NEW YORK – While hospitals and doctors' offices have mostly been using artificial intelligence-based tools for documentation and clerical tasks, experts in the space expect an incoming wave of applications for in-depth analysis of electronic health records, improved guidance on testing and treatment, and more efficient monitoring of care..

纽约——尽管医院和医生办公室主要使用基于人工智能的工具来处理文档和文书任务，但该领域的专家预计，将迎来一波新应用，这些应用将深入分析电子健康记录、改进检测和治疗指导，并更有效地监控护理过程。

In total, it could amount to a new future for the clinical use of AI.

总计下来，它可能为人工智能的临床应用开创一个崭新的未来。

At Cedars-Sinai in Los Angeles, Yaron Elad, chief medical informatics officer and cardiologist at the medical center, said that it has long used clinical decision support tools to inform decisions on patient testing. Those tools, he said, may soon be replaced with AI-based algorithms that can incorporate more parameters and provide better guidance.

洛杉矶Cedars-Sinai医学中心的首席医学信息官兼心脏病专家雅龙·伊拉德表示，该医学中心长期以来一直使用临床决策支持工具来辅助患者检测相关的决策。他说，这些工具可能很快会被基于人工智能的算法取代，这种算法能够整合更多参数并提供更优指导。

.

。

While a rules-based tool might recommend treatments with consideration for a patient's high cholesterol, family history of heart disease, and diagnosis of diabetes, for example, an AI-based model could provide deeper analysis of a patient's chart and identify a conglomeration of symptoms and risk factors, he said.

他表示，基于规则的工具可能会考虑到患者胆固醇高、心脏病家族史和糖尿病诊断而推荐治疗方案，而基于人工智能的模型则可以对患者的病历进行更深入的分析，识别出一系列症状和风险因素的综合情况。

If that analysis noted that CAT scan results years prior had identified calcified blood vessels, for instance, those findings might trigger additional testing or follow-up care that the patient should have with his or her primary care provider..

如果分析指出，几年前的CAT扫描结果发现有钙化的血管，那么这些发现可能会促使患者需要接受更多的检查或后续护理，而这应该由其初级保健医生来进行。

Clinician interest in AI-based tools is on the rise. The American Medical Association

临床医生对基于人工智能的工具的兴趣正在上升。美国医学协会

said earlier this year

今年早些时候说的

that 66 percent of physicians surveyed in 2024 reported using at least one AI-developed tool in practice, up from 38 percent in 2023. Most often they used the tools to document tasks such as taking notes on patient visits or writing discharge summaries.

2024 年接受调查的医生中有 66% 报告称在实践中使用了至少一种人工智能开发的工具，高于 2023 年的 38%。他们最常使用这些工具来完成记录任务，例如记录患者就诊笔记或撰写出院总结。

The clinicians were optimistic, though, about the potential of the technologies for both clinical and administrative functions. In the survey of 1,183 physicians, 75 percent of respondents in 2024 said that AI-developed tools could help with efficiency, 72 percent said that the technologies could augment diagnostic abilities, and 62 percent said they could help to improve clinical outcomes..

临床医生对这些技术在临床和行政职能方面的潜力表示乐观。在对1183名医生进行的调查中，2024年有75%的受访者表示，人工智能开发的工具可以提高效率，72%的人认为这些技术可以增强诊断能力，62%的人表示它们有助于改善临床结果。

Despite the high expectations for the potential of AI tools, surveyed members also expressed worries about such technologies, with only 35 percent of physicians saying they are more excited than concerned about AI usage, whereas 40 percent said they were equally excited and concerned and 25 percent said that they were more concerned.

尽管对人工智能工具的潜力寄予厚望，但受访成员也表达了对这类技术的担忧。仅有35%的医生表示，他们对人工智能的使用感到兴奋多于担忧，而40%的医生表示既兴奋又担忧，25%的医生表示更加担忧。

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。

According to the survey, physicians said that AI technologies need to incorporate feedback loops, address data privacy concerns, integrate into workflows, and come with adequate training and education for their use. Almost half of physicians said increased regulatory oversight also would increase their trust in AI tools..

根据调查，医生表示，人工智能技术需要融入反馈机制、解决数据隐私问题、整合到工作流程中，并提供充分的培训和教育以指导其使用。近一半的医生表示，加强监管也会增加他们对人工智能工具的信任。

At electronic health record provider Epic, executives said that nearly every healthcare organization in the US is using AI in some capacity, and about two-thirds are using generative AI to create blocks of text to summarize clinical information.

在电子健康记录供应商Epic，高管们表示，几乎每个美国医疗保健机构都在某种程度上使用人工智能，其中约三分之二的机构正在使用生成式人工智能来创建文本块以总结临床信息。

Phil Lindemann, VP of data and research at Epic, said that AI-developed algorithms are used with the firm's EHR system to summarize patient clinical histories and test results, identify which patients need extra reminders for appointments, draft replies to patient messages, find diagnosis codes, and draft appeals when payors deny claims for medically necessary services.

Epic的数据与研究副总裁菲尔·林德曼表示，使用人工智能开发的算法与公司的电子健康记录系统配合，用于总结患者的临床病史和检测结果，识别哪些患者需要额外的预约提醒，起草对患者信息的回复，查找诊断代码，并在支付方拒绝必要医疗服务的索赔时起草申诉。

Among Epic's current projects is one evaluating the use of AI to help doctors review a patient's medical history ahead of a visit. By summarizing, for example, recent data from the patient's cardiologist and lab results, the tools can save physicians time and reduce their mental workload, he said..

Epic当前的项目之一是评估使用人工智能帮助医生在患者就诊前查阅其病史。他表示，通过总结患者的心脏科医生近期的数据和化验结果等信息，这些工具可以节省医生的时间并减轻他们的脑力负担。

Meantime, computer technology firm Oracle said in October that it was planning to launch in 2025 a revamped electronic health record that incorporates generative AI-based summaries of patient conditions and medications and offers physicians access to additional summaries of patient treatments, side effects, and notes from previous visits.

同时，计算机技术公司甲骨文在十月份表示，计划于2025年推出一款经过改进的电子健康记录系统，该系统结合了基于生成式人工智能的患者状况和药物总结，并为医生提供患者治疗、副作用及以往就诊记录的额外总结。

Suhas Uliyar, senior VP of product development at Oracle, said in an email that the upcoming Oracle Health EHR system will be used to analyze myriad sources of patient data including tools that leverage conversational AI, offer treatment recommendations, and automate administrative tasks..

甲骨文产品开发高级副总裁苏哈斯·乌利亚尔在一封电子邮件中表示，即将推出的甲骨文健康电子病历系统将用于分析众多的患者数据来源，包括利用对话式人工智能、提供治疗建议和自动执行行政任务的工具。

Conversational AI is typically used to mimic human interactions by simulating conversation, and it has been employed in software such as chatbots or virtual agents.

会话式人工智能通常用于通过模拟对话来模仿人类互动，并已应用于聊天机器人或虚拟代理等软件中。

The new EHR will offer patient-specific chart summaries, analyze patient data to provide more precise treatment recommendations, review testing recommendations, and let doctors find, for example, a patient's three most recent HbA1c levels using a natural language-based search, Uliyar said. The firm is already seeing encouraging results from its Oracle Health Clinical AI Agent that is used to summarize charts and automate note taking, with physicians reporting they spend nearly 30 percent less time on documentation..

新的电子健康记录系统将提供针对患者的图表摘要，分析患者数据以提供更精确的治疗建议，审核检测建议，并让医生通过基于自然语言的搜索找到例如患者最近三次的糖化血红蛋白水平，Uliyar说道。该公司已经从其用于总结图表和自动记笔记的Oracle Health Clinical AI助手看到了令人鼓舞的结果，医生们报告称他们在文档处理上花费的时间减少了近30%。

'Meanwhile, in hospitals, AI tools can help triage patients, provide care pathway optimization, and improve clinical decision-making and operational efficiencies using predictive analytics,' Uliyar said. He added that labs can streamline their integration of diagnostic data and automatically provide physicians with relevant clinical records..

“同时，在医院中，人工智能工具可以帮助对患者进行分诊、优化护理路径，并通过预测分析改进临床决策和运营效率，”乌利亚尔说。他补充道，实验室可以简化诊断数据的整合，并自动向医生提供相关的临床记录。

Expanding beyond rules-based models

超越基于规则的模型

In the

在

in vitro

体外

diagnostics testing space, the use of AI may be most common in digital pathology. AI-based algorithms have

诊断测试空间，AI的使用在数字病理学中可能最为常见。基于AI的算法已经

proliferated in digital pathology

在数字病理学中激增

and formed the basis of tests for various conditions such as

并构成了各种条件下测试的基础，例如

pulmonary disease

肺部疾病

and

和

sepsis

败血症

. In addition to analyzing individual test results to aid the diagnosis of disease, healthcare firms see the potential to use AI-developed tools to provide broader analysis of patterns in patient health records.

除了分析单个测试结果以帮助诊断疾病外，医疗公司还看到了利用人工智能开发的工具来提供患者健康记录中更广泛模式分析的潜力。

Stephan Fihn is co-leader of University of Washington Medicine's Predictive Analytics Committee, whose work includes investigating new ways to deploy AI in healthcare and medical research. He estimates that healthcare providers have now developed tens of thousands of algorithms designed to predict patient outcomes, although far fewer have been deployed so far for clinical use..

斯蒂芬·菲恩是华盛顿大学医学院预测分析委员会的联合负责人，该委员会的工作包括研究在医疗保健和医学研究中部署人工智能的新方法。他估计，医疗服务提供者现在已经开发了成千上万种旨在预测患者结果的算法，尽管到目前为止，用于临床的算法要少得多。

He said that UW Medicine has spent enormous amounts of time testing AI-based alert systems in Epic's EHR system and integrating them into workflows. The system's sepsis model, for example, is used to alert physicians and nurses to consider implementing the sepsis protocol, and careful tuning is needed to provide alerts when interventions could help patients without overwhelming clinicians with false alarms..

他说，UW Medicine 花费了大量时间测试 Epic 电子健康记录系统中基于人工智能的警报系统，并将它们整合到工作流程中。例如，该系统的败血症模型用于提醒医生和护士考虑实施败血症协议，需要仔细调整以在干预措施可能帮助患者时发出警报，同时不会因误报让临床医生不堪重负。

Elad said that most of Cedars-Sinai's clinicians began using in the last year an AI-based tool to draft responses to patient messages, with tight guardrails to prevent it from proposing any testing, diagnosis, or treatment of disease. Fihn said that patients have been sending their doctors far more text messages since the pandemic, and physicians have been using such AI-developed tools to lighten the load..

埃拉德表示，塞达斯-西奈的大多数临床医生从去年开始使用一种基于人工智能的工具来起草对患者信息的回复，该工具有严格的限制，防止它提出任何检测、诊断或治疗疾病的建议。菲恩说，自疫情以来，患者一直在给医生发送更多的短信，医生们则一直使用这种人工智能开发的工具来减轻负担。

Clinicians also have been using 'ambient listening' models to dictate conversations during patient visits and generate notes in the EHR.

临床医生还一直在使用“环境监听”模型，在患者就诊期间口述对话并生成电子健康记录中的笔记。

'It does allow me to focus more on really taking care of the patient, really listening to them, and really having the opportunity to think about their care,' Elad said.

“它确实让我能够更加专注于真正照顾患者，真正倾听他们，并且真正有机会思考他们的护理，”埃拉德说。

He expects that future iterations of those scribes could hear a doctor tell a patient with recent chest pain that they need a stress test and a cholesterol panel and respond by automatically teeing up draft orders for the physician to sign.

他预计，未来这些抄写员的迭代版本能够听到医生告诉最近胸痛的患者需要进行压力测试和胆固醇检查，并自动为医生准备好待签署的草稿订单。

Epic's Lindemann said that a hospital in Ohio has been using Epic's AI-based tools to review text-based notes from radiology findings to identify incidental findings that may require follow-up, and some reports have resulted in the earlier identification of cancers. Other customers have also been using AI-based tools with the company's health records to reduce readmissions by identifying the patients who are most likely to need follow-up visits or reminders to adhere to their medication schedules..

Epic的林德曼表示，俄亥俄州的一家医院一直使用Epic基于人工智能的工具来审查放射学结果中的文本笔记，以识别可能需要跟进的偶然发现，一些报告促成了癌症的早期识别。其他客户也一直在利用该公司健康记录中的人工智能工具，通过识别最有可能需要复诊或提醒遵守药物计划的患者，来减少再入院率。

While rules-based sepsis protocols have long been available, he said that more recently developed AI-based tools have been used to save lives by identifying sepsis and health deterioration sooner, resulting in faster ICU admissions and stabilization.

虽然基于规则的脓毒症协议早已存在，但他表示，最近开发的基于人工智能的工具通过更早识别脓毒症和健康状况恶化拯救了生命，从而加快了重症监护室的入院和稳定。

Expanding analysis of EHRs

扩展电子健康记录分析

Shounak Majumder, gastroenterologist and researcher for the Mayo Clinic, said that clinicians' notes contain a wealth of unstructured information, and last year he and 10 other Mayo researchers coauthored an

梅奥诊所的胃肠病学家兼研究员肖纳克·马朱姆德表示，临床医生的笔记包含了大量的非结构化信息，去年他和另外十位梅奥研究人员共同撰写了一篇论文。

article in

文章在

Pancreatology

胰腺学

on the identification of pancreatic cancer risk factors from clinical notes using natural language processing.

利用自然语言处理从临床记录中识别胰腺癌风险因素。

Majumder said that such a tool can help primary care providers to identify which patients should receive risk-based cancer screening by finding notes about family history and prior genetic testing. It also could be used to help identify patients who would benefit from genetic testing.

马朱姆德尔表示，这种工具可以帮助初级保健提供者通过查找有关家族史和先前基因检测的记录，来识别哪些患者应该接受基于风险的癌症筛查。它还可以用于帮助识别哪些患者会从基因检测中受益。

'A tool like this brings that information to the surface and enables a physician to act on it,' he said.

“像这样的工具将信息呈现出来，并使医生能够对其采取行动，”他说道。

He noted that while screening and early detection improves outcomes, pancreatic cancer is usually not diagnosed until it is in an advanced stage. While MRI and endoscopic ultrasound are typically used for screening, he noted that multiple companies have been developing blood-based tests for biomarkers of early-stage pancreatic cancers..

他指出，虽然筛查和早期发现可以改善预后，但胰腺癌通常在晚期才被诊断出来。虽然通常使用磁共振成像（MRI）和内窥镜超声进行筛查，但他提到多家公司一直在开发基于血液的早期胰腺癌生物标志物检测方法。

Mainz Biomed and Liquid Biosciences, for example,

例如，美因茨生物医学公司和液体生物科学公司，

announced last month

上个月宣布的

that they had formed a collaboration to develop a blood-based early detection test for pancreatic cancer. Immunovia also recently said that it is

他们已经建立合作关系，共同开发一种基于血液的胰腺癌早期检测测试。Immunovia最近还表示，它正在

preparing to launch

准备启动

this year an antibody-based ELISA for identifying early-stage pancreatic ductal adenocarcinoma.

今年，一种基于抗体的ELISA技术被用于识别早期胰腺导管腺癌。

Majumder also said that AI-based tools are good at finding and presenting information that would be relevant to a physician examining a patient in the ER presenting with debilitating abdominal pain. How these tools are used, though, will depend on whether physicians see them as a benefit or another burden..

马朱姆德还表示，基于人工智能的工具擅长查找和呈现与急诊室中出现严重腹痛的患者相关的资料。然而，这些工具的使用方式将取决于医生是否将其视为一种好处或额外的负担。

Meanwhile, Epic's Lindemann said that the company is focusing resources on the development of AI-based 'agents,' or applications that can orchestrate a series of clerical and clinical tasks for a clinician. A physician could use an agent to identify patients who are due for colorectal cancer screening and recommend either colonoscopy or the use of Exact Sciences' Cologuard test.

同时，Epic的林德曼表示，公司正集中资源开发基于人工智能的“代理”或应用程序，这些程序可以为临床医生协调一系列文书和临床任务。医生可以使用代理来识别需要进行结直肠癌筛查的患者，并推荐结肠镜检查或使用Exact Sciences公司的Cologuard测试。

If the Cologuard results show an elevated risk of cancer, the agent could use the results to automatically alert the patient and propose times for a follow-up colonoscopy, he said..

他说，如果 Cologuard 的结果显示癌症风险升高，该代理可以使用这些结果自动提醒患者，并提议进行后续结肠镜检查的时间。

'Think of a physician having a team of these virtual agents that are carrying out some of these really standard care pathways for cancer care, like colon cancer or breast cancer screening,' he said.

“想象一下，一位医生拥有一个由这些虚拟助手组成的团队，它们正在执行一些非常标准的癌症护理路径，例如结肠癌或乳腺癌筛查，”他说道。

Those agents also could be used for scheduling routine blood work or arranging follow-up messages to patients.

这些代理还可以用于安排常规血液检查或安排对患者的后续信息。

Elad said that Cedars-Sinai also has been working with a vendor to develop software that can generate narratives for patients on their lab results. Other projects involve augmenting the interpretation of radiology and electrocardiogram results.

埃拉德说，西达斯-西奈医疗中心也一直在与一家供应商合作开发软件，该软件可以为患者生成关于他们化验结果的叙述。其他项目涉及增强对放射学和心电图结果的解读。

Peter DeVault, VP of interoperability and genomics at Epic, said he hopes that AI-based tools will also help to improve access to genomic testing through better analysis of coverage requirements and clinical guidelines as well as alerts that tests are available. AI-based tools also could be used to support genome-wide and phenome-wide association studies that could lead to new predictive models that incorporate genotypic, phenotypic, and EHR data..

Epic的互操作性和基因组学副总裁彼得·德沃特表示，他希望基于人工智能的工具还能通过更好地分析覆盖范围要求和临床指南，以及提醒测试可用性，帮助改善基因组测试的获取途径。基于人工智能的工具还可以用于支持全基因组和全表型组关联研究，这可能会带来新的预测模型，将基因型、表型和电子健康记录数据纳入其中。

A note of caution

注意事项

Some voices in healthcare have called for a cautious approach, though, to make sure that AI technologies live up to their potential.

不过，医疗保健领域的一些声音呼吁采取谨慎的态度，以确保人工智能技术能够充分发挥其潜力。

Christian Rose and Jonathan Chen of Stanford University wrote last year in

斯坦福大学的克里斯蒂安·罗斯和乔纳森·陈去年写道

NPJ Digital Medicine

NPJ数字医学

that the electronic health record was once heralded as a way to reduce medical errors and improve efficiency, yet it has since increased administrative burden and burnout among clinicians. They called for caution to avoid repeating those mistakes with AI-developed tools.

电子健康记录曾被誉为减少医疗错误和提高效率的一种方法，但此后却增加了临床医生的行政负担和职业倦怠。他们呼吁谨慎行事，以避免在使用人工智能开发的工具时重蹈覆辙。

Poorly designed interfaces disrupt workflows and frustrate clinicians while information overload, alert fatigue, and the complexity of EHR systems contribute to missed diagnoses and care inefficiencies. Extensive data entry requirements cut into patient care time and contribute to exhaustion, as well..

设计拙劣的界面会打乱工作流程，使临床医生感到沮丧，而信息过载、警报疲劳以及电子健康记录系统的复杂性则会导致诊断遗漏和护理效率低下。大量的数据录入要求也削减了患者护理时间，并导致疲惫不堪。

'While these technologies may help prevent errors in specific scenarios, their widespread use has inadvertently hindered patient safety — the very thing they were meant to improve,' they wrote.

“虽然这些技术可能有助于在特定场景中预防错误，但它们的广泛使用却反而阻碍了患者安全——这恰恰是它们旨在改进的方面，”他们写道。

While the integration of AI-powered tools into EHRs is seen by some as the way to realize the benefits envisioned from EHRs, the authors said that user-centered design, data standards, ongoing refinements in response to user feedback, and user training are needed.

尽管将人工智能驱动的工具整合到电子健康记录（EHR）中被一些人视为实现电子健康记录预期效益的方式，但作者表示，需要以用户为中心的设计、数据标准、根据用户反馈进行的持续改进以及用户培训。

Elad said that how well AI-based suggestions are received by physicians depends on whether they are presented at the right time in the visit to provide relevant information. Alerts that are too early or late or occur during unrelated tasks contribute to alert fatigue.

埃拉德说，基于人工智能的建议是否能被医生接受，取决于这些建议是否在就诊的适当时间提供相关信息。过早或过晚的提醒，或在无关任务期间出现的提醒，会导致提醒疲劳。

Healthcare providers need to ensure that AI-developed models are trained on appropriate populations and designed to minimize the potential for 'hallucinations,' he said. Cedars-Sinai has developed AI councils for physicians, nurses, lab staff, and operations staff, and he noted that clinicians remain in charge of any decisions on patient care..

他说，医疗保健提供者需要确保人工智能开发的模型在合适的群体上进行训练，并设计为尽量减少“幻觉”的可能性。西达斯-西奈医院已经为医生、护士、实验室工作人员和运营人员成立了人工智能委员会，他指出，临床医生仍然负责任何有关患者护理的决策。

'While we're really excited about it, we also have to still keep our guard up and really put AI to the same kind of rigorous testing that we put any kind of new technology' through, Elad said.

“虽然我们对此感到非常兴奋，但我们也必须保持警惕，真正对人工智能进行与任何新技术相同的严格测试，”埃拉德说。