Innovative Interdisciplinary Strategies to Address the Intensivist Shortage

Buchman, Timothy G.; Coopersmith, Craig M.; Meissen, Heather; Grabenkort, W. Robert; Bakshi, Vishal; Hiddleson, Cheryl; Gregg, Sara

doi:10.1097/ccm.0000000000002209

Cited by 35 publications

(13 citation statements)

References 19 publications

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“…A concern about the future of the medical work force in the US is a projected dearth of medical graduates in different specialties [40], creating a potential crisis [41]. However, this is controversial, as some researchers do not see a shortfall [24] and suggest alternatives to increasing the supply of medical graduates in the US [42].…”

Section: Discussionmentioning

confidence: 99%

Exploring relationships between medical college rankings and performance with big data

Rao

Clarke

2019

Big Data Anal

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Background: It is important to examine the cost-effectiveness of medical education. The public wants to know how government spending is being utilized to train doctors. There are very few studies that examine national data to understand the relationships between medical education and outcomes. We used Big Data analytics with open health data to explore answers. We joined physician data and hospital total performance score data reported by Center for Medicare and Medicaid Services (CMS), containing information for nearly 600,000 practitioners and performance scores from three thousand hospitals in the United States. We combined this data medical college costs from the American Association of Medical Colleges and medical school rankings. We used Mullan's social mission to compare medical schools. We also computed the correlation between the rankings of 4-year baccalaureate colleges in the US published by the Wall Street Journal, and the in-state tuition at these colleges in the Integrated Post-secondary Education System database. Results: We found a statistically significant but negligible correlation (Spearman rank correlation − 0.04, p-value < 0.0001) between the rank of a medical school and the total performance score of the hospitals that their graduates practiced in. We found a statistically significant and high correlation (Spearman rank correlation of − 0.903, p-value = 0.003) between the averaged rank of medical schools and average number of graduates produced by these schools associated with CMS hospitals. Similar results were obtained for the social mission score. In contrast, the correlation between the ranking of 4-year colleges and (a) their tuition was − 0.34 and (b) their outcomes was − 0.86 (p-value < 10 − 5). Conclusions: Our results suggest that US medical education is robust and produces satisfactory performance outcomes. Higher tuition is not correlated with higher ranks or better outcomes. Hence, the public needs to question what they are getting in return for higher tuition. We also suggest that it may be better to produce more graduates from existing medical schools than opening new schools.

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Section: Discussionmentioning

confidence: 99%

Exploring relationships between medical college rankings and performance with big data

Rao

Clarke

2019

Big Data Anal

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“…For at least the last 15 years, the number of intensivists has been decreasing worldwide, leaving most ICUs incapable of providing optimal levels of care. 18 Moreover, in the United States, roughly a quarter of critical care physicians and pulmonologists are aged 60 and older, putting them at a higher risk of COVID-related complications. And while sufficient PPE is mandatory, healthcare workers worldwide argue that they are not adequately protected due to its shortage.…”

Section: The Most Critical Vulnerability In Icu Is Not Infrastructurementioning

confidence: 99%

Does "Flattening the Curve" Affect Critical Care Services Delivery for COVID-19? A Global Health Perspective

Gilardino

2020

Int J Health Policy Manag

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During this coronavirus disease 2019 (COVID-19) global pandemic, nations are taking bold measures to mitigate the spread of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in order to avoid the overwhelming its critical care facilities. While these "flattening the curve" initiatives are showing signs of impeding the potential surge in COVID-19 cases, it is not known whether these measures alleviate the burden placed on intensive care units. Much has been made of the desperate need for critical care beds and medical supplies, especially personal protective equipment (PPE). But while these initiatives may provide health systems time to bolster their critical care infrastructure, they do little to protect the most essential element – the critical care providers. This article examines bolder initiatives that may be needed to both protect crucial health systems and the essential yet vulnerable providers during this global pandemic.

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“…We categorized ICUs by their primary mission whereby a: (a) cardiothoracic surgical ICU (CTICU) treats patients after major heart, lung, and vascular surgery; (b) neuroscience ICU (NSICU) treats patients following cerebrovascular insults and intracranial procedures; (c) surgical ICU (SICU) treats postoperative patients not in one of the two prior categories, (d) medical ICU (MICU) treats critically ill adults not having recently undergone surgery, and (e) medical-surgical ICU (MSICU) treats a mixture of critically ill adults. The studied ICUs vary in their format and staffing (see Additional file 1 : Table S1 for further details) [ 31 , 32 ]. Ventilator management is the responsibility of the critical care physician, or the admitting physician in ICUs without critical care staffing.…”

Section: Main Textmentioning

confidence: 99%

Modes of mechanical ventilation vary between hospitals and intensive care units within a university healthcare system: a retrospective observational study

et al. 2018

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ObjectiveAs evidence-based guidance to aid clinicians with mechanical ventilation mode selection is scant, we sought to characterize the epidemiology thereof within a university healthcare system and hypothesized that nonconforming approaches could be readily identified. We conducted an exploratory retrospective observational database study of routinely recorded mechanical ventilation parameters between January 1, 2010 and December 31, 2016 from 12 intensive care units. Mode epoch count proportions were examined using Chi squared and Fisher exact tests as appropriate on an inter-unit basis with outlier detection for two test cases via post hoc pairwise analyses of a binomial regression model.ResultsFinal analysis included 559,734 mode epoch values. Significant heterogeneity was demonstrated between individual units (P < 0.05 for all comparisons). One unit demonstrated heightened utilization of high-frequency oscillatory ventilation, and three units demonstrated frequent synchronized intermittent mandatory ventilation utilization. Assist control ventilation was the most commonly recorded mode (51%), followed by adaptive support ventilation (23.1%). Volume-controlled modes were about twice as common as pressure-controlled modes (64.4% versus 35.6%). Our methodology provides a means by which to characterize the epidemiology of mechanical ventilation approaches and identify nonconforming practices. The observed variability warrants further clinical study about contributors and the impact on relevant outcomes.Electronic supplementary materialThe online version of this article (10.1186/s13104-018-3534-z) contains supplementary material, which is available to authorized users.

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Innovative Interdisciplinary Strategies to Address the Intensivist Shortage

Cited by 35 publications

References 19 publications

Exploring relationships between medical college rankings and performance with big data

Exploring relationships between medical college rankings and performance with big data

Does "Flattening the Curve" Affect Critical Care Services Delivery for COVID-19? A Global Health Perspective

Modes of mechanical ventilation vary between hospitals and intensive care units within a university healthcare system: a retrospective observational study

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