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确定医疗保健领域创新实施的预测因素:实施效果的定量分析。

Determining the predictors of innovation implementation in healthcare: a quantitative analysis of implementation effectiveness.

作者信息

Jacobs Sara R, Weiner Bryan J, Reeve Bryce B, Hofmann David A, Christian Michael, Weinberger Morris

机构信息

Public Health Research Division, RTI International, 3040 East Cornwallis Road, Post Office Box 12194, Research Triangle Park, NC, 27709-2194, USA.

Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

出版信息

BMC Health Serv Res. 2015 Jan 22;15:6. doi: 10.1186/s12913-014-0657-3.

Abstract

BACKGROUND

The failure rates for implementing complex innovations in healthcare organizations are high. Estimates range from 30% to 90% depending on the scope of the organizational change involved, the definition of failure, and the criteria to judge it. The innovation implementation framework offers a promising approach to examine the organizational factors that determine effective implementation. To date, the utility of this framework in a healthcare setting has been limited to qualitative studies and/or group level analyses. Therefore, the goal of this study was to quantitatively examine this framework among individual participants in the National Cancer Institute's Community Clinical Oncology Program using structural equation modeling.

METHODS

We examined the innovation implementation framework using structural equation modeling (SEM) among 481 physician participants in the National Cancer Institute's Community Clinical Oncology Program (CCOP). The data sources included the CCOP Annual Progress Reports, surveys of CCOP physician participants and administrators, and the American Medical Association Physician Masterfile.

RESULTS

Overall the final model fit well. Our results demonstrated that not only did perceptions of implementation climate have a statistically significant direct effect on implementation effectiveness, but physicians' perceptions of implementation climate also mediated the relationship between organizational implementation policies and practices (IPP) and enrollment (p <0.05). In addition, physician factors such as CCOP PI status, age, radiological oncologists, and non-oncologist specialists significantly influenced enrollment as well as CCOP organizational size and structure, which had indirect effects on implementation effectiveness through IPP and implementation climate.

CONCLUSIONS

Overall, our results quantitatively confirmed the main relationship postulated in the innovation implementation framework between IPP, implementation climate, and implementation effectiveness among individual physicians. This finding is important, as although the model has been discussed within healthcare organizations before, the studies have been predominately qualitative in nature and/or at the organizational level. In addition, our findings have practical applications. Managers looking to increase implementation effectiveness of an innovation should focus on creating an environment that physicians perceive as encouraging implementation. In addition, managers should consider instituting specific organizational IPP aimed at increasing positive perceptions of implementation climate. For example, IPP should include specific expectations, support, and rewards for innovation use.

摘要

背景

在医疗保健机构中实施复杂创新的失败率很高。根据所涉及的组织变革范围、失败的定义以及判断标准,估计失败率在30%至90%之间。创新实施框架为研究决定有效实施的组织因素提供了一种有前景的方法。迄今为止,该框架在医疗保健环境中的应用仅限于定性研究和/或群体层面分析。因此,本研究的目的是使用结构方程模型对美国国立癌症研究所社区临床肿瘤项目中的个体参与者进行该框架的定量研究。

方法

我们在美国国立癌症研究所社区临床肿瘤项目(CCOP)的481名医生参与者中,使用结构方程模型(SEM)研究了创新实施框架。数据来源包括CCOP年度进展报告、对CCOP医生参与者和管理人员的调查以及美国医学协会医师主文件。

结果

总体而言,最终模型拟合良好。我们的结果表明,不仅实施氛围的认知对实施效果有统计学上的显著直接影响,而且医生对实施氛围的认知还介导了组织实施政策与实践(IPP)和登记人数之间的关系(p<0.05)。此外,诸如CCOP主要研究者身份、年龄、放射肿瘤学家和非肿瘤专科医生等医生因素对登记人数以及CCOP组织规模和结构有显著影响,而这些因素通过IPP和实施氛围对实施效果有间接影响。

结论

总体而言,我们的结果从定量角度证实了创新实施框架中所假定的个体医生在IPP、实施氛围和实施效果之间的主要关系。这一发现很重要, 因为尽管该模型此前已在医疗保健机构中进行过讨论,但相关研究主要是定性的且/或在组织层面。此外,我们的发现具有实际应用价值。希望提高创新实施效果的管理人员应专注于营造一种医生认为有利于实施的环境。此外,管理人员应考虑制定旨在增强对实施氛围积极认知的特定组织IPP。例如,IPP应包括对创新使用的具体期望、支持和奖励。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78cd/4307151/7aa61086c954/12913_2014_657_Fig1_HTML.jpg

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