如何让临床医生保持满意：Ascension之道
How to Keep Clinicians Satisfied, the Ascension Way
AI记录员让医生无需在整个患者就诊过程中持续打字，但对于患者离开诊室后临床医生面临的大量行政事务，仍有许多工作需要推进。
Ascension正通过将AI的应用范围从记录笔记扩展到就诊结束后会变得棘手的任务（如医嘱录入和计费），来解决这一问题。据该医疗系统首席临床官Thomas Aloia介绍。
环境式聆听和AI驱动的记录工具已经很好地帮助医生减轻了记录笔记的负担，但患者离开后，他们仍然需要检查AI生成的记录是否准确、下达医嘱，并且在某些情况下协助计费。Aloia认为，下一步的重大突破将是能够实时预测这些任务的AI——这样，工具就能感知何时需要下达医嘱，并提示医生当场确认，而不是事后再处理。
由以下机构呈现赞助文章从盲点到更佳结果：SNF数据透明度如何强化LTSS如果健康计划能够在可避免的住院发生之前识别成员状况恶化，会怎样？对长期住院SNF成员进行实时临床可视化，可以更早发现风险并推动更佳结果。
作者：Centene Corporation LTSS产品与战略副总裁Anna Keith，以及Real Time Medical Systems基于价值的护理执行副总裁、RN Phyllis Wojtusik“我们确实看到了这样一个时间点：我们可以拥有一项完全自动化的任务，并配备审计备份。”Aloia在谈到计费和编码时说。
他指出，Ascension的医生“不是计费专家；他们是医生专家”，这也是该医疗系统关注多家供应商开发能够自动对记录进行编码和计费的工具的部分原因。
Aloia表示，合规始终是第一位的，但他也很清楚手动处理的局限性。
“编码和计费中存在一定程度的人为错误。”Aloia说，并补充道，从准确性和一致性两方面来看，AI与强大的审计机制相结合，最终可能优于人类。
由以下机构呈现赞助文章缩小职场心理健康领域的质量与可负担性差距在一次采访中，Kyan Health联合创始人兼首席商务官Konstantin Struck讨论了Kyan如何让中型市场和企业雇主能够获得高端员工心理健康服务，同时价格也在可负担范围内。
作者：Stephanie Baum
及时性也会影响这一点。Aloia指出，一份记录在最终确定前搁置的时间越长，医生对就诊情况的记忆就会淡化；他表示，这进一步凸显了配备内置审计轨迹的实时系统的必要性。
但在Ascension，受益于AI驱动文档工具的并不只有医生。在住院服务方面，该医疗系统已经推出AI摘要功能，帮助护士为下一班次准备交接报告——这项任务过去通常需要耗时一个半小时。Aloia说，如今AI只需几分钟就能生成患者近期病史摘要。
Aloia指出，这只是Ascension利用AI的多种方式之一，其目的不仅是节省时间，还要减少手动流程中长期存在的那类差异性。
在他看来，这两个例子都凸显了当前大多数医疗系统所关注的目标：利用AI将时间还给临床医生，让他们能够专注于患者护理，而不是文书工作。正如他所说，这关乎“医生满意度、在工作中创造愉悦感、回归职业使命”。
图片：iodrakon，Getty Images
AI scribes have freed physicians from having to type all throughout patient visits, but there’s still a lot of progress that needs to be made on the pile of administrative chores clinicians face once the patient leaves the room.
Ascension
is working to solve that issue by extending AI beyond note-taking and into the tasks that become a headache once the visit ends, like order entry and billing, according to Thomas Aloia, the health system’s chief clinical officer.
Ambient listening and AI-powered scribing has done a great job of offloading the note-taking burden from physicians, but after the patient leaves, they still have to review the AI-generated note for accuracy, place orders, and in some cases help with billing. Aloia thinks the next leap forward is AI that can anticipate those tasks in real time — so that tools can sense when an order needs to be placed and prompt the physician to confirm it on the spot, rather than after the fact.
“We do see a time point where we have a fully automated task with audit backup,” Aloia said of billing and coding.
He noted that Ascension physicians “are not expert billers; they’re expert doctors,” which is part of why the health system is watching several vendors develop tools that can code and bill a note automatically.
Compliance will always come first, Aloia stated, but he is also realistic about the limits of manual processing.
“There’s a certain amount of human error in coding and billing,” Aloia said, adding that AI paired with a strong audit mechanism could ultimately outperform humans in terms of both accuracy and consistency.
Timeliness plays into that too. Aloia pointed out that the longer a note sits before it’s finalized, the more a physician’s memory of the visit fades, which he said reinforces the need for a real-time system with a built-in audit trail.
But physicians aren’t the only clinicians benefiting from AI-driven documentation tools at Ascension. On the inpatient side, the health system has rolled out AI summarization to help nurses prepare handoff reports for the next shift — a task that has traditionally taken up to an hour and a half. Aloia said AI now generates a summary of a patient’s recent history in a matter of minutes.
Aloia noted it’s one of several ways Ascension is using AI not just to save time, but to reduce the kind of variability that’s long been baked into manual processes.
To him, both examples underscore a goal that most health systems are focused on right now: using AI to give time back to clinicians so they can focus on patient care instead of paperwork. As he put it, it’s about “physician satisfaction, creating joy in work, returning to vocation.” Photo: iodrakon, Getty Images