AIMS AND OBJECTIVES: To explore how nurses use computerised clinical decision support systems in clinical practice and the factors that influence use. BACKGROUND: There is limited evidence for the benefits of computerised clinical decision support systems in nursing, with the majority of existing research focusing on nurses' use of decision support for telephone triage. Research has suggested that several factors including nurses' experience, features of the technology system and organisational factors may influence how decision support is used in practice. DESIGN: A multiple case site study. METHODS: Four case sites were purposively selected to provide variation in staff experience, technology used and decisions supported by the technology. Data were collected in each case site using non-participant observation of nurse/patient consultations (n = 115) and interviews with nurses (n = 55). Data were analysed using thematic content analysis. RESULTS: Computerised decision support systems were used in a variety of ways by nurses, including recording information, monitoring patients' progress and confirming decisions that had already been made. Nurses' experience with the decision and the technology affected how they used a decision support system and whether or not they over-rode recommendations made by the system. The ability of nurses to adapt the technology also affected its use. CONCLUSIONS: How nurses use computerised decision support appears to be the result of an interaction between a nurses' experience and their ability to adapt the technology to 'fit' with local clinical practice. RELEVANCE TO CLINICAL PRACTICE: One of the stated aims of introducing computerised decision support systems to assist nursing practice is to reduce variation and/or the number of errors associated with clinical practice. The study found unanticipated uses in such systems such as the routine over-riding of recommendations which could lead to an increase rather than a decrease in variation or errors.
AIMS AND OBJECTIVES: To explore how nurses use computerised clinical decision support systems in clinical practice and the factors that influence use. BACKGROUND: There is limited evidence for the benefits of computerised clinical decision support systems in nursing, with the majority of existing research focusing on nurses' use of decision support for telephone triage. Research has suggested that several factors including nurses' experience, features of the technology system and organisational factors may influence how decision support is used in practice. DESIGN: A multiple case site study. METHODS: Four case sites were purposively selected to provide variation in staff experience, technology used and decisions supported by the technology. Data were collected in each case site using non-participant observation of nurse/patient consultations (n = 115) and interviews with nurses (n = 55). Data were analysed using thematic content analysis. RESULTS: Computerised decision support systems were used in a variety of ways by nurses, including recording information, monitoring patients' progress and confirming decisions that had already been made. Nurses' experience with the decision and the technology affected how they used a decision support system and whether or not they over-rode recommendations made by the system. The ability of nurses to adapt the technology also affected its use. CONCLUSIONS: How nurses use computerised decision support appears to be the result of an interaction between a nurses' experience and their ability to adapt the technology to 'fit' with local clinical practice. RELEVANCE TO CLINICAL PRACTICE: One of the stated aims of introducing computerised decision support systems to assist nursing practice is to reduce variation and/or the number of errors associated with clinical practice. The study found unanticipated uses in such systems such as the routine over-riding of recommendations which could lead to an increase rather than a decrease in variation or errors.
Authors: Dawn Dowding; David Russell; Margaret V McDonald; Marygrace Trifilio; Jiyoun Song; Carlin Brickner; Jingjing Shang Journal: J Am Med Inform Assoc Date: 2021-02-15 Impact factor: 4.497
Authors: Reed T Sutton; David Pincock; Daniel C Baumgart; Daniel C Sadowski; Richard N Fedorak; Karen I Kroeker Journal: NPJ Digit Med Date: 2020-02-06