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New applications of artificial intelligence (AI) repeatedly challenge what was once thought possible. This technology is having a profound impact on nearly every industry worldwide, wielding greater efficiency and transforming whole operational processes. Healthcare is no exception \u2013 AI is reshaping the way we approach patient care and treatment decisions. <\/p>\n
AI offers practical solutions that can help organizations across the globe to overcome these challenges and improve outcomes, enhance care and advance health equity. <\/p>\n
By integrating AI as part of diagnostic services, healthcare organizations are facilitating faster diagnoses and treatment decisions that improve patient outcomes.<\/p>\n
AI\u2019s complex algorithms provide support to radiologists, who read hundreds of medical images a day, helping them analyse images such as X-rays and MRIs quicker and more accurately. This allows care teams to prioritize complex and urgent cases, and potentially detect modalities that may require further inspection.<\/p>\n
Necessary but time-consuming administrative tasks contribute to employee burnout and take clinicians away from the bedside. New AI tools can help alleviate burnout and allow staff to focus on patients by automating manual and repetitive tasks such as entering data for electronic health records and submitting prior authorization requests to insurance companies.<\/p>\n In addition to supporting employees in their day-to-day work, AI is helping to address staffing needs. Historically, nurse staffing has been a highly manual process relying on phone calls, text messages and spreadsheets. Today, we are increasingly using AI analytics to streamline this process, including seeking to pair team members who have previously collaborated because research demonstrates that it positively impacts productivity<\/a>. <\/p>\n AI technology can add to the exceptional care delivered by primary care providers. New tools can help support the earlier identification of disease which can impact disease progression, potentially slowing, preventing or completely stopping it.<\/p>\n At Hackensack Meridian Health, we have built a predictive health team that is working with stakeholders across the network to take advantage of AI technology to predict and detect disease and embed such intelligence into clinical workflows. For instance, AI has been integrated into the workflow for our primary care providers to help identify stage 3 chronic kidney disease earlier, which can help slow disease progression.<\/p>\n Once treatments become available, we need the right intelligence to optimize effectiveness and reduce the risk of adverse effects. AI algorithms can help us get there sooner by analysing large datasets, including genetic information and medical histories, to inform treatment plans that factor in predicted outcomes and potential treatment responses.<\/p>\n While AI presents a monumental opportunity for change, it requires an ongoing commitment to identifying and addressing the potential concerns that emerge with any new technology.<\/p>\n For the benefits of AI to be realized on a global scale, we must be mindful of potential pitfalls and establish safeguards related to data privacy, ethical considerations, cultural sensitivity and its accessibility to diverse populations. The World Health Organization (WHO) published ethical AI guidance<\/a> in 2021, cautioning that while AI holds great promise for improving the delivery of healthcare worldwide, this can happen \u201conly if ethics and human rights are put at the heart of its design, deployment, and use.\u201d <\/p>\n Potential for bias is of particular concern: if an AI algorithm is trained with data that doesn\u2019t represent the whole population, it can exacerbate health disparities. For instance, skin cancer algorithms<\/a> that were primarily trained on lighter-skinned individuals are not as effective in detecting skin cancer among darker-skinned individuals. Under-representation is a longstanding challenge in clinical research and we need more diverse data to mitigate the risk of bias.<\/p>\n Discover<\/p>\n How is the World Economic Forum creating guardrails for Artificial Intelligence? <\/p>\n<\/a>Healthcare organizations are beginning to recognize more opportunities to use AI Image: Deloitte Insights<\/p>\nAlleviating employee burnout and supporting staffing needs<\/h2>\n<\/p>\n
Early disease detection and improved patient outcomes<\/h2>\n<\/p>\n
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<\/a>In the US, there are an estimated 100 million people with an undiagnosed chronic disease Image: Centers for Disease Control and Prevention<\/p>\nImproving and expediting treatment options<\/h2>\n<\/p>\n
Mindful of potential pitfalls<\/h2>\n<\/p>\n