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TEAM

Emergency Medical Services Predictions

Jessica Liu, Darius Alizadeh, Jonathan Miller, Karina Cho

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The goal of this project is to produce useful predictions using the database published by the National EMS Information Services organization. Given that EMS is underfunded and understaffed across the country, it may be useful to be able to predict how many calls will be in a given region at a given time. If we can produce predictions about the volume of specific types of calls, even better.

A first step would be to do time series modeling using just the data provided in the public NEMSIS database. A second step would be to apply to include data with more location identifiers (specific location identifiers don't automatically come with the default dataset from NEMSIS for medical privacy reasons). A third step could be to try to include other types of data in the model, such as weather, flu/covid rates, unemployment rates, ect.

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