7, where 7 is strongly agree). Usefulness and usability scores were associated with intention to use FitTastic (correlation for both, p < 0.05). Data from provider interviews indicated that useful features of FitTastic included: standardizing the approach to childhood obesity, and facilitating conversations about weight management, without increasing cognitive workload. However, use of FitTastic required more time from nurses to input lifestyle data. CONCLUSION: FitTastic is perceived as a useful and usable EMR-based lifestyle behavior tool that standardizes, facilitates, and streamlines healthy lifestyle conversations with families. Perceived usability and usefulness scores correlated with provider intention-to-use the technology. These data suggest that EMR-based child obesity prevention and management tools can be feasible to use in the clinic setting, with potential for scalability. Usefulness can be optimized by limiting amount of time needed by staff to input data.


Assuntos
Atitude Frente aos Computadores , Registros Eletrônicos de Saúde , Pessoal de Saúde/psicologia , Obesidade Infantil , Atenção Primária à Saúde/estatística & dados numéricos , Humanos , Inquéritos e Questionários
2.
Hum Genome Var ; 3: 16012, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27340555

RESUMO

Small copy number variations (CNVs) have typically not been analyzed or reported in clinical settings and hence have remained underrepresented in databases and the literature. Here, we focused our investigations on these small CNVs using chromosome microarray analysis (CMA) data previously obtained from patients with atypical characteristics or disorders of sex development (DSD). Using our customized CMA track targeting 334 genes involved in the development of urogenital and reproductive structures and a less stringent analysis filter, we uncovered small genes with recurrent and overlapping CNVs as small as 1 kb, and small regions of homozygosity (ROHs), imprinting and position effects. Detailed analysis of these high-resolution data revealed CNVs and ROHs involving structural and functional domains, repeat elements, active transcription sites and regulatory regions. Integration of these genomic data with DNA methylation, histone modification and predicted RNA expression profiles in normal testes and ovaries suggested spatiotemporal and tissue-specific gene regulation. This study emphasized a DSD-specific and gene-targeted CMA approach that uncovered previously unanalyzed or unreported small genes and CNVs, contributing to the growing resources on small CNVs and facilitating the narrowing of the genomic gap for identifying candidate genes or regions. This high-resolution analysis tool could improve the diagnostic utility of CMA, not only in patients with DSD but also in other clinical populations. These integrated data provided a better genomic-epigenomic landscape of DSD and greater opportunities for downstream research.

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