通过护理团队的可操作人工智能策略增强HCA的创新

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 solution to healthcare’s labor crisis? Right now, one of the biggestchallenges in healthcare is to attract and retain staff in a tough job market. These shortages ripplethrough the system, leading to staff burnout, higher turnover rates, and ultimately compromisingthe quality of patient care. Advocates believe Gen AI could alleviate the burden of time-consumingadministrative tasks and increase regular communication with patients — two critical areas ofconcern for healthcare professionals (HCPs). 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 strategies foraccelerating adoption. 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 reason for not implementing Gen AI solutions, nearly 47%cited a risk of privacy and data fines as their top concern. We’ll start by answering a few questions:Can AI simplify healthcare administration? How muchcould it save? If AI has so much potential, why isn’t it more widely used? CAN AI SIMPLIFY HEALTHCAREADMINISTRATION? 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, and that AI is key tothis improvement. 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? 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 payers maysee 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:Back in 2018, experts estimated that AI and cognitive computingcould save the healthcare industry$150 billionby 2025, mostly used to deal with the complexityand growth of medical data. But saving money is part of the story; it signifies a shift toward moreefficient 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 technologies, adapt to new processes, and interact withAI systems. All these considerations factor into the adoption of AI in healthcare. The AMA conducteda comprehensive studyof over 1,000 physicians’ views on the use ofaugmented intelligencein healthcare. It covered current use, future motivations, concerns, andpotential for adoption. The AMA deliberately uses "augmented intelligence" to emphasize that thesetools support rather than replace human decision-making. The AMA study found that physicians arecurrently using or planning to us