Zaugg Mias, Baur Heiner, Schmitt Kai-Uwe
Dept. of Health Professions, Bern University of Applied Sciences (BFH), Academic-Practice-Partnership Between Insel Gruppe and BFH, Murtenstr. 10, 3008, Bern, Switzerland.
Dept. Health Sciences and Technology, Institute for Human Movement Science and Sport, ETH Zurich, Rämistr. 101, 8001, Zurich, Switzerland.
Arch Physiother. 2022 Dec 1;12(1):27. doi: 10.1186/s40945-022-00152-3.
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.
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.
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.
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.
患者报告结局测量（PROMs）是用于筛查人群、监测治疗主观进展、实现以患者为中心的护理以及评估护理质量的工具。QUALITOUCH活动指数（AI）就是这样一种用于物理治疗的工具。本研究旨在提供AI预期结果的参考值。
生成了一个整合临床常规数据和AI结果的大数据集；它包含11948名患者的数据。对于四种明确的诊断，即慢性下背痛、胫后综合征、膝关节骨关节炎和肩部撞击症，分析了与“最大疼痛程度”和“家庭活动”维度相关的AI反应。预期AI结果的参考区间通过代表均值、第1和第3四分位数的线性趋势线得出。
提供了预期AI结果的参考区间。例如，对于慢性下背痛，该区间表明，与视觉模拟量表（VAS乘以系数10）上最大疼痛相关的初始平均AI值49.3±23.8分，应通过治疗干预在四周后的首次随访时改善至36.9±23.8分。
对于四种示例性诊断以及AI的两个维度，一个与疼痛相关，一个与日常活动受限相关，建立了预期治疗进展的参考区间。这些参考区间可用于将患者的个体表现与来自大数据样本的预期进展进行比较。基于数据的治疗成功监测可在治疗规划和管理的不同方面提供帮助。
