New research published in the INFORMS journal Operations Research shows that healthcare systems can substantially reduce overtime, idle time and overall staffing costs by adopting a multilocation, dynamic staff-planning model for anesthesiologists. The study is based on the University of Pittsburgh Medical Center (UPMC), which cut daily overtime and idle time across 11 hospitals, generating over $800,000 in annual cost savings.

Cardiovascular diseases account for approximately 80% of all deaths caused by known medical conditions, making them the leading cause of mortality worldwide. The present study investigates the use of electrocardiogram (ECG) non-linear features and different topological medical features (heart rate, anthropometry, blood, glucose, and lipid profile, and heart rate variability) to discriminate between different Framingham Cardiovascular Risk Scale status groups in adult obesity using machine learning.

Reporting quality in clinical research is critical for evidence-based medicine and reproducibility of clinical studies. Previous work has mostly focused on the reporting quality of clinical trials and observational longitudinal studies. However, few studies have examined the reporting quality of trend analyses. Moreover, the reporting of recommended statistical metrics in trend analyses remains largely unclear. Therefore, we assessed the reporting quality of trend analyses based on reporting of recommended statistical metrics. We systematically searched the PubMed for the trend-analysis articles published in 10 leading medicine and oncology journals over an 11-year period (2008–2018). Studies published after 2019 were excluded due to a sudden, significant increase in publication numbers during and immediately after the COVID-19 pandemic. Only original articles, research letters, and meta-analyses/systematic reviews were included. We scored the reporting quality of these articles based on whether they reported p-values, effect sizes, beta/coefficient/slope/annual-percentage-change (APC). 297 articles met the inclusion criteria. Among these, 193 (66.0%) reported p-values and 216 (72.7%) reported effect sizes. Only 13 (5.8%) analyses reported neither p-values/effect sizes nor beta/coefficient/slope/APC. In multivariable regression models, authors affiliated with epidemiology departments were less likely to report effect sizes, whereas those from statistics departments were more likely to do so. Interestingly, U.S.-based senior authors (versus non-U.S.) more likely reported p-values. No factors were independently associated with reporting APC. Overall, the reporting quality of trend analyses in leading medicine and oncology journals appears moderate and warrants improvement. We thus call for increased awareness and further research on reporting quality in trend analyses in oncology research and beyond.