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市场调查报告书
商品编码
1803052
全球人工智慧驱动的慢性疼痛管理市场预测(至 2032 年):按组件、部署类型、分销管道、应用、最终用户和地区进行分析AI Chronic Pain Management Market Forecasts to 2032 - Global Analysis By Component (Software, Hardware, and Services), Deployment Mode, Distribution Channel, Application, End User and By Geography |
根据 Stratistics MRC 的数据,全球 AI 慢性疼痛管理市场预计在 2025 年达到 60.7 亿美元,到 2032 年将达到 207.8 亿美元,预测期内的复合年增长率为 19.2%。
AI慢性疼痛管理是指应用人工智慧技术来评估、监测和治疗长期疼痛状况。它整合了机器学习、预测分析和数位工具,以个人化疼痛管理策略,提高诊断准确性并优化治疗效果。透过分析患者数据、穿戴式装置输入和病历,AI可以实现早期疗育,减少阿片类药物依赖,并改善慢性疼痛患者的整体生活品质。
慢性疼痛的流行
全球慢性疼痛的增加推动了对创新疼痛管理解决方案的需求。由于人口老化和生活方式因素,关节炎、纤维肌痛和神经病变疼痛等疾病正变得越来越普遍。传统的疼痛管理方法往往无法提供长期缓解,这激发了人们对人工智慧方法的兴趣。人工智慧技术能够更精确地分析患者数据并优化治疗方案。随着医疗保健系统寻求更有效、更具可扩展性的解决方案,人工智慧正逐渐成为个人化疼痛照护的关键推动因素。这种日益增长的需求正在推动医院、诊所和数位健康平台的投资和应用。
来自医疗保健专业人士的抵制
对数据可靠性、临床检验以及缺乏人工监督的担忧阻碍了人工智慧的推广应用。医生可能不愿意相信演算法推荐,而更倾向于相信自己的临床判断,尤其是在复杂的疼痛病例中。有限的培训和人工智慧工具的机会进一步加剧了医学界的阻力。此外,监管的不确定性和伦理方面的考虑也导致人们对采用基于人工智慧的干预措施犹豫不决。这种阻力减缓了市场渗透,并限制了人工智慧在疼痛治疗领域中变革的潜力。
个人化预测护理
预测演算法可以透过预测疼痛发作并建议预防性干预措施来改善患者的治疗效果。这些功能支持主动护理模式,减少对被动且通常无效的治疗的依赖。与穿戴式装置和行动应用程式的整合增强了即时监控和回馈迴路。随着精准医疗的日益普及,人工智慧驱动的疼痛管理与个人化医疗的整体医疗趋势相契合。这一机会正吸引新兴企业、科技巨头和差异化医疗服务提供者。
预测不准确和病人受伤的风险
疼痛管理中的人工智慧系统容易受到资料集偏差或不完整导致的误差的影响。误诊和不恰当的治疗建议可能会对患者造成伤害,并削弱人们对该技术的信任。过度依赖缺乏适当临床监督的演算法可能会加剧风险,尤其是在复杂或非典型病例中。预测模型中的错误可能导致治疗延误并使患者病情恶化。监管审查正在加强,以确保人工智慧应用的安全性和课责。这些风险对市场信誉和长期应用构成了重大威胁。
COVID-19的影响
新冠疫情加速了数位医疗工具(包括基于人工智慧的疼痛管理平台)的普及。封锁措施和麵对面诊疗服务受限,增加了对远端监控和虚拟咨询的需求。人工智慧工具透过实现症状追踪和居家治疗协调,填补了慢性疼痛护理领域的空白。然而,供应链中断和资本重新配置暂时减缓了新型人工智慧解决方案的开发和部署。这种转变将继续支持人工智慧主导的慢性疼痛管理解决方案的成长。
预计软体领域将成为预测期内最大的领域
由于个人化治疗工具、用于疼痛预测的先进机器学习以及云端远距远端医疗解决方案的日益普及,预计软体领域将在预测期内占据最大的市场占有率。值得关注的趋势包括基于应用程式的疼痛监测、与穿戴式装置的整合以及基于订阅的人工智慧平台。近期的进展体现在科技公司与医疗保健提供者之间的合作,旨在建立可互通的系统,以支援与电子健康记录的一致性、简化临床决策流程以及以患者为中心、以结果主导的护理模式。
预计居家医疗领域在预测期内将以最高复合年增长率成长
预计居家医疗领域将在预测期内实现最高增长率,这得益于人们对物联网设备、可穿戴感测器和基于人工智慧的监控系统等技术支援的远端个人化护理的兴趣日益浓厚。主要趋势包括虚拟疼痛管理、即时数据驱动的自适应护理以及用于早期症状检测的预测工具。近期的创新促使技术提供者和医疗保健机构建立策略合作伙伴关係,提供扩充性的云端支援平台,以增强患者能力,减少对医院的依赖,并与不断发展的报销和基于价值的护理模式保持一致。
由于慢性疼痛患者数量的增加、数位医疗系统的扩展以及向非阿片类药物治疗的转变,预计亚太地区将在预测期内占据最大的市场占有率。人工智慧整合行动平台、穿戴式健康追踪器和云端基础的分析等技术正日益普及。主要趋势包括虚拟疼痛支援、多语言人工智慧工具和远端医疗整合。近期发展包括区域高科技医疗伙伴关係、政府主导的数位医疗项目,以及对可扩展人工智慧解决方案的投资增加,以满足多样化的患者需求。
由于慢性疼痛患者人数众多、医疗保健体系健全以及数位化治疗解决方案的广泛应用,北美预计将在预测期内呈现最高的复合年增长率。人工智慧诊断工具、穿戴式疼痛监测设备以及与电子健康记录相连的云端整合平台等技术是关键推动因素。新兴趋势包括个人化疼痛管理演算法、神经调节洞察和虚拟指导。近期的里程碑包括医院采用人工智慧工具的激增、生技药品研究资金的增加以及基于远端医疗的疼痛护理服务的扩展。
According to Stratistics MRC, the Global AI Chronic Pain Management Market is accounted for $6.07 billion in 2025 and is expected to reach $20.78 billion by 2032 growing at a CAGR of 19.2% during the forecast period. AI Chronic Pain Management refers to the application of artificial intelligence technologies to assess, monitor, and treat long-term pain conditions. It integrates machine learning, predictive analytics, and digital tools to personalize pain management strategies, improve diagnosis accuracy, and optimize treatment outcomes. By analyzing patient data, wearable device inputs, and medical histories, AI enables early intervention, reduces dependency on opioids, and enhances overall quality of life for individuals suffering from chronic pain.
Growing prevalence of chronic pain
The increasing global burden of chronic pain is driving demand for innovative management solutions. Conditions such as arthritis, fibromyalgia, and neuropathic pain are becoming more prevalent due to aging populations and lifestyle factors. Traditional pain management methods often fall short in providing long-term relief, prompting interest in AI-driven approaches. AI technologies offer the potential to analyse patient data and optimize treatment plans with greater precision. As healthcare systems seek more effective and scalable solutions, AI is emerging as a key enabler of personalized pain care. This growing need is catalysing investments and adoption across hospitals, clinics, and digital health platforms.
Resistance from healthcare professionals
Concerns around data reliability, clinical validation, and loss of human oversight hinder adoption. Physicians may be reluctant to trust algorithmic recommendations over their clinical judgment, especially in complex pain cases. Limited training and exposure to AI tools further exacerbate resistance within the medical community. Additionally, regulatory ambiguity and ethical considerations contribute to hesitation in deploying AI-based interventions. This resistance slows market penetration and limits the full potential of AI in transforming pain care.
Personalized and predictive treatment
Predictive algorithms can forecast pain flare-ups and recommend pre-emptive interventions, improving patient outcomes. These capabilities support proactive care models, reducing reliance on reactive and often ineffective treatments. Integration with wearable devices and mobile apps enhances real-time monitoring and feedback loops. As precision medicine gains traction, AI-driven pain management aligns with broader healthcare trends toward individualized care. This opportunity is attracting start-ups, tech giants, and healthcare providers seeking to differentiate their offerings.
Risk of inaccurate predictions and patient harm
AI systems in pain management are vulnerable to inaccuracies stemming from biased or incomplete datasets. Misdiagnosis or inappropriate treatment recommendations can lead to patient harm, undermining trust in the technology. Overreliance on algorithms without adequate clinical oversight may exacerbate risks, especially in complex or atypical cases. Errors in prediction models can result in delayed care, worsening patient conditions. Regulatory scrutiny is intensifying to ensure safety and accountability in AI applications. These risks pose a significant threat to market credibility and long-term adoption.
Covid-19 Impact
The COVID-19 pandemic accelerated the adoption of digital health tools, including AI-based pain management platforms. Lockdowns and limited access to in-person care drove demand for remote monitoring and virtual consultations. AI tools helped bridge gaps in chronic pain care by enabling symptom tracking and treatment adjustments from home. However, supply chain disruptions and funding reallocations temporarily slowed development and deployment of new AI solutions. This shift continues to support growth in AI-driven chronic pain management solutions.
The softwaresegment is expected to be the largest during the forecast period
The softwaresegment is expected to account for the largest market share during the forecast period, fuelled by increasing adoption of personalized treatment tools, advanced machine learning for pain prediction, and cloud-enabled remote care solutions. Notable trends include app-based pain monitoring, integration with wearable devices, and subscription-based AI platforms. Recent advancements feature collaborations between tech companies and healthcare providers to create interoperable systems that align with electronic health records, streamline clinical decision-making, and support patient-centric, outcome-driven care models.
The homecaresegment is expected to have the highest CAGR during the forecast period
Over the forecast period, the homecaresegment is predicted to witness the highest growth rate, driven by growing interest in remote, individualized care supported by technologies like IoT-enabled devices, wearable sensors, and AI-based monitoring systems. Key trends include virtual pain management, real-time data-driven adaptive care, and predictive tools for early symptom detection. Recent innovations involve strategic alliances between technology providers and healthcare organizations to deliver scalable, cloud-supported platforms that empower patients, lower hospital dependency, and align with evolving reimbursement and value-based care models.
During the forecast period, the Asia Pacific region is expected to hold the largest market sharedue to increasing cases of chronic pain, expanding digital healthcare systems, and a shift toward non-opioid treatment options. Technologies such as AI-integrated mobile platforms, wearable health trackers, and cloud-based analytics are gaining traction. Key trends include virtual pain support, multilingual AI tools, and telemedicine integration. Recent progress includes regional tech-healthcare partnerships, government-led digital health programs, and rising investments in scalable AI solutions tailored to diverse patient needs.
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, owing to widespread chronic pain cases, robust healthcare systems, and strong uptake of digital treatment solutions. Technologies such as AI-driven diagnostic tools, wearable pain monitoring devices, and cloud-integrated platforms linked to electronic health records are key enablers. Emerging trends include personalized pain management algorithms, neuromodulation insights, and virtual coaching. Recent milestones include a surge in hospital adoption of AI tools, increased funding for biologics research, and expanded telehealth-based pain care services.
Key players in the market
Some of the key players profiled in the AI Chronic Pain Management Market includeJohnson & Johnson, Horizon Therapeutics, Pfizer, Amgen, Medtronic, Mallinckrodt, Teva Pharmaceuticals, AstraZeneca, AbbVie, Bristol-Myers Squibb, Eli Lilly, Regeneron Pharmaceuticals, BoehringerIngelheim, Novartis, and GlaxoSmithKline (GSK).
In July2025, Johnson & Johnson announced the launch of the VIRTUGUIDE(TM) System. This AI-powered, patient-matched solution is designed to support Lapidus procedures2, a type of bunion surgery that helps realign the foot by joining two bones near the arch (the first metatarsal bone and the medial cuneiform).3 The system uses pre-operative planning software, developed in collaboration with PeekMed(R), to assess each patient's bunion and make personalized recommendations for the intended correction.
In October2023,Amgen announced that it has completed its acquisition of Horizon Therapeutics plc for $116.50 per share in cash, representing a transaction equity value of approximately $27.8 billion.