Most analytical Clinical Decision Support Systems (CDSS) remain within a research and development (R&D) environment and lack implementations in clinical contexts. This study discusses these implementation challenges as IT adoption barriers and gives possible solutions for these barriers. For this, we have studied the stakeholder perceptions of the case of an analytical CDSS implementation called ‘Big data for small babies’ (BD4SB) which analyzes medical data to predict the probability on sepsis for prematurely born babies and to support the physicians’ decision-making on ministering antibiotics. The stakeholders explain that the system shows promising results; however, the transition from the R&D environment to the clinical environment is complex. From this study, we learn new insights regarding the adoption of analytical DSS systems in the clinical field and we developed a new generalizable method for analytical DSS projects in an organizational context.
|Number of pages||22|
|Publication status||Published - 24 Oct 2019|
|Event||5th International Conference on Information and Communication Technologies in Organizations and Society, ICTO 2019: The Impact of Artificial Intelligence on Business and Society - Lille, France|
Duration: 24 Oct 2019 → 25 Oct 2019
Conference number: 5
|Conference||5th International Conference on Information and Communication Technologies in Organizations and Society, ICTO 2019|
|Abbreviated title||ICTO 2019|
|Period||24/10/19 → 25/10/19|
- analytics; clinical decision support system; artificial intelligence adoption
Wijnhoven, F., & Klein Koerkamp, R. (2019). Barriers for Adoption of Analytical CDSS in Healthcare: Insights from Case Stakeholders. Paper presented at 5th International Conference on Information and Communication Technologies in Organizations and Society, ICTO 2019, Lille, France.