How machine learning, AI and deep learning will impact care management
Care managers are overwhelmed every day with too much data and too many patients. But in the future, machine learning tools will help care managers by suggesting (not deciding) which patient should be next in line and which interventions can help patients the most.
With the introduction of innovative technology, healthcare systems will be able to learn from their successes and mistakes, leading to built-in continuous improvement.
Ed Daniels, managing member at First Response Management, looks into the future and predicts what care managers can expect to see.
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All the data that pours in about patients is overwhelming. Machine learning can be helpful because it allows care management systems to sort through huge volumes of patient data to identify that small slice of information about a patient that is most important to the care manager.
“Machine learning can narrow down the data and boil it down to specific suggestions that care managers can use for specific patients,” Daniels says. “It might be able to help a care manager decide which patient should be called next. It could also suggest which of all the possible intervention will be most likely to have a positive impact for a specific patient. But the care manager will always have to review these suggestions and make the final decision.”
AI: Beyond voice recognition
When we think about how consumers view AI (Artificial Intelligence) today, we think about Apple’s Siri, Google’s Assistant, Microsoft’s Cortana and Amazon’s Alexa. These devices are migrating from our pockets into our living rooms. Care managers can expect that over the next few years, these easy-to-use AI tools will migrate into their workplace.
When a care manager is managing hundreds of patients, the care management system of the future will be able to:
- Suggest which patient should be the next one to call
- Suggest which intervention will have the biggest impact on outcome and cost
- Learn from what care managers do so that it can do an even better job next time
“AI will help with pre-populating fields to ease the data entry workload,” Daniels says. “In addition, AI will help care managers be more effective by suggesting the best way to communicate with patients.”
Deep Learning: Computer-powered intuition
A care manager can look at a patient’s profile and get a “feeling” about the best way to help that patient. That’s because humans get their intuition from the brain’s massively parallel neural network. Technology is helpful because it can turn new care managers into experienced care managers, without years and years of training.
Now, machine learning experts are applying this “Deep Learning” neural network technology to computer-power our intuition about patient care and care management interventions.
“This is still a budding area of data science, but care management system developers are looking in this direction for the next step in making these systems even more valuable for care managers and the organizations that employ them,” Daniels says.
Disconnected and disjointed data: A care management survival guide
As a care manager, you know how dangerous it can be when you see conflicting data about the same patient, from various systems. But you’ve got to figure out how to let data empower your workflow, not prevent you from doing the best possible job for your patients. Read a few tips on how to do just that.
Interoperability is one of the greatest challenges the healthcare industry faces. Patient information lives across various systems that are used to manage a patient’s health. That’s why it’s important for care managers to act like detectives, searching various sources for the right information to serve the patient.