Department of Epidemiology, Epidemiology, Biostatistics & Prevention Institute, University of Zurich, Zurich, Switzerland
Department of Epidemiology, Epidemiology, Biostatistics & Prevention Institute, University of Zurich, Zurich, Switzerland.
BMJ Open. 2021 May 10;11(5):e044090. doi: 10.1136/bmjopen-2020-044090.
When research evidence is lacking, patient and provider preferences, expected to vary geographically, might have a stronger role in clinical decisions. We investigated whether the strength or the direction of recommendation is associated with the degree of geographic variation in utilisation.
In this cross-sectional study, we selected 24 services following a comprehensive approach. The strength and direction of recommendations were assessed in duplicate. Multilevel models were used to adjust for demographic and clinical characteristics and estimate unwarranted variation.
Observational study of claims to mandatory health insurance in Switzerland in 2014.
Enrolees eligible for the 24 healthcare services.
The variances of regional random effects, also expressed as median odds ratios (MOR). Services grouped by strength and direction of recommendations were compared with Welch's t-test.
The sizes of the eligible populations ranged from 1992 to 409 960 patients. MOR ranged between 1.13 for aspirin in secondary prevention of myocardial infarction to 1.68 for minor surgical procedures performed in inpatient instead of outpatient settings. Services with weak recommendations had a negligibly higher variance and MOR (difference in means (95% CI) 0.03 (-0.06 to 0.11) and 0.05 (-0.11 to 0.21), respectively) compared with strong recommendations. Services with negative recommendations had a slightly higher variance and MOR (difference in means (95% CI) 0.07 (-0.03 to 0.18) and 0.14 (-0.06 to 0.34), respectively) compared with positive recommendations.
In this exploratory study, the geographical variation in the utilisation of services associated with strong vs weak and negative vs positive recommendations was not substantially different, although the difference was somewhat larger for negative vs positive recommendations. The relationships between the strength or direction of recommendations and the variation may be indirect or modified by other characteristics of services. As initiatives discouraging low-value care are gaining attention worldwide, these findings may inform future research in this area.
当缺乏研究证据时，预计会因地理位置不同而有所不同的患者和提供者偏好，可能在临床决策中发挥更大的作用。我们研究了推荐的力度或方向是否与利用的地理差异程度有关。
在这项横断面研究中，我们采用全面的方法选择了 24 项服务。推荐的力度和方向进行了重复评估。使用多水平模型调整人口统计学和临床特征，并估计不必要的变异。
2014 年瑞士强制性健康保险索赔的观察性研究。
符合 24 种医疗保健服务条件的参保人。
区域随机效应的方差，也表示为中位数优势比（MOR）。根据推荐的力度和方向对服务进行分组，并与 Welch 检验进行比较。
合格人群的规模从 1992 年到 409960 人不等。MOR 范围从二级预防心肌梗死时使用阿司匹林的 1.13 到住院而非门诊进行小手术的 1.68。与强烈推荐相比，弱推荐的服务具有微不足道的更高方差和 MOR（均值差（95%CI）分别为 0.03（-0.06 至 0.11）和 0.05（-0.11 至 0.21））。与积极推荐相比，负推荐的服务具有略高的方差和 MOR（均值差（95%CI）分别为 0.07（-0.03 至 0.18）和 0.14（-0.06 至 0.34））。
在这项探索性研究中，与强烈推荐与弱推荐以及负推荐与正推荐相比，服务利用的地理差异并没有实质性的不同，尽管负推荐与正推荐相比，差异略大。推荐的力度或方向与差异之间的关系可能是间接的，或者受到服务其他特征的影响。随着全球范围内抑制低价值医疗保健的举措受到关注，这些发现可能为该领域的未来研究提供信息。
