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

Overview of attention for article published in BMC Health Services Research, January 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

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1 blog
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Title
Determining the predictors of innovation implementation in healthcare: a quantitative analysis of implementation effectiveness
Published in
BMC Health Services Research, January 2015
DOI 10.1186/s12913-014-0657-3
Pubmed ID
Authors

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

Abstract

BackgroundThe 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.MethodsWe 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.ResultsOverall 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 climateConclusionsOverall, 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 215 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Unknown 213 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 40 19%
Student > Ph. D. Student 30 14%
Student > Doctoral Student 21 10%
Student > Bachelor 20 9%
Researcher 19 9%
Other 28 13%
Unknown 57 27%
Readers by discipline Count As %
Medicine and Dentistry 31 14%
Social Sciences 26 12%
Business, Management and Accounting 22 10%
Nursing and Health Professions 21 10%
Psychology 14 7%
Other 39 18%
Unknown 62 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 September 2017.
All research outputs
#3,253,377
of 22,780,165 outputs
Outputs from BMC Health Services Research
#1,487
of 7,623 outputs
Outputs of similar age
#49,454
of 351,834 outputs
Outputs of similar age from BMC Health Services Research
#12
of 78 outputs
Altmetric has tracked 22,780,165 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,623 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has done well, scoring higher than 80% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 351,834 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 78 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.