The use of AI in healthcare has evolved quite a bit over the past few years — with many healthcare organizations transitioning from a state of cautious experimentation to more serious attempts at

在过去的几年里，人工智能在医疗保健领域的应用有了相当大的发展——许多医疗机构从谨慎试验阶段过渡到更加认真的尝试。

scaled integration

缩放整合

. As millions of venture capital dollars

. 数百万的风险投资资金

continue to flow

继续流动

to startups developing healthcare AI, it’s clear that organizations across the industry will be leveraging this technology to optimize workflows and improve patient outcomes for years to come.

对于开发医疗保健人工智能的初创企业来说，很明显，未来几年内，整个行业的组织都将利用这项技术来优化工作流程并改善患者预后。

As this trend continues, healthcare leaders are becoming increasingly interested in the category of agentic AI. Experts

随着这一趋势的持续，医疗保健领域的领导者们对主动型人工智能类别越来越感兴趣。专家们

predict

预测

that AI agents — autonomous, task-specific systems designed to perform functions with little or no human intervention — will likely become increasingly popular in healthcare over the next couple years.

人工智能代理——设计为在极少或无需人类干预的情况下执行特定任务的自主系统——在未来几年内很可能会在医疗保健领域变得越来越受欢迎。

The industry is facing growing pressures to achieve cost containment without compromising care quality, and health tech experts believe AI agents are a scalable solution that can help with this arduous goal.

该行业面临着在不降低护理质量的前提下控制成本的日益增长的压力，而健康技术专家认为人工智能代理是一种可扩展的解决方案，有助于实现这一艰巨目标。

Healthcare

医疗保健

Using Data to Help Healthcare Practices Succeed

利用数据帮助医疗实践取得成功

A new report from Relatient, A Data-Driven Guide to Patient Access Succes, highlights how focusing on data accuracy and relevance can enhance the performance of healthcare practices.

Relatient 的一份新报告《数据驱动的患者访问成功指南》强调了如何通过关注数据的准确性和相关性来提升医疗实践的绩效。

By Relatient

由 Relatient 发布

Why are AI agents getting so much buzz?

为什么人工智能代理如此受关注？

AI agent is somewhat of a buzzword, admitted Punit Soni, CEO of

AI代理某种程度上是一个流行词，Punit Soni承认，他是

Suki

苏琪

.

。

Suki sells an AI agent for physicians. By calling out to the AI-powered assistant, a physician can quickly access key information about their patient, such as their medications, vital signs, allergies or surgical histories. Physicians can also use Suki’s tool to do things like pull up their weekly schedule, dictate clinical notes and assist with ICD-10 coding..

Suki销售面向医生的人工智能助手。通过呼唤这个人工智能助理，医生可以快速获取患者的关键信息，例如他们的药物、生命体征、过敏史或手术史。医生还可以使用Suki的工具来做一些事情，比如拉取他们每周的日程安排、口述临床笔记以及协助进行ICD-10编码。

The agent can also complete tasks autonomously, such as ordering labs, setting up follow-up visits and sending appointment reminders. Its list price is $399 per user per month.

该代理还可以自主完成任务，例如下达实验室订单、安排随访和发送预约提醒。其标价为每位用户每月 399 美元。

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赞助帖子

Tackling Messy Provider Data with an NPI-Forward Approach

使用NPI前向方法解决杂乱的供应商数据问题

Mike Wirth of ProviderTrust shares insights about the company in this interview at the ViVE 2025 conference in Nashville last month.

上个月在纳什维尔举行的 ViVE 2025 大会上，ProviderTrust 的迈克·威尔斯 (Mike Wirth) 在此次采访中分享了有关该公司的见解。

By ProviderTrust and MedCity News

由ProviderTrust和MedCity News提供

In Soni’s view, AI agents are simply building on the foundation of all the AI models that came before — combining predictive capabilities with actions and data to perform tasks. These tools are dubbed “agents” because they mimic human-like assistance, he explained.

在索尼看来，人工智能代理只是在之前所有人工智能模型的基础上进行构建——结合预测能力、行动和数据来执行任务。他解释说，这些工具被称为“代理”，因为它们模仿了类似人类的帮助。

He noted that healthcare can benefit greatly from AI agents, as the field is rife with inefficient workflows.

他指出，医疗保健可以从人工智能代理中获益良多，因为该领域充斥着低效的工作流程。

“Agentic AI works best when the user is incredibly sophisticated, when the workflows that you’re making better are incredibly repeatable, and when the ontology and knowledge that’s required is fixed. In those situations, AI actually is very effective,” Soni stated, adding that healthcare checks all those boxes..

“当用户非常老练、当你要改进的工作流程极具可重复性，并且所需的知识体系和信息是固定的时候，代理型人工智能的效果最佳。”索尼表示，并补充说医疗保健完全符合这些条件。

He said that AI agents should be assistive and invisible, with the main goal of allowing clinicians to focus more on patient care.

他说，人工智能代理应该起到辅助作用且不显山露水，主要目标是让临床医生更加专注于患者护理。

How can providers deploy AI agents?

提供商如何部署人工智能代理？

Soni said that agentic AI will see widespread adoption first for back-end, administrative use cases. When it comes to AI in the healthcare sector, this is always the first step, he noted. Some use cases include autonomous prior authorization requests and call center agents.

索尼表示，代理型人工智能将首先在后端、行政管理使用场景中得到广泛应用。他指出，在医疗保健领域，这始终是第一步。一些使用案例包括自主事先授权请求和呼叫中心代理。

Another healthcare expert — Naimish Patel, head of healthcare at

另一位医疗保健专家——Naimish Patel，医疗保健部门负责人

Red Cell Partners

红细胞伙伴

, an investment and incubation firm — agreed with Soni. He also said healthcare organizations will begin by deploying AI agents in non-clinical use cases, with clinical applications to follow.

，一家投资和孵化公司——同意索尼的观点。他还表示，医疗保健组织将首先在非临床用例中部署人工智能代理，随后将应用于临床。

In Patel’s view, AI agents focused on the patient journey will see the greatest adoption. For example, there are agentic AI models that can autonomously schedule appointments and check in with patients to see if they’re following their care plan at home, he explained.

在帕特尔看来，专注于患者旅程的人工智能代理将得到最广泛的采用。例如，他解释说，有一些自主性人工智能模型可以自动安排预约，并跟进患者以查看他们是否在家中遵循护理计划。

“That’s a pretty low-stakes use case, but there are lots of areas where AI can greatly improve that process. Think about the specific preferences certain providers have — you may have three dermatologists, but one of those dermatologists may not perform certain procedures. Knowing which dermatologist performs which procedure and looking for availability are all multiple steps that a person would be doing — but now the AI can do it almost instantaneously,” Patel declared..

“这是一个风险较低的使用案例，但人工智能可以在许多领域大大改进这一过程。想想某些供应商的具体偏好——你可能有三位皮肤科医生，但其中一位可能不执行某些程序。知道哪位皮肤科医生执行哪个程序并寻找可用性，这些都是一个人需要完成的多个步骤——但现在人工智能几乎可以瞬间完成，”帕特尔表示。

InTrivo

因特里沃

is an example of a company selling agentic AI tools to complete the tasks Patel described for patients, as well as help them schedule appointments.

是一家向患者销售代理人工智能工具以完成帕特尔所描述的任务以及帮助他们预约的公司示例。

AI agents can also take over some basic tasks for busy healthcare staff — which is key given the sector’s ongoing workforce shortage.

人工智能代理还可以接管繁忙的医护人员的一些基本任务——鉴于该行业持续的劳动力短缺，这是关键。

Agentic AI can help alleviate the labor shortage by automating repetitive tasks, therefore allowing clinicians to focus on practicing at the top of their licenses. For instance, AI agents can make calls on behalf of nurses

能动型人工智能可以通过自动化重复性任务来帮助缓解劳动力短缺，从而使临床医生能够专注于在其执业许可范围内进行最高水平的实践。例如，人工智能代理可以代表护士拨打电话。

and send text messages to patients to remind them to pick up their medication or gather information about their recovery, Patel pointed out.

并向患者发送短信，提醒他们取药或收集有关他们康复的信息，Patel指出。

Some examples of companies selling agentic AI for these use cases include

一些为这些用例销售代理型人工智能的公司示例包括

Notable

值得注意的

,

，

Luma Health

光健康

and

和

Hyro

海罗

.

。

One agentic AI company —

一家代理型人工智能公司——

VoiceCare AI

语音护理AI

— has developed an agent specifically for providers’ revenue cycle management teams.

— 已经专门为供应商的收入周期管理团队开发了一种代理。

The startup’s agent, named Joy, makes its own business-to-business calls, for things like insurance verification, prior authorization, claims processing and appeals.

这家初创公司的代理名为 Joy，可以自行拨打企业对企业电话，处理保险验证、事先授权、理赔处理和申诉等事务。

Mayo Clinic is currently using the tool. Joy is making calls on Mayo’s behalf and then providing the health system with summaries of the outcomes, explained VoiceCare AI CEO Parag Jhaveri.

梅奥诊所目前正在进行测试。Joy 代表梅奥诊所拨打电话，然后向卫生系统提供结果摘要，VoiceCare AI 首席执行官 Parag Jhaveri 解释道。

“Let’s say we wanted to get a prior auth approval for a particular surgery or treatment. Joy can call the insurance company to ask if there is a prior auth on file or not. If there is not, she can initiate a prior auth — and she can follow up with the prior auth when it is approved to get the prior auth approval number and the reference ID.

“假设我们需要为某个特定手术或治疗获得事先授权批准。Joy可以打电话给保险公司，询问是否有事先授权的记录。如果没有，她可以启动事先授权流程——并且在授权被批准后跟进，以获取事先授权批准号和参考ID。

The patient can be seen by the doctor, and every conversation is recorded on the cloud,” he said..

“病人可以由医生看诊，而且每一次对话都会记录在云端，”他说道。

Automating these phone calls end-to-end eliminates a “tremendous” amount of tedious work, Jhaveri pointed out.

Jhaveri 指出，端到端自动化这些电话消除了“大量”繁琐的工作。

He said he was recently on a call with leaders from another large health system who told him their imaging department makes 70,000 calls to insurers per month.

他说他最近与另一家大型卫生系统的领导人通话，对方告诉他，他们的影像科每月要给保险公司打7万个电话。

“They were saying, ‘Hey, can we free up these people to do other things?’ It’s slowly manifesting into becoming a reality as we speak,” Jhaveri declared.

“他们一直在说，‘嘿，我们能不能让这些人腾出来做其他事情？’ 正如我们所说，它正在慢慢变成现实，”贾维里宣称。

He said this tool usually costs between $4.02 and $4.49 per hour on a consumption-based pricing model. Providers with higher call volumes pay a rate closer to the less expensive side of this range, and providers with lower call volumes pay a rate toward the more expensive side.

他说，该工具通常在基于消费的定价模式下每小时花费 4.02 美元到 4.49 美元。通话量较高的供应商支付的费率接近此范围较低的一端，而通话量较低的供应商支付的费率则接近较高的一端。

Jhaveri mentioned that VoiceCare also has an outcomes-based model, meaning providers have to pay only if the agent successfully delivers results. For providers opting for this pricing model, the agent costs between $4.99 and $5.99 per hour.

贾维里提到，VoiceCare 还有一种基于结果的模式，这意味着提供商只有在代理成功交付结果时才需要付费。对于选择这种定价模式的提供商，代理每小时的费用在 4.99 美元到 5.99 美元之间。

How can payers deploy AI agents?

付款人如何部署人工智能代理？

Payers can also leverage agentic AI to improve member satisfaction. For instance, automation company

支付者还可以利用代理人工智能来提高会员满意度。例如，自动化公司

Ushur

乌舒尔

released a new

发布了新的

health plan-focused AI agent

专注于健康计划的人工智能代理

this week.

本周。

Ushur CEO Simha Sadasiva said he began his company because of the experience he had as the primary caregiver for his terminally ill mother. Every couple of weeks, he would spend hours on the phone with her health plan, often on hold and waiting to be transferred.

Ushur首席执行官Simha Sadasiva表示，他创办公司是因为他曾作为绝症母亲的主要照顾者时的经历。每隔几周，他都会花数小时与母亲的健康计划部门通电话，经常处于等待状态并被转接。

Ushur’s agent enables payers to automate member requests that would typically require human intervention at call centers. Unlike traditional chatbots that simply provide scripted answers to frequently asked questions, Ushur’s agentic AI can process and fulfill service requests, such as issuing a member ID card or scheduling a procedure — eliminating the need for human call center agents to manually perform these routine tasks, Sadasiva said..

Ushur的代理程序使支付方能够自动化处理通常需要呼叫中心人工干预的会员请求。Ushur的智能AI不同于传统的聊天机器人，后者只能提供针对常见问题的预设答案，而Ushur的AI可以处理并完成服务请求，例如发放会员卡或安排手术流程，从而无需人工呼叫中心代理手动执行这些常规任务，萨达西瓦表示。

As of 2023, the average annual cost of operating a healthcare call center is nearly

截至2023年，运营医疗保健呼叫中心的平均年度成本接近

$14 million

1400万美元

.

。

“For example, a member may need their member ID card. Rather than sending that request to another worker and then waiting for somebody to actually make sure that member ID card is shipped out to the end customer, we can now take that entire workflow, digitize it, and offer that member ID card through a digital channel that can now be in your wallet on your phone.

“例如，会员可能需要他们的会员身份证。过去，我们需要将这个请求发送给其他工作人员，然后等待有人确保将会员身份证寄送给最终客户，现在我们可以将整个工作流程数字化，并通过数字渠道提供会员身份证，这样它就可以直接保存在你手机的钱包里了。”

That’s an example of getting access to service requests in a jiffy — in a matter of a few seconds — as opposed to the hoops that end customers have to navigate,” he explained..

“这是一个快速获取服务请求的示例——在几秒钟内——相比于最终用户必须经历的繁琐流程，”他解释道。

In just two months, Ushur’s AI agent resolved over 36,000 interactions autonomously for one of its health plan customers, Sadasiva noted. He pointed out that this member adoption occurred organically, with members discovering the tool through self-service options on the health plan’s website.

萨达西瓦指出，仅仅两个月的时间，Ushur的AI代理就为其中一家健康计划客户自主解决了超过36,000次互动。他指出，这种会员采用是有机发生的，会员通过健康计划网站上的自助服务选项发现了该工具。

How do AI agents generate value?

AI代理如何创造价值？

Another healthcare technology expert — Kimberly Powell, vice president and general manager of healthcare at

另一位医疗技术专家——金伯利·鲍威尔，英伟达医疗保健部门的副总裁兼总经理

Nvidia

英伟达

— argued that AI agents can save providers time and money, while also enhancing the patient experience.

——认为人工智能代理可以为供应商节省时间和金钱，同时还可以改善患者的体验。

Nvidia is developing an AI enterprise platform to create task-specific AI agents, she noted. For example, the company recently created a preoperative agent for

她指出，英伟达正在开发一个用于创建特定任务AI代理的AI企业平台。例如，该公司最近为手术前创建了一个代理。

The Ottawa Hospital

渥太华医院

to provide patients with 24/7 access to reliable information about their surgeries.

为患者提供每天24小时、每周7天的手术相关信息的可靠访问。

Nvidia developed this AI-powered digital avatar to help answer patients’ questions about things like anesthesia, how to get ready for the procedure and recovery, Powell said. The agent increases patients’ preparedness and reduces their pre-procedure anxiety by offering continuous access to information, as well as alleviates the burden on hospital staff, she remarked..

Nvidia 开发了这款由人工智能驱动的数字虚拟人，帮助患者解答关于麻醉、如何为手术做准备以及术后恢复等问题，鲍威尔说道。她指出，该代理通过提供持续的信息访问，不仅提高了患者的准备度，减轻了他们的术前焦虑，还缓解了医院工作人员的压力。

“Pre-op appointments can take up to two hours, and these are conducted with a healthcare professional. But a lot of [the information shared during these appointments] — where to park, when to arrive — is not diagnostic or clinical information. But the patient needs to know it so they can adhere to the right instructions — so they can be there on time, and so they don’t have to cancel the surgery because they had any food that morning,” Powell stated..

“术前预约可能需要长达两个小时，而且这些预约是由医疗专业人员进行的。但是很多[在这些预约中分享的信息]——比如在哪里停车，什么时候到达——不是诊断或临床信息。但患者需要知道这些信息，以便遵循正确的指示——这样他们才能准时到达，不至于因为当天早上吃了东西而不得不取消手术，”鲍威尔表示。

The Ottawa Hospital sees Nvidia’s agent as a way to address its workforce shortages while also improving patient experiences, she added.

她补充说，渥太华医院认为英伟达的代理系统是解决其人手短缺问题的同时改善患者体验的一种方法。

She pointed out that The Ottawa Hospital conducts about 80,000 surgeries a year. In the past, each surgery required a pre-operative appointment lasting about two hours, she said.

她指出，渥太华医院每年进行约 8 万台手术。她说，过去每台手术都需要大约两个小时的术前预约。

“That’s 160,000 hours of preoperative appointments with healthcare staff. What if you could shrink each one of those appointments down by 50%? Then you’ve essentially given back to The Ottawa Hospital 80,000 hours of healthcare staff time,” Powell declared.

“这是16万小时的术前与医务人员的预约时间。如果能将每一次预约时间减少50%呢？那就相当于为渥太华医院的医护人员节省了8万小时的时间，”鲍威尔说道。

She also noted that patients are satisfied with Nvidia’s agent. Patients can ask the agent as many questions as they want — and people don’t always feel like they can do that with their provider, Powell noted. With an AI agent, patients don’t have to worry about feeling judged or getting a rushed answer, she added..

她还指出，患者对英伟达的代理感到满意。患者可以随心所欲地向代理提问——鲍威尔指出，人们并不总是觉得他们能这样与医疗服务提供者互动。她补充说，有了人工智能代理，患者不必担心被评判或得到仓促的回答。

The typical cost per use case when building out these digital teammates is between $500,000 and $1 million, according to a Nvidia spokesperson.

据英伟达发言人称，构建这些数字队友时，每个用例的典型成本在 50 万到 100 万美元之间。

How might AI agent adoption evolve?

AI代理的采用可能会如何演变？

Soni of Suki envisions a bright future when it comes to expanding the use cases for agentic AI in the healthcare realm. Beyond administrative workflows, AI agents could play a key part in keeping patients in the loop about their health, he noted.

Suki的索尼展望了在医疗领域扩展代理人工智能使用案例的光明未来。他指出，除了行政工作流程外，人工智能代理可以在让患者了解自身健康状况方面发挥关键作用。

“At some point, all the administrative activities will help clinicians teach the AI enough that it can potentially start helping them connect to patients,” he declared.

“在某种程度上，所有的管理活动将帮助临床医生教会人工智能足够的知识，以至于它有可能开始帮助他们与患者建立联系，”他宣称。

For example, AI agents may be able to instantly provide patients with after-visit summaries or answers to their questions in the EHR, Soni said.

例如，索尼表示，人工智能代理可能能够立即为患者提供就诊后的摘要或他们在电子健康记录中的问题答案。

He also pointed out that agentic AI could someday help physicians make clinical decisions.

他还认为，人工智能代理有一天可以帮助医生做出临床决策。

“At some point, [AI agents] will get enough information that they can start helping doctors with clinical acumen,” Soni stated.

“在某种程度上，[AI代理]将获得足够的信息，从而能够开始以临床敏锐度帮助医生，”索尼表示。

If this prediction becomes a reality, it won’t be anytime soon, he noted.

他指出，如果这一预测成为现实，也不会很快发生。

An AI expert from a health system — Jeff Jones, senior vice president of product development at

一位来自健康系统的AI专家——杰夫·琼斯，产品开发高级副总裁

UPMC Enterprises

UPMC企业

— said that for agentic AI to play a real role in clinical decision-making, it must be rigorously tested and proven. Otherwise, patients won’t be comfortable with their providers using it.

——表示，为了使代理型人工智能在临床决策中发挥作用，必须对其进行严格的测试和验证。否则，患者将无法接受医疗服务提供者使用它。

“Trust begins with proof. AI tools need to be accurate, reliable and safe before they can support a physician’s choices. Nearly as important, they must integrate seamlessly into clinical workflows, delivering meaningful insights at the right time without disrupting care delivery,” Jones stated.

“信任始于证据。在支持医生决策之前，人工智能工具必须做到准确、可靠和安全。同样重要的是，它们必须能够无缝融入临床工作流程，在恰当的时机提供有意义的见解，同时不干扰医疗服务的提供，”琼斯表示。

Ensuring that future generations of agentic AI are both effective and responsible will require close collaboration between health systems and technology partners.

确保未来几代自主人工智能既有效又负责任，将需要卫生系统和技术伙伴之间的密切合作。

Solutions like UPMC Enterprises’ Ahavi platform, which was

像UPMC Enterprises的Ahavi平台这样的解决方案，该平台

released

发布

last month, allows hospitals to test AI tools on de-identified patient data before they are ever deployed on real-world patients, he pointed out.

他指出，上个月，医院被允许在现实患者身上部署之前，对人工智能工具进行去标识化的患者数据测试。

Another health system AI expert — Zafar Chaudry, chief digital officer and chief AI and information officer at

另一个健康系统AI专家——Zafar Chaudry，首席数字官兼首席人工智能和信息官 tại

Seattle Children’s

西雅图儿童医院

— noted that realizing agentic AI’s potential in clinical decision-making “requires substantial progress.”

“要充分释放主动式人工智能在临床决策中的潜力，还需要取得重大进展。”

“This includes developing AI models with verifiable, transparent reasoning, conducting extensive clinical trials to ensure safety and accuracy, and establishing clear legal and ethical standards for its deployment,” Chaudry said.

“这包括开发具有可验证、透明推理的人工智能模型，进行广泛的临床试验以确保安全性和准确性，并为其部署建立明确的法律和伦理标准，”乔杜里说。

What might the future hold?

未来可能会怎样？

Powell of Nvidia pointed out another exciting use case she thinks may gain popularity: disaster relief agents.

英伟达的鲍威尔指出了另一个她认为可能会受欢迎的令人兴奋的应用案例：救灾代理。

She mentioned that

她提到 rằng

Hippocratic AI

希波克拉底人工智能

has already created disaster relief agents to check in with patients and provide information during situations like wildfires, heatwaves and freezes.

已经创建了救灾代理，以便在野火、热浪和寒潮等情况下与患者联系并提供信息。

“They can deploy agents that can reach out to patients to see if they are in need of urgent care, or to help them keep the continuity of their dialysis treatment,” she explained. “You would never have enough nurses or healthcare staff to be able to deploy on a moment’s notice, or at the scale of hundreds of thousands of people.”.

“他们可以部署能够联系患者的代理，查看他们是否需要紧急护理，或者帮助他们保持透析治疗的连续性，”她解释说。“你永远不会有足够的护士或医疗人员能够随时部署，或者在数十万人的规模上进行部署。”

Hippocratic has made a big splash in the agentic AI space, having snagged $278 million in funding since

Hippocratic在代理AI领域引起了巨大轰动，自成立以来已获得2.78亿美元的融资。

being founded

被创立

in 2023. Despite its fundraising success, AI expert and self-proclaimed “healthcare AI fraud investigator” Sergei Polevikov has

2023年。尽管其募资成功，但人工智能专家、自称“医疗保健人工智能欺诈调查员”的谢尔盖·波利维科夫

criticized

批评

the company, saying that thousands of outsourced nurses have to monitor every AI interaction. Hippocratic CEO Munjal Shah declined to be interviewed for this article.

该公司表示，成千上万名外包护士必须监控每次人工智能互动。希波克拉底首席执行官穆恩贾尔·沙阿拒绝就本文接受采访。

Another person who is deeply familiar with healthcare AI —

另一位对医疗人工智能有深入了解的人——

Innovaccer

英诺维克

CEO Abhinav Shashank — thinks AI agents have the potential to help scale value-based care models. His company

首席执行官阿比纳夫·沙尚克认为，人工智能代理有潜力帮助扩大基于价值的护理模式的规模。他的公司

launched

已启动

a suite of AI agents for providers last month, including tools that can complete tasks such as referrals, coding and prior authorization.

上个月，为供应商提供了一套人工智能代理工具，这些工具可以完成诸如转诊、编码和事先授权等任务。

As healthcare AI developers continue to apply agentic AI to new use cases, Shashank believes there is a future in which agent-driven care management can expand preventive outreach beyond just the highest-risk patients.

随着医疗保健AI开发者继续将代理型AI应用于新的用例，Shashank认为未来代理驱动的护理管理可以将预防性服务扩展到最高风险患者之外的人群。

“If anyone is going into a value-based care contract, through their care coordination efforts, they’re only able to touch 5% of the highest-risk patients,” he said.

“如果有人要签订基于价值的护理合同，通过他们的护理协调工作，他们只能接触到5%的最高风险患者，”他说。

But with AI agents autonomously calling and sending messages to patients, providers could proactively engage a much larger group — closer to 50% of high-risk patients, leading to earlier interventions and better outcomes, Shashank explained.

但是，沙尚克解释说，通过人工智能代理自主地给患者打电话和发送信息，医疗服务提供者可以主动接触更多的群体——接近50%的高风险患者，从而实现更早的干预和更好的结果。

Tedious tasks like patient outreach, prior authorization and appointment scheduling are not the best use of healthcare staff’s time — especially when the industry is

像患者外展、事先授权和预约安排这样繁琐的任务并不是医疗人员时间的最佳利用方式 —— 尤其是在这个行业是...

projected

投影的

to face a shortage of 3.2 million workers by 2026. The magnitude of this problem is why Shashank said he is not worried about all the other companies releasing AI agents for healthcare in recent months.

到2026年将面临320万工人短缺的问题。这个问题的严重性就是沙尚克说他并不担心近几个月其他公司推出的医疗保健AI代理的原因。

“After the last generation of technology that came into healthcare, productivity dropped. I think, as tech companies, we need to be responsible for helping our doctors deliver better care —  it’s just such a large problem to solve, the more tools the better,” he declared.

“在上一代技术进入医疗保健领域后，生产力下降了。我认为，作为科技公司，我们需要负责帮助我们的医生提供更好的护理——这是一个非常大的问题，需要解决，工具越多越好，”他宣称。

To him and the other executives interviewed in this article, the next frontier in healthcare AI isn’t just intelligence — it’s action.

对他以及本文采访的其他高管来说，医疗保健人工智能的下一个前沿不仅仅是智能——而是行动。

Photo: Andrzej Wojcicki, Getty Images

照片来源：安德烈·沃伊切基，盖蒂图片社