One of the key issues contributing to inefficiency in Puskesmas is the time-consuming nature of doctor-patient interactions. Doctors need to conduct thorough consultations, which include diagnosing the patient's condition, providing treatment advice, and transcribing detailed notes into medical records. In regions with diverse linguistic backgrounds, doctors often have to ask clarifying questions, further prolonging the process. While diagnosing is essential, transcription and summarization can often be automated using AI to improve time efficiency and help doctors enhance care quality and enable early diagnosis and intervention. This paper proposes a solution using a localized large language model (LLM) to transcribe, translate, and summarize doctor-patient conversations. We utilize the Whisper model for transcription and GPT-3 to summarize them into the ePuskemas medical records format. This system is implemented as an add-on to an existing web browser extension, allowing doctors to fill out patient forms while talking. By leveraging this solution for real-time transcription, translation, and summarization, doctors can improve the turnaround time for patient care while enhancing the quality of records, which become more detailed and insightful for future visits. This innovation addresses challenges like overcrowded facilities and the administrative burden on healthcare providers in Indonesia. We believe this solution will help doctors save time, provide better care, and produce more accurate medical records, representing a significant step toward modernizing healthcare and ensuring patients receive timely, high-quality care, even in resource-constrained settings.

翻译：导致Puskesmas（社区卫生中心）效率低下的关键问题之一是医患交互的耗时性。医生需要进行全面的问诊，包括诊断患者病情、提供治疗建议以及将详细记录转录到病历中。在语言背景多元的地区，医生常常需要提出澄清性问题，进一步延长了该过程。虽然诊断环节必不可少，但转录与摘要工作通常可利用人工智能实现自动化，以提升时间效率，帮助医生提高护理质量，并实现早期诊断与干预。本文提出一种基于本地化大语言模型（LLM）的解决方案，用于对医患对话进行转录、翻译与摘要生成。我们采用Whisper模型进行语音转录，并利用GPT-3将内容摘要整理为ePuskesmas病历格式。该系统以现有网页浏览器扩展插件的形式实现，使医生能够在交谈过程中同步填写患者表单。通过运用该方案进行实时转录、翻译与摘要生成，医生能够缩短患者护理的周转时间，同时提升记录质量——这些记录将更为详尽且富有洞察力，为后续诊疗提供支持。此项创新应对了印度尼西亚医疗机构过度拥挤及医护人员行政负担过重等挑战。我们相信该方案将帮助医生节省时间、提供更优质的护理服务并生成更准确的医疗记录，是迈向医疗现代化、确保患者在资源有限环境下仍能获得及时高质量护理的重要一步。