[2026 Latest] Focus on patient-centered care: Automated IC documentation via AI voice input.

In Japan's medical field, one of the primary factors increasing the burden on physicians is "documentation work." In particular, recording informed consent (IC) is critical for medical safety and litigation risk avoidance; however, the more detailed the records, the more time physicians spend typing during consultations, losing valuable eye contact with their patients. This article explores the forefront of medical DX, where the latest medical AI voice input technology is used to structure and record dialogue in real-time, simultaneously achieving work-style reform for physicians and improving patient satisfaction.

1. The Limitations of "Computer-Centric Consultations" and Physician Burnout

When speaking with physicians in actual support settings, the most common concern we hear is a "reversal phenomenon" where post-consultation charting and paperwork take longer than the examination itself. From the patient's perspective, seeing a doctor touch-typing while listening to their concerns leads to dissatisfaction, with patients feeling uneasy because "the doctor is only looking at the screen." This is a serious issue that pushes a physician's cognitive load (Cognitive Load) to the limit, ultimately leading to burnout (burnout syndrome).

In the field of support, the challenge is not simply about efficiency, but how to build an environment where doctors can focus on their primary roles of "diagnosis and treatment." The UI/UX optimization expertise we have cultivated through In-house EC Site Construction and Growth Support to establish business foundations is also applicable to improving system workflows in medical settings. Freeing doctors' hands from the keyboard and returning their gaze to the patient is the first step toward medical DX.

2. Structuring Process for IC Records via AI Voice Input

最新の医療AIは、単に音声をテキスト化するだけではありません。自然言語処理（NLP）技術を用いることで、医師と患者の非構造的な会話から、主訴、所見、診断、治療方針といったカルテ項目を自動で抽出・分類します。特にインフォームド・コンセント（IC）においては、「副作用の説明をしたか」「代替案を提示したか」といった必須項目をAIがチェックし、漏れのない記録を生成します。

In our actual support projects, the key to successful implementation lies in registering medical-specific terminology and addressing dialects and ambiguous expressions. By leveraging Large Language Models (LLMs) specialized in the medical domain rather than general-purpose AI, we can accurately structure specialized clinical dialogues. This enables a workflow where a nearly complete draft of the medical record is generated the moment the examination concludes.

3. Contribution to Medical Safety and Risk Management

For healthcare professionals, accurate records are the best defense. When relying on memory to write medical records in bulk after consultations, information loss or distortion is inevitable. Real-time recording by AI objectively preserves evidence of 'who explained what and when,' which drastically reduces the risk of future disputes. A common issue in clinical settings is when busy schedules lead to the omission of critical explanations that later become problematic; AI serves as a partner to fill those 'documentation gaps.'

Furthermore, this structured data can also be utilized for secondary purposes. From a hospital management perspective, analyzing which explanations contribute to patient satisfaction (retention rates) directly leads to improvements in medical services across the entire organization. This is an area with high affinity for the strategic approach of Direct-to-Consumer (D2C) EC Site Development and Growth Support, which focuses on accumulating and analyzing customer data to maximize LTV.

4. Quantitative Effects of Implementation: Reduction in Administrative Work Hours

The impact of implementing AI voice input is clearly reflected in the data. Based on our research and implementation cases, the average daily time spent on medical records per physician has been significantly reduced compared to before implementation. The following chart shows the change in the distribution of work hours in a typical outpatient consultation.

As shown in the chart, medical record entry time plummeted from 40% to 15%, and the time allocated for 'patient interaction' has increased by approximately 1.5 times. This is not just about saving time; these figures represent a transformation in the quality of medical care itself. While reducing physician burnout, creating time where patients feel they have been 'truly listened to' will be the winning strategy for medical management from 2026 onward.