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Harvesting the wisdom of the crowd: using online ratings to explore care experiences in regions

机译:收获群众的智慧:使用在线评分来探索地区的护理经验

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Regional population health management (PHM) initiatives need an understanding of regional patient experiences to improve their services. Websites that gather patient ratings have become common and could be a helpful tool in this effort. Therefore, this study explores whether unsolicited online ratings can provide insight into (differences in) patient’s experiences at a (regional) population level. Unsolicited online ratings from the Dutch website Zorgkaart Nederland (year?=?2008–2017) were used. Patients rated their care providers on six dimensions from 1 to 10 and these ratings were geographically aggregated based on nine PHM regions. Distributions were explored between regions. Multilevel analyses per provider category, which produced Intraclass Correlation Coefficients (ICC), were performed to determine clustering of ratings of providers located within regions. If ratings were clustered, then this would indicate that differences found between regions could be attributed to regional characteristics (e.g. demographics or regional policy). In the nine regions, 70,889 ratings covering 4100 care providers were available. Overall, average regional scores (range?=?8.3–8.6) showed significant albeit small differences. Multilevel analyses indicated little clustering between unsolicited provider ratings within regions, as the regional level ICCs were low (ICC pioneer site ?0.01). At the provider level, all ICCs were above 0.11, which showed that ratings were clustered. Unsolicited online provider-based ratings are able to discern (small) differences between regions, similar to solicited data. However, these differences could not be attributed to the regional level, making unsolicited ratings not useful for overall regional policy evaluations. At the provider level, ratings can be used by regions to identify under-performing providers within their regions.
机译:区域人口健康管理(PHM)计划需要了解区域患者的经验,以改善他们的服务。收集患者评分的网站已变得很普遍,并且可能是这项工作的有用工具。因此,本研究探讨了未经请求的在线评分是否可以洞察(地区)人群水平的患者体验(差异)。使用来自荷兰网站Zorgkaart Nederland的未经请求的在线评分(年份?=?2008-2017)。患者从1到10的6个维度对他们的护理提供者进行了评分,这些评分是根据9个PHM地区在地理上汇总的。探索了区域之间的分布。对提供者类别进行了多级分析,产生了类内相关系数(ICC),以确定位于区域内的提供者的评级聚类。如果对评级进行聚类,则表明区域之间的差异可能归因于区域特征(例如人口统计或区域政策)。在这9个地区中,可提供覆盖4100位护理人员的70,889个评分。总体而言,平均区域分数(范围?=?8.3-8.6)显示出显着差异,尽管差异很小。多级分析表明,由于区域级别的ICC较低(ICC先锋站点<0.01),区域内未经请求的提供商评分之间几乎没有聚类。在提供商级别,所有ICC均高于0.11,这表明评分是集群的。与请求的数据类似,未经请求的基于在线提供程序的评级能够辨别区域之间的(小)差异。但是,这些差异不能归因于区域级别,因此未经请求的评级对整体区域政策评估没有用处。在提供商级别,区域可以使用评分来识别其区域内表现不佳的提供商。

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