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Implement Sci. 2016 Feb 20;11:21. doi: 10.1186/s13012-016-0382-x.

Bariatric surgery implementation trends in the USA from 2002 to 2012.

Author information

1
College of Nursing, Medical University of South Carolina, Room 414, 99 Jonathan Lucas Street, Charleston, SC, 29425, USA. johnsoem@Musc.edu.
2
Department of Health Leadership and Management, Medical University of South Carolina, 151 Rutledge Avenue, Charleston, SC, 29425, USA. simpsona@musc.edu.
3
Department of Health Leadership and Management, Medical University of South Carolina, 151 Rutledge Avenue, Charleston, SC, 29425, USA. harveyji@musc.edu.
4
Department of Health Leadership and Management, Medical University of South Carolina, 151 Rutledge Avenue, Charleston, SC, 29425, USA. simpsonk@musc.edu.

Abstract

BACKGROUND:

Many beneficial health care interventions are either not put into practice or fail to diffuse over time due to complex contextual factors that affect implementation and diffusion. Bariatric surgery is an example of an effective intervention that recently experienced a plateau and decrease in rates, with minimal documented justification for this trend. While there are conceptual models that provide frameworks of general innovation implementation and diffusion, few studies have tested these models with data to measure the relative effects of factors that affect diffusion of specific health care interventions.

METHODS:

A literature review identified factors associated with implementation and diffusion of health care innovations. These factors were utilized to construct a conceptual model of diffusion to explain changes in bariatric surgery over time. Six data sources were used to construct measures of the study population and factors in the model that may affect diffusion of surgery. The population included obese and morbidly obese patients from 2002 to 2012 who had bariatric surgery in 15 states. Multivariable models were used to identify environmental, population, and medical practice factors that facilitated or impeded diffusion of bariatric surgery over time.

RESULTS:

It was found that while bariatric surgery rates increased over time, the speed of growth in surgeries, or diffusion, slowed. Higher cumulative number of surgeries and higher proportion of the state population in age group 50-59 slowed surgery growth, but presence of Medicare centers of excellence increased the speed of surgery diffusion. Over time, the factors affecting the diffusion of bariatric surgery fluctuated, indicating that diffusion is affected by temporal and cumulative effects.

CONCLUSIONS:

The primary driver of diffusion of bariatric surgery was the extent of centers of excellence presence in a state. Higher cumulative surgery rates and higher proportions of older populations in a state slowed diffusion. Surprisingly, measures of the presence of champions were not significant, perhaps because these are difficult to measure in the aggregate. Our results generally support the conceptual model of diffusion developed from the literature, which may be useful for examining other innovations, as well as for designing interventions to support rapid diffusion of innovations to improve health outcomes and quality of care.

PMID:
26897023
PMCID:
PMC4761154
DOI:
10.1186/s13012-016-0382-x
[Indexed for MEDLINE]
Free PMC Article

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