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Improving patient safety and quality through AI and ML

Artificial intelligence(AI) and machine learning(ML) are some of the latest technologies to hit the healthcare world in the past few years. While for the most part they are still being integrated into medical offices, both artificial intelligence and machine learning could help improve patient safety and treatment quality drastically, all while helping to reduce the current strain placed on the healthcare system as a whole.

The healthcare system suffers from overreach. That should not come as a great surprise to most people. The deficit in healthcare workers and offices around the country leads to issues in providing adequate care. Anyone who has ever tried to call for a doctor's appointment can get a sense of the overwhelming need for a more streamlined system of patient care. While many doctors and nurses do their best to try and care for all of their patients, many offices are severely underfunded. Not only this, but the frequency of medical errors in the modern-day and age is astounding. Recent studies show that medical errors are in the top ten causes of death in the United States. In many cases, these are preventable errors. But how do artificial intelligence and machine learning factor into this?

improving Patient Safety and Quality Through AI and Machine Learning whiznets

AI in healthcare

Recently, the development of new programs has led to an increase in interest in how artificial intelligence could help alleviate some of the current stress placed on the healthcare system as a whole. Focusing in on medical uses, artificial intelligence has been used to calculate a patient's symptoms and demographic information, as well as a genetic propensity for certain ailments, and has successfully diagnosed the patient's condition. By tapping into a wealth of symptom history logs and extensive medical research, learning machines could detect patterns that many humans may miss when looking at a patient's symptoms. Artificial intelligence could not only aid doctors in making their diagnosis; they could alert providers to potentially deadly illnesses or issues that may otherwise go misdiagnosed. 

Not only would this allow doctors to more effectively care for their patients, but it could also reduce the need for face-to-face doctor's visits. Picture this: "You are suffering from a headache and a runny nose. You assume it is allergies, but decide to ask your doctor just in case. Instead of calling your office and scheduling an in-person visit that could take hours out of your busy day. Instead, you open up an app on your phone or website on your computer that is securely connected to your healthcare providers. You put in your symptoms, and the program notices that you have a vulnerability to sinus infections, something your doctor may not have noticed. All this without before setting foot in your doctor's office."

While artificial intelligence is still in the starting stages, implementing these services into the world of healthcare could help improve the quality of treatment for thousands of people all without increasing the cost of medical care.

Source(s):

https://news.mit.edu/2017/using-machine-learning-improve-patient-care-0821 

https://www.slideshare.net/healthcatalyst1/improving-patient-safety-machine-learning-targets-an-urgent-concern 

https://www.cs.cmu.edu/~neill/papers/ieee-is2013.pdf 

https://hbr.org/2006/05/why-innovation-in-health-care-is-so-hard

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