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

Table 3 Standardized total, direct, and indirect effects

	Total effect	Direct effect	Indirect effect
*Outcome: Enrollment in NCI-Sponsored Cancer Clinical Trials in 2011*
Perceptions of Implementation Climate	0.285*	0.285*	N/A
Organizational Implementation Policies and Practices (IPP)	0.069*	N/A	0.069*
Age	−0.264*	−0.179	−0.085
Hospital-Based^	−0.043	−0.066	0.023
Solo Practice^	−0.001	0.034	−0.035
Non U.S. Trained	−0.035	−0.011	−0.024
PI	0.356*	0.322*	0.034
Tenure	0.224	0.117	0.107
Oncology⁺	−0.097	−0.075	−0.022
Radiation Oncology⁺	−0.162*	−0.120	−0.042
Surgery⁺	−0.114	−0.077	−0.037
Other Specialty⁺	−0.147*	−0.120	−0.027
Organizational Size	0.028*	N/A	0.028*
Structure: Hospital Cancer Center⁺⁺	0.047*	N/A	0.047*
Structure: Research Institute⁺⁺	0.016*	N/A	0.016*
Structure: Other⁺⁺	0.024*	N/A	0.024*
Organizational Maturity	0.000	N/A	0.000

Model Fit Statistics: CFI = 0.933; TLI = 0.918; RMSEA = 0.045; SRMR = 0.048.
Note: Total effects is the sum of direct and indirect effects.
Note: Indirect effects are the product of the regression coefficients leading to the outcome. For example for OIPP, OIPP predicts perceptions and perceptions predicts enrollment. The indirect effect and subsequently the total effect of OIPP on enrollment equals the product of the two regression coefficients (From Figure 3) 0.243*0.285 = 0.069.
*Statistically Significant (p < 0.05).
^Compared to Group Practice.
⁺Compared to General Non-Specialized Oncology.
⁺⁺Compared to Separate Non-Profit Structure.

ISSN: 1472-6963