17 research outputs found
Perceptions of preparedness: How hospital-based orientation can enhance the transition from academic to clinical learning.
Background: Clinical placements are essential for applied learning experiences in health professions education. Unfortunately, there is little consensus on how best to prepare learners for the transition between academic and clinical learning. We explored learners’ perceptions of hospital-based orientation and resulting preparedness for clinical placement.
Methods: Sixty-three learners participated in a total of 18 semi-structured focus groups, during their clinical placements. Data were analyzed thematically.
Results: We organized learners’ perceptions of hospital-based orientation that support their preparedness for placement into three themes: (1) adequate site orientation for learner acquisition of organization acumen and (2) clinical preceptor training to support unit/service and (3) individual components.
Conclusion: Thoughtful attention to hospital-based orientation can support learners in transitioning from academic to clinical learning. Hospital organizations should attend to all three components during orientation to better support learners’ preparedness for clinical learning
An efficient approach for surveillance of childhood diabetes by type derived from electronic health record data: the SEARCH for Diabetes in Youth Study
Objective To develop an efficient surveillance approach for childhood diabetes by type across 2 large US health care systems, using phenotyping algorithms derived from electronic health record (EHR) data
Use of administrative and electronic health record data for development of automated algorithms for childhood diabetes case ascertainment and type classification: the SEARCH for Diabetes in Youth Study
The performance of automated algorithms for childhood diabetes case ascertainment and type classification may differ by demographic characteristics
Assessing the Clinical Competence of Health Care Professionals Who Perform Airway Suctioning in Adults
MicroRNA regulatory network as biomarkers of late seizure in patients with spontaneous intracerebral hemorrhage
Approximately 15% of patients experience seizures after spontaneous intracerebral hemorrhage (ICH). The pathogenesis of seizures post-ICH is not well-known; however, iron deposition–related neuronal injury following hemoglobin breakdown may contribute. Profiling known miRNAs to identify biomarkers for post-ICH late seizures, we found 64 differentially expressed miRNA: 32 upregulated and 32 downregulated in seizure vs. non-seizure. Functional classification of upregulated miRNA for KEGG pathways and biological processes identified enrichment for cell cycle, protein modifications, and FoxO neurotrophin signaling pathways. No significant enrichment was found for downregulated miRNA. Molecular functions Gene Ontology (GO) terms enriched for upregulated miRNA are numerous, while downregulated miRNAs were associated with ion channel activity. RT-PCR confirmed two miRNAs, 4317 and 4325, were differentially expressed in patients who developed seizures at 1\ua0year. MiR-4317 regulates SLC38A1, a glutamine–glutamate transporter. Integrated miRNA–mRNA network analysis identified COMMD6, APOBEC2, and RASSF6—involved in NF-kB regulation. Two miRNAs (miR-4317 and 4325) differentiated post-ICH late seizures vs. non-seizures at 1\ua0year. The results suggest functional and miRNA–mRNA networks as potential biomarkers for post-ICH late seizures
Lessons learned in preparing for and responding to the early stages of the COVID-19 pandemic: one simulation’s program experience adapting to the new normal
Abstract
Use of simulation to ensure an organization is ready for significant events, like COVID-19 pandemic, has shifted from a “backburner” training tool to a “first choice” strategy for ensuring individual, team, and system readiness. In this report, we summarize our simulation program’s response during the COVID-19 pandemic, including the associated challenges and lessons learned. We also reflect on anticipated changes within our program as we adapt to a “new normal” following this pandemic. We intend for this report to function as a guide for other simulation programs to consult as this COVID-19 crisis continues to unfold, and during future challenges within global healthcare systems. We argue that this pandemic has cemented simulation programs as fundamental for any healthcare organization interested in ensuring its workforce can adapt in times of crisis. With the right team and set of partners, we believe that sustained investments in a simulation program will amplify into immeasurable impacts across a healthcare system
Efficient Surveillance of Childhood Diabetes Using Electronic Health Record Data
We aimed to develop an efficient surveillance approach for childhood diabetes. We analyzed EHR data from two independent US academic health care systems. Presumptive diabetes cases were identified as those having >1 of the five diabetes indicators in the past 3.5 years. EHRs of the presumptive cases were manually reviewed. We developed a stepwise surveillance approach using billing codes-based pre-specified algorithms and targeted manual EHRs review. The sensitivity and positive predictive value in both systems were approximately >90%. This stepwise surveillance approach resulted in a >70% reduction in the number of cases requiring manual validation compared to traditional surveillance methods
Efficient Surveillance of Childhood Diabetes Using Electronic Health Record Data
We aimed to develop an efficient surveillance approach for childhood diabetes. We analyzed EHR data from two independent US academic health care systems. Presumptive diabetes cases were identified as those having >1 of the five diabetes indicators in the past 3.5 years. EHRs of the presumptive cases were manually reviewed. We developed a stepwise surveillance approach using billing codes-based pre-specified algorithms and targeted manual EHRs review. The sensitivity and positive predictive value in both systems were approximately >90%. This stepwise surveillance approach resulted in a >70% reduction in the number of cases requiring manual validation compared to traditional surveillance methods