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Predictive Analytics in Clinical Practice: Advantages and Disadvantages
Hendrik-Jan Mijderwijk1, Hans-Jakob Steiger2
1Department of Neurosurgery, Heinrich Heine University, Medical Faculty, Düsseldorf, Germany. Hendrik-Jan.Mijderwijk@med.uni-duesseldorf.de.
Abstract:
Predictive analytics are increasingly reported by clinicians. These tools aim to improve patient outcomes in terms of quality, safety, and efficiency. However, deploying predictive analytics in clinical practice remains challenging today. We highlight several advantages and disadvantages of the application of predictive analytics in clinical practice. To flourish and reach its potential, predictive analytics need data that is of adequate quantity and quality, ideally tailored to clinical scenarios in equipoise regarding optimal management. Adequate reporting of predictive analytic tools is incumbent for uptake into clinical workflows. At least for now, the clinicians' knowledge, experience, and vigilance remain imperative for applying predictive analytics in clinical practice.
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