Intermountain Healthcare Studies AI Use in Pneumonia Diagnosis

Intermountain Healthcare Studies AI Use in Pneumonia Diagnosis Technology has improved the way care is provided to patients. It has also enhanced the way medical transcription service is provided to physicians.

Today, technology plays an important role in every industry. Advancements in medical technology have allowed physicians to diagnose and treat patients efficiently and save countless lives. The developments of technology range from diverse methods of treatment offered to the patients to various types of software and techniques used in medical transcription service and other such business solutions.

AI in Healthcare To make the healthcare industry more advanced and efficient, AI and robotics are being increasingly incorporated. AI increases healthcare professionals’ ability to better understand the day-to-day patterns and needs of the people they care for, and with that understanding they are able to provide better feedback, guidance and support for staying healthy.

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According to Frost & Sullivan, AI systems are projected to be a $6 billion-dollar industry by 2021. McKinsey’s review predicted healthcare as one of the top 5 industries with more than 50 use cases that would involve AI, and over $1bn USD already raised in start-up equity. In simple terms, Artificial Intelligence refers to the use of machines or computers to think like humans.

Use of AI in healthcare 

Radiology: AI is used to automate image analysis and diagnosis as it can highlight areas of interest on a scan. This improves efficiency and minimizes human errors. It can also automatically read and interpret a scan without human oversight and this enables instant interpretation in under-served geographies or after hours.

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Discovering drugs: AI solutions can identify new potential therapies from vast databases of information on existing medicines, which could be redesigned to target critical threats such as the Ebola virus.This improves the success rate of developing new drugs.

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Risk identification of patients: AI solutions can provide real-time support to clinicians in identifying patients who are at risk. Re-admission risks, patients who have an increased chance of returning to the hospital within 30 days of discharge, can be identified. Many health systems and healthcare companies are developing solutions on data in the patient’s electronic health record, by increasing push back from payers on covering hospitalisation costs associated with re-admission.

Researchers at Intermountain Healthcare and Stanford University found that the use of artificial intelligence could help radiologists to identify key findings in chest X-Rays of suspected pneumonia patients in the ER within just 10 seconds. This, according to the researchers, is a tremendous improvement from earlier averages of 20 minutes or more. The use of AI can therefore enable treatment to start sooner.

The researchers studied the CheXpert system which is an automated chest X-ray interpretation model built at Stanford that helps to review images at several emergency departments at Intermountain hospital in Utah, and reached the consensus that key findings were identified very accurately and the 10-second response rate significantly outperforms current clinical practice.

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Nathan Dean, MD, principal investigator of the study, said that CheXpert is going to be faster and accurate as radiologists viewing the studies. CheXpert was developed by the Stanford Machine Learning Group that used 188,000 chest imaging studies to create a model that can identify what is and what is not pneumonia. They are also developing a deep learning algorithm that can automatically detect pneumonia and related findings in chest X-rays. They hope that the algorithm can improve the quality of pneumonia care at Intermountain, from improving diagnostic accuracy to reducing time to diagnosis.

In the study, radiologists categorized 461 patients and assessed them through four metrics on how likely they were to have pneumonia. Later, they assessed images that showed the disease in multiple parts of the lungs and whether the patients had fluid build-up between the lungs and chest cavity. The researchers found that the CheXpert model outperformed the current system of using a radiologist to create radiology reports for all important pneumonia findings, plus NLP (natural language processing).

There has been a huge improvement in medical treatment made possible by advanced technology. Technology has also considerably improved the way medical transcription service is provided to physicians. Today, with the EHR system, physicians and other healthcare professionals use the HL7 interface which provides the framework for integrating, sharing and retrieval of EHR. It provides an encrypted and secure means of transferring files.

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