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INTRODUCTION: Does telehealth decrease health disparities by improving connections to care or simply result in new barriers for vulnerable populations who often lack access to technology? This study aims to better understand the role of telehealth and social determinants of health in improving care connections and outcomes for Community Health Center patients with diabetes. METHODS: This retrospective analysis of Electronic Health Record (EHR) data examined the relationship between telehealth utilization and glycemic control and consistency of connection to the health care team ("connectivity"). EHR data were collected from 20 Community Health Centers from July 1, 2019 through December 31, 2021. Descriptive statistics were calculated, and multivariable linear regression was used to assess the associations between telehealth use and engagement in care and glycemic control. RESULTS: The adjusted analysis found positive, statistically significant associations between telehealth use and each of the 2 primary outcomes. Telehealth use was associated with 0.89 additional months of hemoglobin A1c (HbA1c) control (95% confidence interval [CI], 0.73 to 1.04) and 4.49 additional months of connection to care (95% CI, 4.27 to 4.70). DISCUSSION: The demonstrated increased engagement in primary care for telehealth users is significant and encouraging as Community Health Center populations are at greater risk of lapses in care and loss to follow up. CONCLUSIONS: Telehealth can be a highly effective, patient-centered form of care for people with diabetes. Telehealth can play a critical role in keeping vulnerable patients with diabetes connected to their care team and involved in care and may be an important tool for reducing health disparities.
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Centros Comunitários de Saúde , Diabetes Mellitus , Hemoglobinas Glicadas , Telemedicina , Humanos , Telemedicina/estatística & dados numéricos , Centros Comunitários de Saúde/estatística & dados numéricos , Centros Comunitários de Saúde/organização & administração , Estudos Retrospectivos , Masculino , Feminino , Pessoa de Meia-Idade , Diabetes Mellitus/terapia , Hemoglobinas Glicadas/análise , Idoso , Registros Eletrônicos de Saúde/estatística & dados numéricos , Adulto , Determinantes Sociais da Saúde , Controle Glicêmico/estatística & dados numéricos , Acessibilidade aos Serviços de Saúde/estatística & dados numéricosRESUMO
Three-dimensional echocardiography (3DE) imaging has permitted advancements in the quantification of left ventricular (LV) and right ventricular (RV) volumes and ejection fraction. We evaluated the availability of 3DE equipment / analysis software, the integration of 3DE assessment of the LV and RV in routine clinical practice, current training provisions in 3DE, and aimed to ascertain barriers preventing the routine use of 3DE for volumetric analysis. Through the British Society of Echocardiography (BSE) regional representatives' network, echocardiographers were invited to participate in an open online survey. A total of 181 participants from echocardiography departments in the United Kingdom (UK), the majority from tertiary centres (61%), completed the 28-question survey. For 3DE quantification, 3DE-LV was adopted more frequently than 3DE-RV (48% vs 11%, respectively). Imaging feasibility was a recognised factor in 3DE RV and LV adoption. Many respondents had access to 3D probes (93%). The largest observed barriers to 3DE routine use were training deficiencies, with 83% reporting they would benefit from additional training opportunities and the duration of time permitted for the scan, with 68% of responders reporting allowances of less than the BSE standard of 45-60 min per patient (8% < 30-min). Furthermore, of those respondents who had undertaken professional accreditation, competence in 3DE was not formally assessed in 89%. This UK survey also reported good accessibility to magnetic resonance imaging (72%), which was related to overall 3DE adoption. In summary, although 3DE is now readily available, it remains underutilised. Further training opportunities, integrated formal assessment, improved adoption of BSE minimum recommended scanning times, alongside industry and societal support, may increase 3DE utilisation in routine practice.
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Clinical workflows that prioritize repetitive patient intake screening to meet performance metrics may have unintended consequences. This retrospective analysis of electronic health record data from 24 Federally Qualified Health Centers assessed effectiveness and accuracy of the 2-item Patient Health Questionnaire (PHQ-2) for depression screening and Generalized Anxiety Disorder 2 (GAD-2) for anxiety screening from 2019 to 2021. Scores of over 91% of PHQ-2 and GAD-2 tests indicated low likelihood of depression or anxiety, which diverged markedly from published literature on screening outcomes. Visit-based screenings linked to performance metrics may not be delivering the intended value in a real-world setting and risk distracting clinical effort from other high value activities.
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Transtornos de Ansiedade , Ansiedade , Humanos , Estudos Retrospectivos , Inquéritos e Questionários , Transtornos de Ansiedade/diagnóstico , Ansiedade/diagnóstico , Depressão/diagnósticoRESUMO
Recent advances in analysis of fMRI have established the existence of functional sub-networks in the human brain that are active during the performance of visual, motor, language, and other tasks. We describe two computational methods of delineating functional sub-networks that are active when an individual performs an approach-avoidance paradigm. The paradigm consisted of presentation of images of pleasant and unpleasant faces that were shown to nine volunteers for 10 seconds after a preceding rest period of 50 seconds during which a green computer screen was displayed. The subjects were instructed to squeeze a ball with their right hand if they judged the face to be unpleasant, in which case the unpleasant face would disappear. An fMRI BOLD activation was created and used as input for two different kinds of clustering method: The MCODE algorithm based on graph-theoretical analysis and a Conscious Self-Organizing Map (CSOM). Clustering obtained with both methods was based on the temporal variations of the fMRI BOLD signal activity. Both methods identified distinct regions in the brain which were separated by long-range connections. The MCODE algorithm was supplied with time-courses for activated voxels when performing the paradigm, while the CSOM clustering used all voxels in the brain. Both yielded similar clusters for activated voxels. The combination of MCODE and CSOM presents a new approach in identifying functional subunits in the human brain and warrants further investigation into the subject.