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

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 promisi...

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Bibliographic Details
Published in:BMC health services research 2015-01, Vol.15 (1), p.6-6, Article 6
Main Authors: Jacobs, Sara R, Weiner, Bryan J, Reeve, Bryce B, Hofmann, David A, Christian, Michael, Weinberger, Morris
Format: Article
Language:English
Subjects:
Adult
Attitude of Health Personnel
Cancer
Clinical trials
Cross-Sectional Studies
Data Interpretation, Statistical
Efficiency, Organizational - standards
Efficiency, Organizational - statistics & numerical data
Enrollments
Female
Forecasting
Health services
Hospitals
Humans
Hypotheses
Innovations
Laws, regulations and rules
Male
Medical societies
Middle Aged
National Cancer Institute (U.S.) - standards
National Cancer Institute (U.S.) - statistics & numerical data
Oncology Service, Hospital - standards
Oncology Service, Hospital - statistics & numerical data
Organizational change
Organizational Innovation
Patient Protection & Affordable Care Act 2010-US
Patients
Physicians
Physicians - psychology
Qualitative Research
Quantitative analysis
Technological change
Technology application
United States
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Summary: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. 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. 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
ISSN:1472-6963
1472-6963
DOI:10.1186/s12913-014-0657-3