There has been an exponential advancement in technology in recent times with companies breaking new grounds in the area of artificial intelligence, chat bots, 3D technology and simulations and Machine learning. Machine learning for Healthcare is using this great advancement in technology to make the healthcare industry more efficient. Many industries besides the Healthcare Industry, use machine learning for more efficiency. Some of these industries are Marketing and Sales, Financial Services, Government, Transportation and Oil and Gas.
These industries work with big data just like the healthcare industry and have found ways to use the benefits of Machine learning to their advantage. The Healthcare industry is doing same. It’s very important to use Machine Learning for healthcare in order to improve the quality of life of patients and efficiency of people in the health industry.
Before listing the benefits of Machine Learning for Healthcare, we should first understand what it means. Put simply, Machine learning is a method of data analysis that automates the development and building of analytical models. With Machine learning the algorithms and programs iteratively and independently learn from data. Hence, computers can find insights and patterns that would be missed by the human eye without being programmed to do so.
Benefits of Machine Learning for Healthcare
It helps to reduce readmissions in Hospitals: Machine Learning can predict which patients are more likely to be readmitted for a similar or related illness or which patients have displayed this pattern in this past. With this information, hospitals can take measures to prevent or reduce these readmissions.
It prevents hospital-acquired infections (HAIs): Central-line associated bloodstream infections (CLABSIs) are known to be very serious issues that affect patients. When germs and/or bacteria enters the bloodstream through the central line it puts patients at great risk. Machine Learning can predict which patients are more susceptible to CLABSIs giving physicians the chance to be proactive and take extra measure to prevent it.
It reduces hospital Length-of-Stay (LOS): With the information gotten from Machine Learning, Hospitals can reduce the length of stay of patients. For example, as mentioned above, preventing hospital-acquired infections like Central-line associated bloodstream infections means a higher turnover for patient beds. This is a great benefit to both the patients and the hospital.
It predicts chronic diseases: Machine learning can predict the likelihood of a patient to develop a chronic disease. It can also help diagnose unknown or misdiagnosed chronic diseases and infections. In cases where these diseases are infectious and contagious, this information helps prevent it’s spread and gives the hospital or health facility a head start in dealing with outbreaks.
It reduces 1-year mortality: Death within one year of discharge is a problem hospital and patients have to deal with. With the predictive data gotten from machine learning, hospitals can predict which patients are more susceptible to this and thus provide the appropriate care and support system for the patients after they are discharged. With the hospitals following up on these patients it reduces or even completely prevents the likelihood of a 1-year mortality. Also, with machine learning pointing out which patients need this care, the hospital doesn’t have to spread its resources thin by providing this follow-up to those who don’t need it. This improves efficiency and patient satisfaction and most importantly, survival rate.
It predicts patients’ propensity-to-pay: Using patient information and data they provide, Machine Learning can predict which patients are more likely to have difficulty paying their health bills. That way, patients can be offered financial assistance or payment plans to help them pay their bills. This way the hospital doesn’t lose money and the patients are not in debt.
All these benefits make the practice of medicine more proactive than reactive. Hospitals and Health Organizations that use Machine learning reap these benefits and stay ahead of the game in terms of efficiency and quality of care to patients.