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Transforming Healthcare Systems with Machine Learning

The healthcare field is leveraging the advances of consumer technology to transform patient care. By applying consumer technologies in healthcare, some of the toughest industry milestones can be tackled to provide high-quality patient care.

Machine learning is one of the technologies that can evolve the healthcare industry due to its ability to absorb data and improve itself with more experiences. Healthcare companies are utilizing machine learning to detect breast cancer, prevent blindness in patients with diabetes, and identify high-risk of cardiac arrest. The healthcare industry needs to continue evolving these upheavals.

Hospitals can be the perfect grounds to prove new patient care technologies. The current technology used in hospitals cannot adapt without manual program updates; it must be pre-programmed to respond to a trigger. However, machine learning system becomes smarter over time on their own. No manual program updates are required. It can identify the characteristics of patient needs and take proper actions. This system can be applied in many places in hospitals and solve a set of challenges.

Analyzing the organizational workflow and the interaction between human resources and technology is of utmost importance to capitalize on machine learning. Machine learning will continue to accumulate data and make predictions and decisions based on that information. Since some of this information will need to be transmitted to hospital workers, there needs to an ongoing discussion on the notification that is sent and received. This and many other pain points need to be addressed directly with different stakeholders.

The healthcare industry has been welcoming new technologies. But in order to fully leverage machine learning, health systems need to understand and evaluate the relationship between human resources and technology to support workflow.

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