Loren Larsen, CEO and co-founder, Videra Health

洛伦·拉森，首席执行官兼联合创始人，Videra Health

The integration of

整合

Artificial Intelligence (AI)

人工智能（AI）

in mental healthcare presents transformative opportunities to enhance patient care while raising important ethical considerations.

在心理健康护理领域，提供了提升患者护理的变革性机会，同时引发了重要的伦理考量。

As mental health providers increasingly adopt AI tools to improve their practice efficiency and patient outcomes, understanding how to implement these technologies ethically becomes crucial. The road to implementing AI can feel daunting and the options overwhelming, which is why it’s vital to partner with a company experienced in AI that is not just selling software, but an overall solution that stays with you along the AI implementation journey..

随着心理健康服务提供者越来越多地采用人工智能工具来提高执业效率和患者疗效，了解如何合乎道德地实施这些技术变得至关重要。实施人工智能的道路可能令人望而生畏，选择也可能会让人不知所措，因此与一家在人工智能领域有经验的公司合作显得尤为重要，这家公司不仅销售软件，还提供一个贯穿人工智能实施全程的整体解决方案。

The Promise of AI in Mental Healthcare

人工智能在心理健康领域的前景

AI tools are already demonstrating their value in mental healthcare settings through several practical applications. Clinical note-taking applications represent a successful early implementation, converting voice recordings to EHR-friendly text while keeping providers firmly in control of the decision-making process.

人工智能工具通过多种实际应用，已经在心理健康护理领域展示了其价值。临床笔记应用代表了一个成功的早期实施，将语音记录转换为适合电子健康记录的文本，同时让医护人员牢牢掌控决策过程。

These tools enhance efficiency without compromising the quality of care or raising significant ethical concerns..

这些工具提高了效率，而没有影响护理质量或引发重大的伦理问题。

The potential benefits of AI extend beyond administrative tasks. AI systems can help:

人工智能的潜在好处不仅限于行政任务。人工智能系统可以帮助：

• Analyze patterns in patient data to support early detection of mental health conditions

分析患者数据中的模式，以支持早期发现心理健康状况。

• Provide 24/7 support through carefully implemented chatbots and virtual assistants

• 通过精心设计的聊天机器人和虚拟助手提供全天候支持

• Generate personalized treatment recommendations based on comprehensive data analysis

• 基于全面数据分析生成个性化的治疗建议

• Improve patient engagement through interactive digital interventions

• 通过互动式数字干预提高患者参与度

• Surface population-level insights to enhance treatment strategies

• 表面人口水平的见解以改进治疗策略

Core Ethical Principles for AI Implementation

人工智能实施的核心伦理原则

To ensure responsible AI adoption, mental health providers should adhere to these fundamental ethical principles:

为了确保负责任地采用人工智能，心理健康服务提供者应遵守以下基本伦理原则：

1. Informed Consent and Patient Autonomy.

1. 知情同意与患者自主权。

Mental health providers must:

心理健康服务提供者必须：

– Clearly communicate how AI tools are used in patient care

– 清楚地传达人工智能工具在患者护理中的使用方式

– Explain the benefits and limitations of AI-assisted care

- 解释人工智能辅助护理的好处和局限性

– Obtain explicit consent for AI tool usage

– 获取使用人工智能工具的明确同意

– Provide patients the option to opt out of AI-assisted care components

- 为患者提供选择退出人工智能辅助护理组件的选项

– Regularly review and update consent as AI capabilities evolve

- 随着人工智能能力的演变，定期审查和更新同意书

2. Privacy and Data Security.

2. 隐私与数据安全。

Similar to the guidelines for HIPAA compliance, implement robust safeguards including:

类似于HIPAA合规指南，实施强有力的保护措施，包括：

– End-to-end encryption for all patient data

- 对所有患者数据进行端到端加密

– Regular security audits and updates

- 定期的安全审计和更新

– Clear data retention and deletion policies

– 明确的数据保留和删除政策

– Careful vetting of third-party AI vendors

- 对第三方AI供应商进行仔细审查

– Comprehensive staff training on data protection

- 全面的员工数据保护培训

3. Accuracy and Reliability.

3. 准确性与可靠性。

Ensure AI tool reliability through:

通过以下方式确保AI工具的可靠性：

– Regular validation of AI system outputs

定期验证人工智能系统输出结果

– Maintaining human oversight of AI-generated insights

– 维持对人工智能生成的洞察的人类监督

– Establishing clear protocols for handling AI system errors

- 建立处理人工智能系统错误的明确协议

– Documenting AI system performance metrics

记录AI系统性能指标

– Regular updates and maintenance of AI systems

– 人工智能系统的定期更新与维护

4. Equity and Fairness.

4. 公平与公正。

Address potential biases by:

通过以下方式解决潜在的偏见：

– Regularly assessing AI systems for demographic biases

定期评估人工智能系统的群体偏见

– Using diverse training data sets

– 使用多样化的训练数据集

– Monitoring treatment outcomes across different patient groups

- 监测不同患者群体的治疗结果

– Ensuring accessibility for patients with varying technical literacy

– 确保不同技术素养的患者都能获得访问权限

– Providing alternative care options when needed

- 在需要时提供替代护理方案

5. Human-Centered Care.

5. 以人为中心的护理。

Maintain the primacy of human connection by:

通过以下方式保持人类联系的首要地位：

– Using AI as a supplement to, not replacement for, human care

- 将人工智能作为人类护理的补充，而非替代

– Preserving meaningful provider-patient interactions

– 保持有意义的医患互动

– Regularly assessing the impact of AI tools on therapeutic relationships

定期评估人工智能工具对治疗关系的影响

– Adjusting AI implementation based on patient feedback

根据患者反馈调整AI实施

– Training providers in effective AI tool integration

- 培训提供者有效整合AI工具

Practical Implementation Guidelines

实施指南

Consider the following steps when implementing AI tools in a mental healthcare practice:

在心理健康实践中实施AI工具时，请考虑以下步骤：

1. Start Small

1. 从小处开始

– Begin with low-risk applications like administrative tasks

– 从低风险的应用开始，比如行政任务

– Gradually expand to more complex applications as comfort and confidence grow

– 随着舒适度和信心的提升，逐渐扩展到更复杂的应用

– Monitor and evaluate outcomes at each stage

- 监控并评估每个阶段的结果

2. Establish Clear Protocols

2. 建立明确的协议

– Develop specific guidelines for AI tool usage

– 制定AI工具使用的具体指南

– Create emergency protocols for system failures

– 为系统故障创建应急协议

– Define roles and responsibilities for AI oversight

– 定义人工智能监督的角色与职责

– Document all AI-related processes and decisions

– 记录所有与人工智能相关的流程和决策

3. Maintain Transparency

3. 保持透明度

– Keep detailed records of AI system usage

– 详细记录AI系统使用情况

– Regularly communicate updates and changes to patients

- 定期向患者传达更新和变化

– Share outcomes data with relevant stakeholders

- 与相关利益方分享结果数据

– Foster open dialogue about AI implementation

– 促进关于人工智能实施的公开对话

4. Regular Review and Assessment

4. 定期审查与评估

– Schedule periodic evaluations of AI tool effectiveness

定期评估人工智能工具的有效性

– Gather feedback from both providers and patients

- 收集来自提供者和患者的反馈

– Track ethical concerns and resolution strategies

跟踪伦理问题及其解决策略

– Update protocols based on emerging best practices

– 根据新兴的最佳实践更新协议

Moving Forward with Confidence

自信前行

Mental health providers should feel empowered to adopt AI tools while maintaining ethical standards. The key is to approach implementation thoughtfully and systematically, always prioritizing patient well-being and ethical considerations. Start with clear guidelines, maintain strong oversight, and regularly assess outcomes..

心理健康服务提供者应在保持道德标准的同时，积极采用人工智能工具。关键在于深思熟虑且系统化地进行实施，始终将患者福祉和道德考量放在首位。从明确的指导原则开始，保持强有力的监督，并定期评估结果。

By following these ethical principles and implementation guidelines, providers can confidently leverage AI to enhance their practice while ensuring patient safety and care quality. The future of mental healthcare lies in the ethical integration of AI tools that support and augment, rather than replacing, human care providers..

通过遵循这些道德原则和实施指南，提供者可以自信地利用人工智能来增强他们的实践，同时确保患者的安全和护理质量。心理健康护理的未来在于道德整合人工智能工具，这些工具支持和增强而不是取代人类护理提供者。

Remember that ethical AI implementation is an ongoing process requiring regular review and adjustment. This can be challenging if you are doing it all yourself or trying to piece together a number of point solutions from multiple vendors. EHR vendors have typically not delivered high levels of service for customers.

请记住，道德人工智能的实施是一个持续的过程，需要定期审查和调整。如果你是自己一个人在做，或者试图从多个供应商那里拼凑出许多点式解决方案，这可能会很有挑战性。电子健康记录（EHR）供应商通常未能为客户提供高水平的服务。

Finding the right implementation partner is key to staying informed about evolving best practices and ensuring you are getting the best value..

找到合适的实施合作伙伴是了解不断发展的最佳实践并确保您获得最大价值的关键。

Loren Larsen

洛伦·拉森

is the CEO and co-founder of Videra Health, the leading AI-driven mental health assessment platform, and is a pioneer in leveraging video and artificial intelligence to assess and measure mental health.

是Videra Health的首席执行官兼联合创始人，该公司是领先的AI驱动的心理健康评估平台，并且是利用视频和人工智能评估和测量心理健康的先驱。