Dataset Information

Identifying and prioritising technical procedures for simulation-based curriculum in paediatrics: a Delphi-based general needs assessment.

ABSTRACT: Objectives:To identify and prioritise technical procedures that should be integrated in a curriculum of simulation-based procedural training in paediatrics using the Delphi method. Study design:National general needs assessment using a Delphi process was completed among 93 key opinion leaders in paediatrics in Denmark. Delphi round 1 identified technical procedures. Round 2 explored frequency of procedures, number of paediatricians performing the procedures, risks and/or discomfort for patients and feasibility for simulation-based training. Round 3 included final elimination and reprioritisation. Results:Response rates in the Delphi rounds were 73%, 71% and 72%. We identified 37 procedures in Delphi round 1, preprioritised in round 2, resulting in a final list of 19 procedures in round 3. Strong correlation between the prioritisation from the second and third Delphi rounds was identified, Spearman's r of 0.94 (p<0.0001). Top five on the final list were acute neonatal airway management, acute non-neonatal airway management, non-neonatal peripheral intravenous and intraosseous access, neonatal vascular access and advanced heart lung resuscitation. Conclusion:We identified and prioritised 19 technical procedures in paediatrics that are suitable for simulation and may be used as a guide for the development of simulation-based curriculum in paediatrics.

SUBMITTER: Thim S

PROVIDER: S-EPMC7437683 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identifying and prioritising technical procedures for simulation-based curriculum in paediatrics: a Delphi-based general needs assessment.

Thim Signe S Nayahangan Leizl Joy LJ Paltved Charlotte C Jensen Rune Dall RD Konge Lars L Hertel Niels Thomas NT Balslev Thomas T

BMJ paediatrics open 20200818 1

<h4>Objectives</h4>To identify and prioritise technical procedures that should be integrated in a curriculum of simulation-based procedural training in paediatrics using the Delphi method.<h4>Study design</h4>National general needs assessment using a Delphi process was completed among 93 key opinion leaders in paediatrics in Denmark. Delphi round 1 identified technical procedures. Round 2 explored frequency of procedures, number of paediatricians performing the procedures, risks and/or discomfor ...[more]

PMID: 32844123

Similar Datasets

Project description:Background and needsMedical educators with simulation fellowship training have a unique skill set. Simulation fellowship graduates have the ability to handle basic and common troubleshooting issues with simulation software, hardware, and equipment setup. Outside of formal training programs such as this, simulation skills are inconsistently taught and organically learned. This is important to address because there are high expectations of medical educators who complete simulation fellowships. To fill the gap, we offer one way of teaching and assessing simulation technical skills within a fellowship curriculum and reflect on lessons learned throughout the process. This report describes the instructional designs, implementation, and program evaluation of an educational intervention: a simulation technology curriculum for simulation fellows.Curriculum designThe current iteration of the simulation technical skill curriculum was introduced in 2018 and took approximately 8 months to develop under the guidance of expert simulation technology specialists, simulation fellowship-trained faculty, and simulation center administrators. Kern's six steps to curriculum development was used as the guiding conceptual framework. The curriculum was categorized into four domains, which emerged from the outcome of a qualitative needs assessment. Instructional sessions occurred on 5 days spanning a 2-week block. The final session concluded with summative testing.Program evaluationFellows were administered summative objective structured exams at three stations. The performance was rated by instructors using station-specific checklists. Scores approached 100% accuracy/completion for all stations.ConclusionsThe development of an evidence-based educational intervention, a simulation technical skill curriculum, was highly regarded by participants and demonstrated effective training of the simulation fellows. This curriculum serves as a template for other simulationists to implement formal training in simulation technical skills.

Project description:BackgroundIdentifying locally relevant and agreed-upon priorities for improving young people's mental health, aligned with social and environmental factors, is essential for benefiting target communities. This paper describes a participatory approach to engage young people and professionals in identifying such priorities, whilst considering the social determinants related to them.MethodsWe utilised a community-based participatory approach to support young people and professionals in identifying, reviewing, refining, and prioritising, locally relevant opportunity areas that are crucial for understanding and addressing social determinants of young people's mental health. We adopted a flexible five-stage process, which enabled greater reflection and adaptation in response to young people's and professionals' feedback and reflections.ResultsOver seven months, we engaged with young people and professionals in Northern Devon, (a rural area in southwest England), involving over 290 individuals to identify locally relevant priorities for supporting young people's mental health. Three priorities were identified for subsequent exploration using co-design approaches: (1) identity and belonging; (2) mental health awareness and literacy; and (3) diverse opportunities (for education, employment and leisure). The engagements suggested that designing initiatives and strategies in these areas could contribute to improvements in young people's mental health.ConclusionYoung people in Northern Devon prioritised three themes for the next phase of the Kailo Programme-mental health literacy, access to diverse careers and employment opportunities, and identity and belonging within their communities. Rural communities face unique barriers associated with these issues, related to less diverse populations, lack of access to reliable and affordable transport and local industries, and seasonal working. The perceived neglect by authorities towards rural young people has resulted in a lack of activities and opportunities catering to their specific needs, compared to urban areas. Although the government has recognised the need to address these disparities, community members suggest that there is still more work to be done.

Project description:OBJECTIVES:Healthcare is a complex system, so quality improvement will commonly lead to unintended consequences which are rarely evaluated. In previous qualitative work, we proposed a framework for considering the range of these potential consequences, in terms of their desirability and the extent to which they were predictable or expected during planning. This paper elaborates on the previous findings, using consensus methods to examine what consequences should be identified, why and how to prioritise, evaluate and interpret all identified consequences, and what stakeholders should be involved throughout this process. DESIGN:Two-round modified Delphi consensus study. SETTING AND PARTICIPANTS:Both rounds were completed by 60 panellists from an academic, clinical or management background and experience in designing, implementing or evaluating quality improvement programmes. RESULTS:Panellists agreed that trade-offs (expected undesirable consequences) and unpleasant surprises (unexpected undesirable consequences) should be actively considered. Measurement of harmful consequences for patients, and those with high workload or financial impact was prioritised, and their evaluation could also involve the use of qualitative methods. Clinical teams were agreed as important to involve at all stages, from identifying potential consequences, prioritising which of those to systematically evaluate, undertaking appropriate evaluation and interpreting the findings. Patients were necessary in identifying consequences, managers in identifying and prioritising, and improvement advisors in interpreting the data. CONCLUSION:There was consensus that a balanced approach to considering all the consequences of improvement can be achieved by carefully considering predictable trade-offs from the outset and deliberately pausing after implementation to identify any unexpected surprises and make an informed decision as to whether quantitative or qualitative evaluation is needed and feasible. Stakeholders' roles in in the process of identifying, prioritising, evaluating and interpreting potential consequences should be explicitly addressed within planning and revisited during and after implementation.

Project description:ObjectivesPediatric training is an essential component of emergency medicine (EM) residency. The heterogeneity of pediatric experiences poses a significant challenge to training programs. A national simulation curriculum can assist in providing a standardized foundation of pediatric training experience to all EM trainees. Previously, a consensus-derived set of content for a pediatric curriculum for EM was published. This study aimed to prioritize that content to establish a pediatric simulation-based curriculum for all EM residency programs.MethodsSeventy-three participants were recruited to participate in a three-round modified Delphi project from 10 stakeholder organizations. In round 1, participants ranked 275 content items from a published set of pediatric curricular items for EM residents into one of four categories: definitely must, probably should, possibly could, or should not be taught using simulation in all residency programs. Additionally, in round 1 participants were asked to contribute additional items. These items were then added to the survey in round 2. In round 2, participants were provided the ratings of the entire panel and asked to rerank the items. Round 3 involved participants dichotomously rating the items.ResultsA total of 73 participants participated and 98% completed all three rounds. Round 1 resulted in 61 items rated as definitely must, 72 as probably should, 56 as possibly could, 17 as should not, and 99 new items were suggested. Round 2 resulted in 52 items rated as definitely must, 91 as probably should, 120 as possibly could, and 42 as should not. Round 3 resulted in 56 items rated as definitely must be taught using simulation in all programs.ConclusionsThe completed modified Delphi process developed a consensus on 56 pediatric items that definitely must be taught using simulation in all EM residency programs (20 resuscitation, nine nonresuscitation, and 26 skills). These data will serve as a targeted needs assessment to inform the development of a standard pediatric simulation curriculum for all EM residency programs.

Project description:ImportanceTo better elucidate the role of artificial intelligence (AI) in surgical skills training requires investigations in the potential existence of a hidden curriculum.ObjectiveTo assess the pedagogical value of AI-selected technical competencies and their extended effects in surgical simulation training.Design, setting, and participantsThis cohort study was a follow-up of a randomized clinical trial conducted at the Neurosurgical Simulation and Artificial Intelligence Learning Centre at the Montreal Neurological Institute, McGill University, Montreal, Canada. Surgical performance metrics of medical students exposed to an AI-enhanced training curriculum were compared with a control group of participants who received no feedback and with expert benchmarks. Cross-sectional data were collected from January to April 2021 from medical students and from March 2015 to May 2016 from experts. This follow-up secondary analysis was conducted from June to September 2022. Participants included medical students (undergraduate year 0-2) in the intervention cohorts and neurosurgeons to establish expertise benchmarks.ExposurePerformance assessment and personalized feedback by an intelligent tutor on 4 AI-selected learning objectives during simulation training.Main outcomes and measuresOutcomes of interest were unintended performance outcomes, measured by significant within-participant difference from baseline in 270 performance metrics in the intervention cohort that was not observed in the control cohort.ResultsA total of 46 medical students (median [range] age, 22 [18-27] years; 27 [59%] women) and 14 surgeons (median [range] age, 45 [35-59] years; 14 [100%] men) were included in this study, and no participant was lost to follow-up. Feedback on 4 AI-selected technical competencies was associated with additional performance change in 32 metrics over the entire procedure and 20 metrics during tumor removal that was not observed in the control group. Participants exposed to the AI-enhanced curriculum demonstrated significant improvement in safety metrics, such as reducing the rate of healthy tissue removal (mean difference, -7.05 × 10-5 [95% CI, -1.09 × 10-4 to -3.14 × 10-5] mm3 per 20 ms; P < .001) and maintaining a focused bimanual control of the operative field (mean difference in maximum instrument divergence, -4.99 [95% CI, -8.48 to -1.49] mm, P = .006) compared with the control group. However, negative unintended effects were also observed. These included a significantly lower velocity and acceleration in the dominant hand (velocity: mean difference, -0.13 [95% CI, -0.17 to -0.09] mm per 20 ms; P < .001; acceleration: mean difference, -2.25 × 10-2 [95% CI, -3.20 × 10-2 to -1.31 × 10-2] mm per 20 ms2; P < .001) and a significant reduction in the rate of tumor removal (mean difference, -4.85 × 10-5 [95% CI, -7.22 × 10-5 to -2.48 × 10-5] mm3 per 20 ms; P < .001) compared with control. These unintended outcomes diverged students' movement and efficiency performance metrics away from the expertise benchmarks.Conclusions and relevanceIn this cohort study of medical students, an AI-enhanced curriculum for bimanual surgical skills resulted in unintended changes that improved performance in safety but negatively affected some efficiency metrics. Incorporating AI in course design requires ongoing assessment to maintain transparency and foster evidence-based learning objectives.

Dataset Information

Identifying and prioritising technical procedures for simulation-based curriculum in paediatrics: a Delphi-based general needs assessment.

Publications

Identifying and prioritising technical procedures for simulation-based curriculum in paediatrics: a Delphi-based general needs assessment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets