在物理治疗中应用患者报告的结果测量(PROMs):基于QUALITOUCH活动指数的评估

IF 2.1 Q1 REHABILITATION Archives of physiotherapy Pub Date : 2022-12-01 DOI:10.1186/s40945-022-00152-3
Mias Zaugg, Heiner Baur, Kai-Uwe Schmitt
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引用次数: 0

摘要

背景:患者报告结果测量(PROMs)是筛查人群、监测治疗的主观进展、实现以患者为中心的护理和评估护理质量的工具。QUALITOUCH活动指数(AI)就是这样一个工具,用于物理治疗。本研究旨在为人工智能的预期结果提供参考价值。方法:生成临床常规数据和人工智能结果的大数据集;它包括11948例患者的数据。针对慢性下背部疼痛、胫骨后症候群、膝关节骨关节炎和肩撞击四种明确的诊断,分析了人工智能对“最大疼痛水平”和“家庭活动”维度的反应。预期人工智能结果的参考走廊被导出为代表平均值、第一和第三四分位数的线性趋势线。结果:提供了预期人工智能结果的参考走廊。例如,对于慢性腰痛,走廊表明,在视觉模拟量表(VAS乘以因子10)上,与最大疼痛相关的初始平均AI值为49.3±23.8分,在四周后的第一次随访中,治疗性干预应提高到36.9±23.8分。结论:对于AI的四个典型诊断和两个维度,一个与疼痛有关,一个与日常活动限制有关,建立了预期治疗进展的参考走廊。这些参考走廊可用于将患者的个人表现与从大数据样本中获得的预期进展进行比较。基于数据的治疗成功监测可以在计划和管理治疗的不同方面提供帮助。
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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Applying patient-reported outcome measures (PROMs) in physiotherapy: an evaluation based on the QUALITOUCH Activity Index.

Background: Patient-reported outcome measures (PROMs) are tools to screen a population, to monitor the subjective progress of a therapy, to enable patient-centred care and to evaluate the quality of care. The QUALITOUCH Activity Index (AI) is such a tool, used in physiotherapy. This study aimed to provide reference values for expected AI outcomes.

Methods: A large data set uniting clinical routine data and AI outcomes was generated; it consisted of data of 11,948 patients. For four defined diagnoses, i.e. chronic lower back pain, tibia posterior syndrome, knee joint osteoarthritis and shoulder impingement, the AI responses related to the dimensions "maximum pain level" and "household activity" were analyzed. Reference corridors for expected AI outcomes were derived as linear trend lines representing the mean, 1st and 3rd quartile.

Results: Reference corridors for expected AI outcomes are provided. For chronic lower back pain, for example, the corridor indicates that the initial average AI value related to maximum pain of 49.3 ± 23.8 points on a visual analogue scale (VAS multiplied by factor 10) should be improved by a therapeutic intervention to 36.9 ± 23.8 points on a first follow-up after four weeks.

Conclusions: For four exemplary diagnoses and two dimensions of the AI, one related to pain and one related to limitations in daily activities, reference corridors of expected therapeutic progress were established. These reference corridors can be used to compare an individual performance of a patient with the expected progress derived from a large data sample. Data-based monitoring of therapeutic success can assist in different aspects of planning and managing a therapy.

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CiteScore
3.60
自引率
0.00%
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审稿时长
10 weeks
期刊最新文献
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