Lean thinking integrated with an app-based e-training platform could optimize the process of resident assessment, finds a study published in BMCMedEduc. This could reduce waste and promote teaching and learning in medical education.
Optimizing the process of resident assessment to provide continuous improvements in quality
COVID-19 has greatly influenced the field of education and has highlighted a profound need for advanced technology. In teaching hospitals, educators are also clinical doctors. In medical education, face-to-face assessment is still the dominant way for clinical educators to evaluate whether residents are competent.
Using the waste framework, we were able to save time through multiple activities supported by the app. For instance, the function of sending notifications to everyone involved in the examination saved time spent on phone calls or text messages. The function providing grade statistics and reports saved doctors from calculating or preparing those manually, avoiding potential errors. The function of text conversion from voice input could save time and enable more detailed feedback.
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BMC Global and Public Health.BMC_GPH welcomes SannaJay1to its Editorial Board. With a background in community medicine and public health, Jayasinghe is a medical epidemiologist at Australia’s NCIRS.
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Ring are making major update to app - and fans are fumingRING is overhauling its app – and fans are vowing to boycott the brand in favour of Google. The Amazon-owned app announced it will be locking a number of features behind a paywall, much to it…
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This is what happens when you ask an AI app to paint 'Shropshire'We used an AI art app to see what artificial intelligence has to offer when it comes to painting the beautiful county of Shropshire.
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Influence of poor sleep on cardiovascular disease-free life expectancy: a multi-resource-based population cohort study - BMC MedicineBackground The complexity of sleep hinders the formulation of sleep guidelines. Recent studies suggest that different unhealthy sleep characteristics jointly increase the risks for cardiovascular disease (CVD). This study aimed to estimate the differences in CVD-free life expectancy between people with different sleep profiles. Methods We included 308,683 middle-aged adults from the UK Biobank among whom 140,181 had primary care data linkage. We used an established composite sleep score comprising self-reported chronotype, duration, insomnia complaints, snoring, and daytime sleepiness to derive three sleep categories: poor, intermediate, and healthy. We also identified three clinical sleep disorders captured by primary care and inpatient records within 2 years before enrollment in the cohort: insomnia, sleep-related breathing disorders, and other sleep disorders. We estimated sex-specific CVD-free life expectancy with three-state Markov models conditioning on survival at age 40 across different sleep profiles and clinical disorders. Results We observed a gradual loss in CVD-free life expectancy toward poor sleep such as, compared with healthy sleepers, poor sleepers lost 1.80 [95% CI 0.96–2.75] and 2.31 [1.46–3.29] CVD-free years in females and males, respectively, while intermediate sleepers lost 0.48 [0.41–0.55] and 0.55 [0.49–0.61] years. Among men, those with clinical insomnia or sleep-related breathing disorders lost CVD-free life by 3.84 [0.61–8.59] or 6.73 [5.31–8.48] years, respectively. Among women, sleep-related breathing disorders or other sleep disorders were associated with 7.32 [5.33–10.34] or 1.43 [0.20–3.29] years lost, respectively. Conclusions Both self-reported and doctor-diagnosed poor sleep are negatively associated with CVD-free life, especially pronounced in participants with sleep-related breathing disorders.
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Ethnic disparities in COVID-19 outcomes: a multinational cohort study of 20 million individuals from England and Canada - BMC Public HealthBackground Heterogeneous studies have demonstrated ethnic inequalities in the risk of SARS-CoV-2 infection and adverse COVID-19 outcomes. This study evaluates the association between ethnicity and COVID-19 outcomes in two large population-based cohorts from England and Canada and investigates potential explanatory factors for ethnic patterning of severe outcomes. Methods We identified adults aged 18 to 99 years in the QResearch primary care (England) and Ontario (Canada) healthcare administrative population-based datasets (start of follow-up: 24th and 25th Jan 2020 in England and Canada, respectively; end of follow-up: 31st Oct and 30th Sept 2020, respectively). We harmonised the definitions and the design of two cohorts to investigate associations between ethnicity and COVID-19-related death, hospitalisation, and intensive care (ICU) admission, adjusted for confounders, and combined the estimates obtained from survival analyses. We calculated the ‘percentage of excess risk mediated’ by these risk factors in the QResearch cohort. Results There were 9.83 million adults in the QResearch cohort (11,597 deaths; 21,917 hospitalisations; 2932 ICU admissions) and 10.27 million adults in the Ontario cohort (951 deaths; 5132 hospitalisations; 1191 ICU admissions). Compared to the general population, pooled random-effects estimates showed that South Asian ethnicity was associated with an increased risk of COVID-19 death (hazard ratio: 1.63, 95% CI: 1.09-2.44), hospitalisation (1.53; 1.32-1.76), and ICU admission (1.67; 1.23-2.28). Associations with ethnic groups were consistent across levels of deprivation. In QResearch, sociodemographic, lifestyle, and clinical factors accounted for 42.9% (South Asian) and 39.4% (Black) of the excess risk of COVID-19 death. Conclusion International population-level analyses demonstrate clear ethnic inequalities in COVID-19 risks. Policymakers should be cognisant of the increased risks in some ethnic populations and design equitable health po
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