Utilizing a learning health system to capture real-world patient data: Application of the reliable change index to evaluate and improve the outcome of a pain rehabilitation program.

IF 2.5 3区 医学 Q2 ANESTHESIOLOGY Pain Practice Pub Date : 2024-07-01 Epub Date: 2024-03-11 DOI:10.1111/papr.13364
Dokyoung S You, Jeanette L Chong, Sean C Mackey, Heather Poupore-King
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Abstract

Background and objectives: The learning healthcare system (LHS) has been developed to integrate patients' clinical data into clinical decisions and improve treatment outcomes. Having little guidance on this integration process, we aim to explain (a) an applicable analytic tool for clinicians to evaluate the clinical outcomes at a group and an individual level and (b) our quality improvement (QI) project, analyzing the outcomes of a new outpatient pain rehabilitation program ("Back-in-Action": BIA) and applying the analysis results to modify our clinical practice.

Methods: Through our LHS (CHOIR; https://choir.stanford.edu), we administered the Pain Catastrophizing Scale (PCS), Chronic Pain Acceptance Questionnaire (CPAQ), and Patient-Reported Outcomes Measures (PROMIS)® before and after BIA. After searching for appropriate analytic tools, we decided to use the Reliable Change Index (RCI) to determine if an observed change in the direction of better (improvement) or worse (deterioration) would be beyond or within the measurement error (no change).

Results: Our RCI calculations revealed that at least a 9-point decrease in the PCS scores and 10-point increase in the CPAQ scores would indicate reliable improvement. RCIs for the PROMIS measures ranged from 5 to 8 T-score points (i.e., 0.5-0.8 SD). When evaluating change scores of the PCS, CPAQ, and PROMIS measures, we found that 94% of patients showed improvement in at least one domain after BIA and 6% showed no reliable improvement.

Conclusions: Our QI project revealed RCI as a useful tool to evaluate treatment outcomes at a group and an individual level, and RCI could be incorporated into the LHS to generate a progress report automatically for clinicians. We further explained how clinicians could use RCI results to modify a clinical practice, to improve the outcomes of a pain program, and to develop individualized care plans. Lastly, we suggested future research areas to improve the LHS application in pain practice.

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利用学习型医疗系统获取真实世界的患者数据:应用可靠的变化指数来评估和改善疼痛康复计划的成果。
背景和目标:学习型医疗保健系统(LHS)的开发旨在将患者的临床数据整合到临床决策中并改善治疗效果。由于在这一整合过程中缺乏指导,我们旨在解释:(a)临床医生评估团体和个人临床结果的适用分析工具;(b)我们的质量改进(QI)项目,分析新的门诊疼痛康复项目("Back-in-Action":BIA)的结果,并将分析结果用于修改我们的临床实践:通过我们的 LHS (CHOIR; https://choir.stanford.edu),我们在 BIA 之前和之后使用了疼痛灾难化量表 (PCS)、慢性疼痛接受度问卷 (CPAQ) 和患者报告结果量表 (PROMIS)®。在寻找到合适的分析工具后,我们决定使用可靠变化指数(RCI)来确定观察到的变化方向是更好(改善)还是更差(恶化),是超出还是在测量误差(无变化)范围之内:我们的 RCI 计算结果表明,PCS 分数至少下降 9 分,CPAQ 分数至少上升 10 分,就表明病情有了可靠的改善。PROMIS 测量的 RCI 在 5 到 8 个 T 分数点之间(即 0.5-0.8 SD)。在评估 PCS、CPAQ 和 PROMIS 测量的变化分数时,我们发现 94% 的患者在 BIA 后至少在一个领域有所改善,6% 的患者没有可靠的改善:我们的 QI 项目揭示了 RCI 是评估团体和个体治疗效果的有用工具,而且 RCI 可纳入 LHS,为临床医生自动生成进展报告。我们进一步解释了临床医生如何利用 RCI 结果来修改临床实践、改善疼痛项目的效果以及制定个性化护理计划。最后,我们提出了未来的研究领域,以改进 LHS 在疼痛实践中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Pain Practice
Pain Practice ANESTHESIOLOGY-CLINICAL NEUROLOGY
CiteScore
5.60
自引率
3.80%
发文量
92
审稿时长
6-12 weeks
期刊介绍: Pain Practice, the official journal of the World Institute of Pain, publishes international multidisciplinary articles on pain and analgesia that provide its readership with up-to-date research, evaluation methods, and techniques for pain management. Special sections including the Consultant’s Corner, Images in Pain Practice, Case Studies from Mayo, Tutorials, and the Evidence-Based Medicine combine to give pain researchers, pain clinicians and pain fellows in training a systematic approach to continuing education in pain medicine. Prior to publication, all articles and reviews undergo peer review by at least two experts in the field.
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