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www.beckershospitalreview.com | ||
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erik.wiffin.com
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| | | | | Executive Summary A major academic medical center faced challenges with high patient no-show rates for scheduled surgical procedures, leading to suboptimal utilization of limited operating room capacity and lost revenue opportunities. To address this problem, I was contracted to develop a machine learning model to predict the likelihood of patient no-shows. By integrating this predictive capability into their scheduling workflows, the hospital was able to proactively identify high-risk no-show patients and take steps to mitigate the issue. | |
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www.healthcarefinancenews.com
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| | | | | Optum calls the study's conclusions "misleading" as health systems use many data elements other than cost to select patients for clinical engagement. | |
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omarmetwally.blog
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| | | | | The strain of the COVID-19 pandemic on society and healthcare systems turned fine fault lines into gaping canyons. Reflecting on my writings about U.S. hospitals 5 years ago, I asked myself what had changed and what still must change to rebuild a healthcare system that can deliver medical care wherever and whenever it's needed. What... | |
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www.harvardmagazine.com
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| | | This week in the battle between Harvard and the Trump administration | ||
