医疗保健中的人工智能：节省成本的关键

A path to cost reduction inhealthcare Featuring insights from a 2024 commissioned global studyconducted by Forrester Consulting on behalf of SoftServe By:Peter M. Burns EXECUTIVE SUMMARY Is Generative AI (Gen AI) the answer to saving $360 billion a year in healthcare costs? The potentialfor AI to streamline existing processes and develop new, more efficient solutions is a hot topic.Many believe it will significantly reduce costs and help with workforce shortages. It offers benefitslike improved clinical decision-making, enhanced operational efficiency, and reduced administrativeburdens. Yet, Gen AI’s adoption in healthcare is slower than in other fields. The reasons include stringentregulatory requirements, concerns over data privacy and security, and the need for exceptionalreliability to ensure patient safety, among others. Despite these challenges, healthcare companiesfind innovative applications for AI technology. A 2024 commissioned global study conducted by Forrester Consulting on behalf of SoftServe showswhere healthcare companies are looking for value, how they define success, and their strategiesfor accelerating adoption. Notably, improving operational efficiency ranks among the top threegoals for Gen AI, both now and in the future. However, a major concern is the security and privacyrisks tied to Gen AI, with nearly half of respondents worried about data breaches and regulatoryfines. Surprisingly, even though workforce retention and burnout are significant challenges, manyrespondents do not seem to consider employee experience to be a key factor in the success of theirAI transformation efforts. Highlights from the 2024 study: Improving operational efficiency ranks among the top three goals for Gen AI, with 60% ofrespondents ranking it as their top priority. Enhancing research and development (R&D) is another primary goal for 62% of respondents,with a focus on testing new treatments and technologies. Software development followsclosely at 60%. 53% see great value in using Gen AI for operations, while 52% recognize similar benefits insupply chain management. While addressing workforce challenges is a key industry challenge, concerns about improvingemployee experience and managing risk are lower, with just over a third very concerned. When asked about the biggest risk of ignoring Gen AI issues, nearly 47% cited privacy anddata fines as their top concern. We’ll start by answering a few questions:Can AI reduce healthcare costs? How much could itsave? If AI has so much potential, why isn’t it more widely used? CAN AI REDUCE HEALTHCARE COSTS? Healthcare leaders are curious about how AI will simplify and improve processes. However, AIadoption in healthcare is slower than in other industries, despite the potential to save more on U.S.healthcare costs. Arecent studyfrom the National Bureau of Economic Research (NBER) showsthat healthcare may be more efficient, costing less and delivering better care. AI is key to thisimprovement. Healthcare productivity in the U.S. may be improved in two ways. First, administrative costs, whichaccount for about 25% of total healthcare spending, need to be addressed. AI automation will helplessen this burden. Second, medical knowledge advances so fast that only 6% of what new doctorslearn in medical school will still be relevant in a decade. AI will offer important clinical data whenclinicians need it during diagnosis and other important stages of care. How much could it save if healthcare widely adopted AI? TheNBER reportfound that using AI in U.S. healthcare may save between $200 billion to $360billion each year over the next five years (2023-2028). These estimates are based on practical AIuse cases achievable with current technology, ensuring quality and access are not compromised. Hospitals maysave $60 billion to $120 billion annually within five years using today’stechnologies without sacrificing quality. Private payersmay see annual savings of $80 billion to $110 billion over the next five years. Physician groups mayreduce costs by 3% to 8%, translating to $20 billion to $60 billion in savings. Administrative processes:It‘s estimated that AI and cognitive computing will generate$150billion in savingsfor the healthcare industryby 2025, mostly from helping manage the complexityand growth of medical data. But saving money is just part of the story; it signifies a shift towardmore efficient and effective healthcare. At the heart of this value-based approach is the healthcareworkforce. And that brings us to the third question: If AI has so much potential, why isn‘t it morewidely used? IF AI HAS SO MUCH POTENTIAL IN HEALTHCARE,WHY ISN’T IT MORE WIDELY USED? While financial savings are important, the human element in AI transformation matters equally. Youneed to consider how employees integrate new technologies, adapt to new processes, and interactwith AI systems. All of these considerations factor into the adoption of AI in healthcare. The AMA conduc