Jeon Hyewon, Yu Su-Yeon, Chertkova Olga, Yun Hyejung, Ng Yi Lin, Lim Yan Yoong, Efimenko Irina, Makhlouf Djoubeir Mohamed
Roche Product Development Safety Risk Management, Roche Products Pty Limited, Sydney, Australia.
Department of Pharmacy, College of Pharmacy, Kangwon National University, Chuncheon, Republic of Korea.
BMC Med Inform Decis Mak. 2025 Mar 18;25(1):137. doi: 10.1186/s12911-025-02929-5.
In this era of active online communication, patients increasingly share their healthcare experiences, concerns, and needs across digital platforms. Leveraging these vast repositories of real-world information, Digital Listening enables the systematic collection and analysis of patient voices through advanced technologies. Semantic-NLP artificial intelligence, with its ability to process and extract meaningful insights from large volumes of unstructured online data, represents a novel approach for understanding patient perspectives. This study aimed to demonstrate the utility of Semantic-NLP technology in presenting the needs and concerns of patients with age-related macular degeneration (AMD) in Korea and Taiwan.
Data were collected and analysed over three months from January 2023 using an ontology-based information extraction system (Semantic Hub). The system identified patient "stories" and extracted themes from online posts from January 2013 to March 2023, focusing on Korea and Taiwan by filtering the geographic location of users, the language used, and the local online platforms. Extracted texts were structured into knowledge graphs and analysed descriptively.
The patient voice was identified in 133,857 messages (9,620 patients) from the Naver online platform in Korea and included internet chat forums focused on macular degeneration. The most important factors for AMD treatments were effectiveness (1,632/3,401 mentions; 48%), price and access to insurance (33%), tolerability (10%) and doctor and clinic recommendations (9%). Treatment burden associated with intravitreal injection of vascular endothelial growth factor inhibitors related to tolerability (254/942 mentions; 27%), financial burden (20%), hospital selection (18%) and emotional burden (14%). In Taiwan, 444 messages were identified from Facebook, YouTube and Instagram. The success of treatment was judged by improvements in visual acuity (20/121 mentions; 16.5%), effect on oedema (10.7%), less distortion (9.1%) and inhibition of angiogenesis (5.8%). Tolerability concerns were rarely mentioned (26/440 mentions; 5.9%).
Digital Listening using Semantic-NLP can provide real-world insights from large amounts of internet data quickly and with low human labour cost. This allows healthcare companies to respond to the unmet needs of patients for effective and safe treatment and improved patient quality of life throughout the product lifecycle.
在这个在线交流活跃的时代，患者越来越多地在数字平台上分享他们的医疗保健经历、担忧和需求。借助这些丰富的现实世界信息库，数字倾听能够通过先进技术系统地收集和分析患者的声音。语义自然语言处理人工智能能够处理和从大量非结构化在线数据中提取有意义的见解，代表了一种理解患者观点的新方法。本研究旨在证明语义自然语言处理技术在呈现韩国和台湾年龄相关性黄斑变性（AMD）患者的需求和担忧方面的实用性。
使用基于本体的信息提取系统（语义中心），在2023年1月起的三个月内收集和分析数据。该系统通过过滤用户地理位置、使用的语言和当地在线平台，识别患者“故事”并从2013年1月至2023年3月的在线帖子中提取主题，重点关注韩国和台湾地区。提取的文本被构建成知识图谱并进行描述性分析。
在韩国Naver在线平台的133,857条消息（9620名患者）中识别出患者声音，其中包括专注于黄斑变性的互联网聊天论坛。AMD治疗最重要的因素是有效性（1632/3401提及；48%）、价格和保险覆盖（33%）、耐受性（10%）以及医生和诊所推荐（9%）。玻璃体内注射血管内皮生长因子抑制剂相关的治疗负担涉及耐受性（254/942提及；27%）、经济负担（20%）、医院选择（18%）和情感负担（14%）。在台湾，从Facebook、YouTube和Instagram上识别出444条消息。治疗成功的判断依据是视力改善（20/121提及；16.5%）、对水肿的影响（10.7%）、较少变形（9.1%）和血管生成抑制（5.8%）。对耐受性的担忧很少被提及（26/440提及；5.9%）。
使用语义自然语言处理的数字倾听能够快速且以低人力成本从大量互联网数据中提供现实世界的见解。这使医疗保健公司能够在整个产品生命周期中回应患者对有效和安全治疗以及改善患者生活质量的未满足需求。
