AI × Healthcare: A New Chapter – Humanity's Future Health Partner

Bruno Huang 黃鼎翰 / 老黑
6月9日
讀畢需時 7 分鐘

AI × 醫療新篇章：人類健康的未來夥伴

Artificial Intelligence (AI) is rapidly transforming our perception of healthcare. No longer just cold algorithms, AI has quietly entered examination rooms, operating theaters, remote consultations, and long-term care facilities, becoming a vital pillar of the medical system. In disease prediction, diagnosis, treatment, and care, AI not only boosts efficiency but also ushers in a vision of more precise and accessible healthcare.

人工智慧（AI）正在迅速改變我們對醫療的想像。不再只是冷冰冰的演算法運算，AI 已悄然進入診間、手術房、遠距看診與長照機構，成為醫療體系的重要支柱。在疾病預測、診斷、治療與照護的過程中，AI 不僅提升效率，也開啟了更精準、更普及的健康願景。

How AI is Reshaping Disease Prevention and Treatment

Predicting and Preventing Disease Risk: AI can analyze vast amounts of health insurance data, genetic information, and lifestyle habits to predict an individual's risk of developing conditions like diabetes, heart disease, and cancer, effectively ushering in a "preventive medicine" model.
Precision Medicine and Personalized Treatment: Based on a patient's genotype, medication history, and lifestyle, AI can assist physicians in providing the most suitable treatment recommendations, enhancing efficacy and reducing side effects.
AI-Assisted Diagnosis and Image Interpretation: AI is already widely used for automated interpretation of X-rays, MRIs, and pathological slides, reducing physicians' workloads and improving diagnostic accuracy.
Health Monitoring and Long-term Care Applications: Combined with wearable devices, AI analysis can instantly detect abnormal physiological indexes and proactively issue alerts, which is especially crucial for chronic disease patients and the elderly.

AI如何重塑疾病防治與治療？

預測與預防疾病風險：AI可分析大量健保資料、基因數據與生活習慣，預測個人罹患糖尿病、心臟病、癌症等風險，有效導入「預防醫學」模式。
精準醫療與個人化治療：根據病患的基因型、用藥史與生活習慣，AI能協助醫師提供最適合的治療建議，提升療效並降低副作用。
AI輔助診斷與影像判讀：AI已廣泛應用於X光、MRI與病理切片的自動判讀，減少醫師工作量並提升診斷準確率。
健康監測與長照應用：結合穿戴裝置與AI分析，能即時偵測異常生理指數，主動發出警訊，對慢性病患者與高齡族群尤為重要。

Taiwan's Healthcare Workforce Shortage and AI's Potential

As Taiwan enters a super-aged society, healthcare demand continues to rise, yet the country faces a severe workforce shortage. According to 2024 Ministry of Health and Welfare statistics, there's a nationwide deficit of 12,000 nursing staff, with emergency rooms, intensive care units, and internal medicine departments being particularly affected. Furthermore, one-third of licensed nurses are not actively practicing, highlighting the dual challenge of pressure on the healthcare frontlines and workforce attrition.

台灣醫療人力短缺現況與AI的應用潛力

隨著台灣進入超高齡社會，醫療需求不斷攀升，卻面臨人力嚴重短缺問題。根據2024年衛福部統計，全台護理人員缺口達12,000人，急診、加護病房與內科領域尤為嚴重。更有三分之一持照護理人員未實際執業，顯示醫療現場壓力與人力流失的雙重挑戰。

這些壓力導致急診壅塞、病床閒置與醫護過勞等現象，已直接影響到全民健康保障的品質與效率。

These pressures lead to emergency room overcrowding, idle hospital beds, and overworked medical professionals, directly impacting the quality and efficiency of national health protection.

Against this backdrop, AI offers several concrete solutions:

Automated Medical Records and Administrative Systems: AI can help process medical record documentation, medication recommendations, and examination scheduling, saving medical staff significant time.
AI Medical Assistants and Robots: For example, Hon Hai (Foxconn) and NVIDIA's collaborative nursing robot, "Nurabot," is being piloted in several Taiwanese hospitals, reducing workloads by over 30% on average.
Smart Diagnosis Platforms: An example is Kaohsiung Medical University Hospital's "KMU Genie" platform, which integrates internal hospital data systems to assist clinical decision-making, improving diagnostic quality and efficiency.
Chi Mei Hospital's AI Copilot System: In collaboration with Microsoft, physicians can quickly generate medical reports, and nurses can significantly shorten handover times. Initial results show a noticeable reduction in stress.
Mackay Memorial Hospital and Ubitus's AI Medical Robot: Applied to patient care and medical logistics, enhancing overall operational efficiency.

在這樣的背景下，AI提供了數項具體的解方：

自動化病歷與行政系統：AI能協助處理病歷書寫、藥物建議與檢查排程，節省醫護人員大量時間。
AI醫療助理與機器人：如鴻海與NVIDIA合作的護理機器人「Nurabot」，已在台灣多家醫院試行，平均減少30%以上的工作負擔。
智慧診斷平台：例如高醫導入的「KMU Genie」平台，整合院內資料系統，輔助臨床決策，提高診療品質與效率。
奇美醫院導入AI Copilot系統：與微軟合作，醫師可快速生成病歷報告、護理人員能有效縮短交班時間，初步成效顯示壓力明顯下降。
馬偕醫院與Ubitus展示AI醫療機器人：應用於病患照護與醫療物流，提升整體作業效率。

AI Promotes Telemedicine and Health Equity

The post-pandemic era has accelerated the adoption of telemedicine. The integration of AI with 5G and IoT technologies has further transformed remote consultations from simple video calls into comprehensive smart healthcare solutions.

Reduced Transportation and Waiting Costs: Especially for individuals in remote areas, the elderly, and those with mobility issues, AI telemedicine can save travel time and lengthy waiting periods.
Chronic Disease and Post-operative Monitoring: Wearable devices collect real-time data, and AI analyzes abnormal trends, alerting medical staff to intervene, thereby increasing the speed of care response.
Improved Resource Accessibility: Allows remote or medically underserved areas to connect instantly with specialists from large hospitals, achieving medical fairness and accessibility.

AI促進遠距醫療與健康平權

後疫情時代加速了遠距醫療的普及，而AI與5G、IoT技術的結合，更讓遠距看診從簡單的視訊對話，邁向全流程的智慧醫療解決方案。

減少交通與等待成本：特別對偏鄉、高齡與行動不便者，AI遠距醫療可省去舟車勞頓與冗長候診時間。
慢性病與術後監控：穿戴式裝置蒐集即時資料，AI分析異常趨勢並提醒醫療人員介入，提升照護反應速度。
提升資源可近性：讓偏鄉或醫療資源不足地區，得以即時連線大醫院專科醫師，實現醫療公平與普及。

International Examples: How AI is Changing the Global Healthcare Landscape

Hinge Health (USA): Utilizes AI for remote physical therapy and motion tracking, significantly boosting physical therapy efficiency and reducing clinical pressure.
Qure.ai (India): Developed AI diagnostic tools for early detection of lung X-rays and diseases like tuberculosis and stroke, having served over 15 million people globally.
NHS Digital Medical Records System Project (UK): Promotes a unified electronic health record platform to establish patient passports, enhancing medical efficiency and patient safety.

國際實例：AI如何改變全球醫療景觀

美國 Hinge Health：利用AI進行遠距物理治療與動作追蹤，大幅提升物理治療效率，降低臨床壓力。
印度 Qure.ai：開發AI診斷工具，用於肺部X光與結核病、中風等疾病的早期檢測，全球已服務超過1,500萬人。
英國 NHS 數位病歷系統計畫：推動統一電子病歷平台，建立病患護照，提升醫療效率與病患安全。

Challenges of Integrating AI with Taiwan's National Health Insurance

Taiwan's National Health Insurance (NHI) system is a global benchmark, but its high coverage and utilization rates also lead to significant financial and human resource pressures. If AI can improve healthcare efficiency, reduce misdiagnoses, and cut unnecessary expenses, it is expected to alleviate the NHI's financial burden.

健保制度與AI的整合挑戰

台灣全民健保制度是全球標竿，但也因高覆蓋與高使用率而面臨沉重的財政與人力壓力。AI若能提升醫療效率、降低誤診與不必要支出，將有望紓解健保財政負擔。

However, for AI to truly integrate into the NHI and clinical settings, several key challenges must be addressed:

Data Privacy and Cybersecurity Protection: AI training relies on vast amounts of personal data. Opening data while protecting patient privacy is a top priority.
Technological Bias and Fairness Issues: Ensuring AI algorithms do not create diagnostic biases against certain groups due to unbalanced data sources.
Establishing Regulatory and Ethical Frameworks: This includes defining AI medical liability, clinical application review, and reforming the NHI payment system, all of which require collaborative efforts from the government and industry.

然而，要讓AI真正融入健保與臨床現場，仍需面對幾項關鍵挑戰：

資料隱私與資安保障：AI訓練仰賴大量個資，如何在保護病患隱私的前提下開放數據，是首要任務。
技術偏誤與公平性問題：確保AI演算法不因數據來源失衡而對某些族群產生診斷偏誤。
法規與倫理框架的建立：包括AI醫療責任歸屬、臨床應用審查與健保支付制度的改革，都需政府與產業共同推動。

AI: Not a Replacement, But a Reinforcement of Healthcare Partnerships

AI will not and should not replace physicians and nurses. Instead, it complements the deficiencies of the current healthcare system, allowing medical professionals to focus more on high-risk and high-value care tasks. For Taiwan, AI is not just a result of technological innovation; it may be the key to sustaining universal health and the long-term viability of the NHI.

In the future, what we need is not just the adoption of technology but also institutional and cultural transformation. Striking a balance between technological advancement and human-centered healthcare will be a core issue for the next generation of healthcare.

AI不是取代，而是強化醫療夥伴關係

AI不會也不應取代醫師與護理人員，而是補足現行醫療體系的不足，讓醫護能更專注於高風險與高價值的照護任務。對台灣而言，AI不僅是科技創新的成果，更可能是維繫全民健康與健保永續的關鍵力量。

未來，我們需要的不只是技術的導入，更是制度與文化的轉型。如何在科技進步與人本醫療之間取得平衡，將是下一個世代醫療的核心課題。

原文 (英文) : Bruno Huang

翻譯 (中文) : Bruno Huang