Artificial intelligence (AI), machine learning (ML), predictive analytics, and the Internet of Things (IoT) are the buzzwords promising to change the face of healthcare. Their value and benefits are undeniable — and they are key to realizing the vision of patient-centered care. However, before realizing the true benefits of these technologies, hospitals need to be careful to not put the information analysis cart before the data-bearing horse.
To build a successful patient-centered program, hospitals must get access to the data feeding the model and visualizations. This is especially important in critical care environments, wheremore than five million people are admitted in the U.S. annually and over 500,000 die every year
often without warning. To help reduce these numbers and save more lives, critical care teams need as much data about a patient as they can get, as fast as possible, along with the relevant context to take action.
AI success in acute healthcare depends on accurate, real-time data — specifically the beat-to-beat, time series waveform data of the most critically ill patients.