Scholarlink

<p>The integration of intravenous (IV) smart pumps with electronic health records (EHR) has been shown to reduce documentation errors and improve safety in nursing practice. However, there is limited information regarding the acceptance of this technology among anesthesiologists. This study aimed to evaluate the acceptance and adoption of IV smart pump integration with an Anesthesia Information Management System (AIMS) at a tertiary pediatric hospital. We conducted a cross-sectional survey six weeks following the implementation of IV smart pump integration. The project was approved as a Quality Improvement initiative. The survey was distributed to 112 anesthesia department members. We employed the Unified Theory of Acceptance and Use of Technology (UTAUT) to assess user acceptance, examining constructs such as Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions. Structural equation modeling (SEM) was used to analyze the relationships between these constructs and Behavioral Intention. Forty-two individuals (38.1%) completed the survey. Adoption was widespread, with respondents utilizing smart pump integration for a median of 76.5% of eligible medications. While 48% of respondents reported satisfaction, 26% were unsatisfied, primarily citing difficulties with troubleshooting. Structural equation modeling revealed that Performance Expectancy was the strongest predictor of Behavioral Intention (path coefficient 0.60), followed by Facilitating Conditions (0.21). Age positively influenced Social Influence (0.25) but negatively affected Performance Expectancy (-0.15). Anesthesiologists demonstrated a high rate of adoption of IV smart pump integration shortly after implementation. Perceived usefulness was the primary driver of the intention to use the system. Given the single-center nature of this study and the limited response rate, these results should be considered hypothesis-generating. Strategies to optimize future adoption should focus on demonstrating clinical utility and providing targeted training on troubleshooting.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Acceptance and Adoption of Intravenous Smart Pump Integration to Anesthesia Information Management System by Anesthesiologists: A Single Centre Study

  • 期刊论文

  • 发表日期：

    2026年3月27日

查看全文
  • Anne Mooser,
  • Gregory Johnson,
  • Conor McDonnell,
  • Clyde Matava

摘要

The integration of intravenous (IV) smart pumps with electronic health records (EHR) has been shown to reduce documentation errors and improve safety in nursing practice. However, there is limited information regarding the acceptance of this technology among anesthesiologists. This study aimed to evaluate the acceptance and adoption of IV smart pump integration with an Anesthesia Information Management System (AIMS) at a tertiary pediatric hospital. We conducted a cross-sectional survey six weeks following the implementation of IV smart pump integration. The project was approved as a Quality Improvement initiative. The survey was distributed to 112 anesthesia department members. We employed the Unified Theory of Acceptance and Use of Technology (UTAUT) to assess user acceptance, examining constructs such as Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions. Structural equation modeling (SEM) was used to analyze the relationships between these constructs and Behavioral Intention. Forty-two individuals (38.1%) completed the survey. Adoption was widespread, with respondents utilizing smart pump integration for a median of 76.5% of eligible medications. While 48% of respondents reported satisfaction, 26% were unsatisfied, primarily citing difficulties with troubleshooting. Structural equation modeling revealed that Performance Expectancy was the strongest predictor of Behavioral Intention (path coefficient 0.60), followed by Facilitating Conditions (0.21). Age positively influenced Social Influence (0.25) but negatively affected Performance Expectancy (-0.15). Anesthesiologists demonstrated a high rate of adoption of IV smart pump integration shortly after implementation. Perceived usefulness was the primary driver of the intention to use the system. Given the single-center nature of this study and the limited response rate, these results should be considered hypothesis-generating. Strategies to optimize future adoption should focus on demonstrating clinical utility and providing targeted training on troubleshooting.