five

Determinants coded to the process domain.

收藏
NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://figshare.com/articles/dataset/Determinants_coded_to_the_process_domain_/22742410
下载链接
链接失效反馈
官方服务:
资源简介:
Background The delivery of high quality care is a fundamental goal for health systems worldwide. One policy tool to ensure quality is the regulation of services by an independent public authority. This systematic review seeks to identify determinants of compliance with such regulation in health and social care services. Methods Searches were carried out on five electronic databases and grey literature sources. Quantitative, qualitative and mixed methods studies were eligible for inclusion. Titles and abstracts were screened by two reviewers independently. Determinants were identified from the included studies, extracted and allocated to constructs in the Consolidated Framework for Implementation Research (CFIR). The quality of included studies was appraised by two reviewers independently. The results were synthesised in a narrative review using the constructs of the CFIR as grouping themes. Results The search yielded 7,500 articles for screening, of which 157 were included. Most studies were quantitative designs in nursing home settings and were conducted in the United States. Determinants were largely structural in nature and allocated most frequently to the inner and outer setting domains of the CFIR. The following structural characteristics and compliance were found to be positively associated: smaller facilities (measured by bed capacity); higher nurse-staffing levels; and lower staff turnover. A facility’s geographic location and compliance was also associated. It was difficult to make findings in respect of process determinants as qualitative studies were sparse, limiting investigation of the processes underlying regulatory compliance. Conclusion The literature in this field has focused to date on structural attributes of compliant providers, perhaps because these are easier to measure, and has neglected more complex processes around the implementation of regulatory standards. A number of gaps, particularly in terms of qualitative work, are evident in the literature and further research in this area is needed to provide a clearer picture.

背景:为全球医疗体系提供高质量照护服务,是其核心目标之一。保障服务质量的一项政策工具,是由独立的公共监管机构对相关服务实施规制。本系统综述旨在明确卫生与社会照护服务领域内,医疗服务主体遵守此类监管规定的决定因素。 研究方法:本研究检索了5个电子数据库及灰色文献(grey literature)来源。符合纳入标准的研究类型涵盖定量研究、定性研究与混合方法研究。由两名评审员独立筛选文献的标题与摘要。从纳入的研究中提取监管合规的决定因素,并将其归类至统一实施研究框架(Consolidated Framework for Implementation Research, CFIR)的相关构念中。两名评审员同样独立完成了对纳入研究的质量评价工作。最终以CFIR的构念作为分组主题,采用叙述性综述的形式对研究结果进行综合分析。 研究结果:本次检索共获取7500篇待筛选文献,最终纳入157篇。其中绝大多数为针对护理院(nursing home)场景的定量研究,且研究开展地以美国为主。本次识别的合规决定因素大多属于结构层面特征,且最常被归类至CFIR的内部环境与外部环境两大领域。研究发现以下结构特征与监管合规呈正相关:机构规模较小(以床位容量衡量)、护士配置水平更高、员工流动率更低。此外,机构的地理位置也与合规情况存在关联。由于定性研究较为匮乏,难以对监管合规背后的过程性决定因素展开深入探究,因此针对过程性决定因素的研究结论存在一定局限性。 研究结论:截至目前,该领域的现有文献多聚焦于合规服务提供者的结构属性,这或许是因为此类属性更易于量化测量,而围绕监管标准实施的更为复杂的过程性因素则被忽视。现有研究存在诸多不足,尤其是在定性研究方面,该领域仍需开展进一步研究,以形成更为清晰的认知图景。
创建时间:
2023-04-13
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作