Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry that limit adoption.
Healthcare organizations are increasingly relying on analytics to drive decisions, but if the underlying information is flawed or premises are biased, it can lead to dangerous conclusions.
Even the best predictive analytics platforms will still need a human mind to tackle high-level analysis, and that will mean major changes in almost all human roles.
