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What Determines the Use of Clinical Decision Support Systems in Nursing? Results of a Multiple Regression Analysis.
Studies in Health Technology and Informatics 2024 August 30
INTRODUCTION: In nursing, professionals are expected to base their practice on evidence-based knowledge, however the successful implementation of this knowledge into nursing practice is not always assured. Clinical Decision Support Systems (CDSS) are considered to bridge this evidence-practice gap.
METHODS: This study examines the extent to which evidence-based nursing (EBN) practices influence the use of CDSS and identifies what additional factors from acceptance theories such as UTAUT play a role.
RESULTS AND DISCUSSION: Our findings from three regression models revealed that nursing professionals and nursing students who employ evidence-based practices are not more likely to use an evidence-based CDSS. The relationship between an EBN composite score (model 1) or is individual dimensions (model 2) and CDSS use was not significant. However, a more comprehensive model (model 3), incorporating items from the UTAUT such as Social Influences, Facilitating Conditions, Performance Expectancy, and Effort Expectancy, supplemented by Satisfaction demonstrated a significant variance explained (R2 = 0.279). Performance Expectancy and Satisfaction were found to be significantly associated with CDSS utilization.
CONCLUSION: This underscores the importance of user-friendliness and practical utility of a CDSS. Despite potential limitations in generalizability and a limited sample size, the results provide insights into that CDSS first and foremost underly the same mechanisms of use as other health IT systems.
METHODS: This study examines the extent to which evidence-based nursing (EBN) practices influence the use of CDSS and identifies what additional factors from acceptance theories such as UTAUT play a role.
RESULTS AND DISCUSSION: Our findings from three regression models revealed that nursing professionals and nursing students who employ evidence-based practices are not more likely to use an evidence-based CDSS. The relationship between an EBN composite score (model 1) or is individual dimensions (model 2) and CDSS use was not significant. However, a more comprehensive model (model 3), incorporating items from the UTAUT such as Social Influences, Facilitating Conditions, Performance Expectancy, and Effort Expectancy, supplemented by Satisfaction demonstrated a significant variance explained (R2 = 0.279). Performance Expectancy and Satisfaction were found to be significantly associated with CDSS utilization.
CONCLUSION: This underscores the importance of user-friendliness and practical utility of a CDSS. Despite potential limitations in generalizability and a limited sample size, the results provide insights into that CDSS first and foremost underly the same mechanisms of use as other health IT systems.
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