The INFORMS Analytics+ Conference showcased how companies are turning advanced analytics and AI into measurable operational results
In most emergency departments, beds are a hot commodity. But some patients don’t actually need a bed for their treatment – and accurately identifying those people is a low-lift but effective way to increase efficiency without sacrificing care quality, finds a study recently published in the journal Management Science.
The researchers developed a simple decision tree, informed by mathematical and machine learning models, to help staff decide whether a patient truly needs a bed or can be routed to a “vertical processing pathway” – that is, an area where they can be treated sitting up. Many hospitals already have such an area but don’t necessarily have a systematic way to decide which patients are treated there.
Diversity alone won’t get the votes for funding public education. It takes communities that are more integrated and connected, where residents have a sense of shared stake.
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Testing and vaccination for monkeypox became available in all Georgia health districts last week, according to the state health department.
Over the past two-plus years, global supply chains have been stretched beyond recognition. Yet stretched is not broken, and covid-19 may serve as the launch pad to create a new and improved global supply chain model.
The Biden administration’s response has made key mistakes in handling the emerging threat. We hope this situation serves as a wake-up call to rethink and re-tool emergency response policies and practices.
In the middle of the ongoing coronavirus pandemic, we're facing a second global, viral crisis: monkeypox.
If “the forecast is always wrong,” is improving forecast accuracy even the solution to our demand planning woes? In times that continue to defy our ability to predict them, the words of famous statistician George Box have never been more right: “All models are wrong, but some are useful.” So what can we do to make models more useful? Artificial intelligence and machine learning (AI/ML) can improve forecast accuracy, but a bigger problem is the failure to set accurate expectations around forecasting models, not the accuracy of the models themselves. For supply chains to get more use from their models, we need to “trust the box;” recognize that models are not the holy grail; and remember that a forecast is an input into making better decisions, not an end in and of itself.
OR/MS Today is the INFORMS member magazine that shares the latest research and best practices in operations research, analytics and the management sciences.
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Analytics magazine showcases articles and research reports based on big data, AI, machine learning, data analytics and other new-age technologies.
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