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- Artificial intelligence enables machines to carry out tasks that we would consider smart
- Machine learning is a subset of AI where we feed the machine lots of data and the machine learns for itself
- Pattern recognition is a subset of machine learning where the machine uses all that data to identify patterns and apply them in various ways
The robots aren’t taking over just yet, but these futuristic-sounding technologies are already in use today in all kinds of life-saving ways.
Machine learning is being used in some hospitals via wearables that can monitor patients’ vitals and predict medical issues so they can be treated in advance. And law enforcement in many cities uses ShotSpotter’s pattern recognition to pinpoint gunfire and respond within seconds to keep communities even safer.
So it makes perfect sense to leverage these technologies to combat drug diversion in hospitals.
When it comes to looking out for controlled substance diversion, half the battle is knowing what to look for, and how to look for it. And since diverters are getting more and more savvy about getting around physical controls and protocols, you need intelligent tools to help you stay ahead of potential issues.
The Bluesight for Controlled Substances platform brings the power of machine learning to bear on the massive amount of data being generated daily from EMRs and ADCs, and learns to recognize your hospital’s patterns and apply them to data on medication usage, distribution, and other behaviors. Instead of being inundated by tons of details, you can clearly see patterns that were not visible before.
And the beauty of machine learning means that the more data Bluesight processes, the smarter it gets.
You can then use what shakes out to put specific, actionable recommendations into place to minimize the very real risk of controlled substance diversion.
So even though we’re not quite ready to welcome our robot overlords, we can take advantage of the latest technologies to make the world safer for both hospitals and patients.