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基于人工智能和移动医疗工具的以患者为中心的疼痛管理:一项随机对照有效性试验。

Patient-Centered Pain Care Using Artificial Intelligence and Mobile Health Tools: A Randomized Comparative Effectiveness Trial.

机构信息

Ann Arbor Department of Veterans Affairs (VA) Center for Clinical Management Research, Ann Arbor, Michigan.

School of Public Health, University of Michigan, Ann Arbor.

出版信息

JAMA Intern Med. 2022 Sep 1;182(9):975-983. doi: 10.1001/jamainternmed.2022.3178.

Abstract

IMPORTANCE

Cognitive behavioral therapy for chronic pain (CBT-CP) is a safe and effective alternative to opioid analgesics. Because CBT-CP requires multiple sessions and therapists are scarce, many patients have limited access or fail to complete treatment.

OBJECTIVES

To determine if a CBT-CP program that personalizes patient treatment using reinforcement learning, a field of artificial intelligence (AI), and interactive voice response (IVR) calls is noninferior to standard telephone CBT-CP and saves therapist time.

DESIGN, SETTING, AND PARTICIPANTS: This was a randomized noninferiority, comparative effectiveness trial including 278 patients with chronic back pain from the Department of Veterans Affairs health system (recruitment and data collection from July 11, 2017-April 9, 2020). More patients were randomized to the AI-CBT-CP group than to the control (1.4:1) to maximize the system's ability to learn from patient interactions.

INTERVENTIONS

All patients received 10 weeks of CBT-CP. For the AI-CBT-CP group, patient feedback via daily IVR calls was used by the AI engine to make weekly recommendations for either a 45-minute or 15-minute therapist-delivered telephone session or an individualized IVR-delivered therapist message. Patients in the comparison group were offered 10 therapist-delivered telephone CBT-CP sessions (45 minutes/session).

MAIN OUTCOMES AND MEASURES

The primary outcome was the Roland Morris Disability Questionnaire (RMDQ; range 0-24), measured at 3 months (primary end point) and 6 months. Secondary outcomes included pain intensity and pain interference. Consensus guidelines were used to identify clinically meaningful improvements for responder analyses (eg, a 30% improvement in RMDQ scores and pain intensity). Data analyses were performed from April 2021 to May 2022.

RESULTS

The study population included 278 patients (mean [SD] age, 63.9 [12.2] years; 248 [89.2%] men; 225 [81.8%] White individuals). The 3-month mean RMDQ score difference between AI-CBT-CP and standard CBT-CP was -0.72 points (95% CI, -2.06 to 0.62) and the 6-month difference was -1.24 (95% CI, -2.48 to 0); noninferiority criterion were met at both the 3- and 6-month end points (P < .001 for both). A greater proportion of patients receiving AI-CBT-CP had clinically meaningful improvements at 6 months as indicated by RMDQ (37% vs 19%; P = .01) and pain intensity scores (29% vs 17%; P = .03). There were no significant differences in secondary outcomes. Pain therapy using AI-CBT-CP required less than half of the therapist time as standard CBT-CP.

CONCLUSIONS AND RELEVANCE

The findings of this randomized comparative effectiveness trial indicated that AI-CBT-CP was noninferior to therapist-delivered telephone CBT-CP and required substantially less therapist time. Interventions like AI-CBT-CP could allow many more patients to be served effectively by CBT-CP programs using the same number of therapists.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02464449.

摘要

重要性

慢性疼痛的认知行为疗法(CBT-CP)是阿片类镇痛药的安全有效替代方法。由于 CBT-CP 需要多次治疗且治疗师稀缺,许多患者的治疗机会有限或无法完成治疗。

目的

确定使用强化学习、人工智能(AI)和交互式语音应答(IVR)呼叫为每位患者个性化治疗的 CBT-CP 计划是否不劣于标准电话 CBT-CP 并节省治疗师的时间。

设计、地点和参与者:这是一项随机非劣效性、比较有效性试验,纳入了来自退伍军人事务部医疗系统的 278 名慢性背痛患者(招募和数据收集时间为 2017 年 7 月 11 日至 2020 年 4 月 9 日)。为了最大限度地提高系统从患者交互中学习的能力,向 AI-CBT-CP 组随机分配的患者多于对照组(1.4:1)。

干预措施

所有患者均接受 10 周的 CBT-CP。对于 AI-CBT-CP 组,患者通过每日 IVR 电话提供的反馈信息由 AI 引擎使用,每周为 45 分钟或 15 分钟的治疗师提供电话会议或个性化的 IVR 传递治疗师消息进行建议。对照组的患者提供 10 次治疗师提供的电话 CBT-CP 治疗(45 分钟/次)。

主要结果和措施

主要结局是 3 个月(主要终点)和 6 个月时的 Roland Morris 残疾问卷(RMDQ;范围 0-24)。次要结局包括疼痛强度和疼痛干扰。采用共识指南来确定应答分析的临床有意义的改善(例如,RMDQ 评分和疼痛强度提高 30%)。数据分析于 2021 年 4 月至 2022 年 5 月进行。

结果

研究人群包括 278 名患者(平均[标准差]年龄,63.9[12.2]岁;248[89.2%]名男性;225[81.8%]名白人个体)。AI-CBT-CP 与标准 CBT-CP 在 3 个月时的平均 RMDQ 评分差异为-0.72 分(95% CI,-2.06 至 0.62),6 个月时的差异为-1.24 分(95% CI,-2.48 至 0);在 3 个月和 6 个月的终点均达到非劣效性标准(P<0.001)。6 个月时,接受 AI-CBT-CP 的患者中有更大比例的患者的 RMDQ(37%比 19%;P=0.01)和疼痛强度评分(29%比 17%;P=0.03)有临床意义的改善。次要结局无显著差异。使用 AI-CBT-CP 的疼痛治疗所需的治疗师时间不到标准 CBT-CP 的一半。

结论和相关性

这项随机比较有效性试验的结果表明,AI-CBT-CP 不劣于治疗师提供的电话 CBT-CP,并且需要的治疗师时间大大减少。像 AI-CBT-CP 这样的干预措施可以使更多的患者在使用相同数量的治疗师的情况下有效地接受 CBT-CP 计划。

试验注册

ClinicalTrials.gov 标识符:NCT02464449。

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