普华永道报告:人工智能导致医疗账单上涨
PwC Report: AI Making Medical Bills Higher

原始链接: https://fortune.com/2026/06/12/ai-making-medical-bills-higher/

一份普华永道(PwC)的最新报告揭示了一个出人意料的趋势:人工智能(AI)目前不仅没有降低医疗成本,反而推高了医疗费用。尽管人工智能常被吹捧为能提升行政效率,但医院正越来越多地利用它来识别并记录细致入微的医疗细节,从而证明更高的计费代码是合理的,即便患者接受的实际护理并未改变。 该报告强调,“编码强度”(coding intensity)是导致医疗成本预计在2027年上涨9%的主要因素。例如,一些医院发现特定的高额赔付诊断——如急性失血性贫血——出现激增,但相应的临床治疗(如输血)却没有增加。审计显示,许多此类由AI生成的编码缺乏足够的临床证据支持。 虽然劳动力和供应成本仍是医疗通胀的主要驱动力,但人工智能已成为一股新的重大压力。通过优化计费以获取更高收益,人工智能目前正服务于医疗提供者的经济利益。尽管专家们希望人工智能最终能通过行政自动化和早期诊断来降低成本,但其当前的影响却让医疗变得更加昂贵。

普华永道(PwC)近期发布并被《财富》杂志报道的一份报告指出,人工智能工具正无意中推高医疗成本。这些工具通过“编码升级”(upcoding)助长了医疗欺诈——即医疗服务提供方利用AI将患者的病情描述得更严重,或将治疗手段标注得更昂贵,从而虚报账单。 Hacker News 上的讨论认为,虽然医疗账单欺诈在AI出现前就已存在,但这项技术很可能加速了这一过程,并提高了医疗机构的利润空间。评论者对营利性医疗体系表示了深度怀疑,指出由于医疗需求缺乏弹性,医疗机构无论效率如何,都能随心所欲地定价。一些人认为,保险公司未来可能会开发自己的“对抗性AI”来应对这些虚高账单,这可能引发一场代价高昂的技术军备竞赛。 与此同时,讨论还涉及了AI驱动的企业贪婪这一大趋势,以及人们对当代新闻质量的普遍不满。部分用户指出,该文章重复且简化的结构可能仅仅是该出版物的文风选择,而非AI生成内容(“垃圾信息”)的固有表现。
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原文

TL;DR: You might have expected AI to cut healthcare costs, whether it’s by reducing paperwork, automating the doctor’s notes, or thinning out hospital staff. But a new 60-page PwC report suggests the reverse: So far, one of its most widespread uses is making medical bills bigger. It’s an example of how AI isn’t only good at making tasks more efficient—it’s also very good at finding more granular ways to boost a sector’s bottom line.

What happened: AI is one of five potential drivers of health costs climbing up to 9% in 2027—matching this year’s rate, the highest since 2010–11—per PwC. The key reason: AI note-taking tools are documenting more specifics about diagnoses and medical complications that a rushed human clinician might have lumped into one broad “code”—a standardized billing label that tells insurers what to pay. Those extra details can justify a higher severity (read: higher paying) code, even if the actual care a patient receives is the same as before.

The devil is in the billing details: One Blue Cross Blue Shield analysis found that some hospitals saw the billing code for acute posthemorrhagic anemia in new mothers jump from 4% to 12.3% of maternity admissions between 2022 and 2025. The number of blood transfusions (a common treatment for this condition), meanwhile, barely budged. An audit of the hospital system with the steepest rise in this code found that fewer than 20% of the cases actually met the clinical criteria for a diagnosis. The rise in higher-intensity coding coincides with hospitals’ growing use of AI for billing. According to BCBS, “coding intensity” added $22 million to maternity spending at the hospitals studied in three years.

The big but: AI is the report’s top-ranked new pressure, but it’s not the biggest driver of costs overall—old standbys like labor and supply costs still account for more of the increase, one of the report’s authors told Healthcare Dive. And AI tools could eventually push the other way, driving down costs by automating hospital administrative work or catching diagnoses earlier.

Bottom line: AI is often pitched as a way to optimize whatever industry it touches—trimming waste and making systems faster and cheaper. But in healthcare, one of the first things it has optimized is how to charge you more. As one health insurance exec put it: Companies “will take AI and say, ‘How can I use this to further my self-interest?’” —WK

This report was originally published by Tech Brew.

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