A new study conducted at the Sheba Medical Center showed for the first time that Artificial Intelligence (AI) not only improves work processes but also saves lives and reduces disability among patients. The results of the study, published in Bio Med Central (The impact on clinical outcomes after 1 year of implementation of an artificial intelligence solution for the detection of intracranial hemorrhage) showed that incorporating AI that decoded head CT scans in the emergency room contributed to a 30% decrease in mortality.
The researchers examined 587 male patients diagnosed with cerebral hemorrhage in 2017, without AI-assisted decoding, and in 2019, after the implementation of an AI system that was developed by AIDOC, an Israeli startup, in the hospital. The AI decodes each new photograph and sorts the photographs in which it detects urgent abnormalities such as bleeding, stroke, or cerebral aneurysm. It was found that patients whose scans were deciphered by AI were released an average of a day and a half earlier than those who were not.
According to the study authors, Dmitry Kotovich, Gilad Twig, Zeev Itsekson-Hayosh, Maximiliano Klug, Asaf Ben Simon, Gal Yaniv, Eli Konen, Noam Tau, Daniel Raskin, Paul J. Chang, and David Orion, AI in healthcare is growing rapidly, and in radiology, AI has the potential to transform the healthcare field by integrating into the radiology workflow and improving the efficiency and efficacy of medical imaging.
“Many studies have been published on the potential of AI to improve the triage, prioritization, and detection of critical conditions and pathologies,” they write. “Intracranial hemorrhage is one condition that is highly impacted by AI’s ability to prioritize and triage suspected findings, thus leading to earlier therapeutic interventions. Literature has shown that earlier detection and initiation of interventions can reduce the risk of complications and overall mortality and morbidity for ICH patients. As to the potential of AI, a few recent studies have shown a significant impact of AI on clinical outcomes for ICH patients. One most recent study showed a significant reduction in hospital length of stay after the implementation of AI software into the radiological workflow at a large academic center. To date, there have been no studies looking at AI’s impact on all-cause mortality rates for ICH patients in the emergent care setting.”
A background literature search was conducted using PubMed and Open Access journal sources, and observational studies as well as systematic reviews and metanalysis were reviewed. The added value of the study emphasizes the introduction of AI computer-aided triage and prioritization software in an emergent care setting that demonstrated a significant reduction in 30- and 120-day all-cause mortality and morbidity for patients diagnosed with intracranial hemorrhage (ICH).
Along with mortality rates, the AI software was associated with a significant reduction in the Modified Rankin Scale (mRs), measuring the degree of disability or dependence in the daily activities of people who have suffered a stroke or other causes of neurological disability.
The study highlights the potential of AI-triage software to offer a new path toward impacting mRs score and mortality rates in this critical population.
