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    The Influence of type of healthcare provider on clinical practice guideline adoption

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    Authors
    Hooper, Vallire Davis
    Issue Date
    2009-11
    URI

    http://hdl.handle.net/10675.2/623179
    
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    Abstract
    Postoperative/postdischarge nausea and vomiting (PONV /PDNV) impacts onethird of surgical patients annually. Evidence-based clinical practice guidelines have been developed to guide the prevention and/or management of PONV/PDNV; however, degree of adoption and common factors impacting the adoption of these guidelines is not ·known. Characteristics influencing guideline adoption include Rogers' Diffusion of Innovations_ l theoretical constructs of perceived guideline characteristics, individual, and organizational innovativeness. A cross-sectional, descriptive exploratory design employing a web-based survey technique was used to explore differences in perianesthesia/anesthesia healthcare provider guideline preferences and attitudes as they relate to the degree of adoption of PONV /PDNV guidelines. A random sample of 3267 perianesthesia nurses, nurse anesthetists, and anesthesiologists were invited to participate. Data analysis techniques included analysis of variance, chi-square (x2) analyses, ordinary least squares regression, and ordinal logistic regression. Survey response rate was 11.2%. Degree of overall guideline adoption was higher than expected at 59.6%. Rogers' theoretical assumptions were supported, with certain caveats. Individual innovativeness scores differed significantly among providers (F(2,324) = 16.75,p = 0.000), but the relationship of individual innovativeness to guideline adoption did not differ by group~ Degree of guideline adoption differed by type of provider with regards to organizational innovativeness and perceived guideline characteristics. Every one unit increase in interconnectedness, the only organizational innovativeness characteristic making a significant contribution (p < 0.00) to adoption, increased the odds of adoption by a factor of 1. 7 5 for perianesthesia nurses, 1.21 for anesthesiologists, and 1.08 for nurse anesthetists. The most influential construct in the overall model, however, was the perianesthesia/anesthesia healthcare provider's perception of guideline characteristics, particularly the observability of guideline related outcomes (p < 0.000). Every one unit increase in observability increased the odds of adoption by a factor of 3 .29 for perianesthesia nurses, 2.05 for nurse anesthetists, and 1.25 for anesthesiologists., The perception of observability of guideline outcomes, in this case, the obvious reduction in the incidence of PONV /PDNV, may influence guideline adoption more than other guideline characteristics. Organizational characteristics should be considered within the context of the adopting unit and the innovation of interest, as the interaction of these variables may fluctuate.
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    School of Graduate Studies
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