How machine learning will help to improve the patient experience

Patients interact with healthcare organizations and professionals on various levels. Right from booking appointments, undergoing tests, receiving and understanding their reports and diagnosis, and taking treatment, to post-treatment care and payments, each step of care contributes to a patient’s experience with a healthcare system.

Much like every other industry, machine learning has been applied to the healthcare field with promising outcomes, and there are more ways in which it can improve the patient experience while easing the burden on professionals. Here’s how machine learning can achieve more of it in the near future.

Diagnosis of Diseases

One of the most prominent areas in the healthcare sector that have the potential to benefit from machine learning is diagnosis. Currently, machine learning is being used primarily for X-rays with the help of algorithms. This involves training a computer on a large set of data to create labels, such as ‘disease present’ and ‘disease not present.

As the computer assesses certain parameters to classify the data on the set, its algorithms subsequently undergo changes and adjustments. This is how the computer is trained, following which the algorithms are validated on a new dataset.

Replacing healthcare professionals with machines is not the intent when using machine learning for disease diagnosis. However, machine learning can provide additional insights to these professionals by flagging certain aspects of diagnosis, which not only eases the diagnosis process for the doctor but also enhances the patient experience.

While the machine provides certain information about the diagnosis, the doctor can provide feedback when the information is incorrect, which further enriches the algorithm.

Natural Language Processing

Maintaining patient records is quite time-consuming, and doctors spend a significant amount of their time entering data, which can actually be spent on interacting with patients.

With the use of artificial intelligence and machine learning, Natural Language Processing can be applied to this task, which involves estimating the meaning of spoken and written language to provide useful information to the computer.

While implementing machine learning in this area has to be a step-by-step process, technologies driven to improve the efficacy of the healthcare industries are working towards this.

When fully implemented, Natural Language Processing can reduce the friction of data entry while making the medical records complete.

Sentiment Analysis Patient Surveys

An application of machine learning that can positively impact patient experience is sentiment analysis based on patient surveys. Conventional means of measuring patient satisfaction is using numerical scores to interpret satisfaction levels.

Sentiment analysis can add more to the accuracy of these numerical scores and provide an in-depth insight into patients’ experience with the healthcare organization. Sentiment analysis also uses Natural Language

Processing to assess unstructured text and assign emotions to it. It goes through comments in the survey and uses its algorithms to analyze the patient’s sentiments. This helps address the exact issues of the patient and work on them, while also tracking changes and improvements over time, which can enhance the overall patient experience.

Robotic Nurse Assistant

Nurses are required to carry out certain repetitive tasks, which, when taken over by robotic nurse assistants, can free up their time that can be spent on interacting more with their patients.

Some of these tasks could be measuring the vital signs of the patient based on a predetermined schedule, delivering medication to the patient, and providing essentials such as blankets, food, and much more. This is achievable by feeding patient data into the machine pertaining to their schedules.

Based on the data available, the robotic nurse assistant carries out various tasks that improve patient experience and reduce the burden on nurses.

Federated machine learning is more about helping healthcare organizations improve their services and enhance patient satisfaction and experience rather than replacing human beings.

Machine learning and artificial intelligence have the capability to help healthcare professionals make well-informed decisions based on the insights they provide. It goes beyond modernizing healthcare practices and is more about reducing the care burden on professionals, leaving them with more time to interact with patients and minimize the chances of errors. And so, machine learning in the area of healthcare can directly enhance patient experience and improve the quality of life for people.

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