As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
We developed a prototype CDSS that 1) provides tailored recommendations by combining a fall-risk prediction model, patients data, and evidence from CPGs, and 2) helps nurses to plan nursing care and document their activities for fall prevention. The accuracy of rules in knowledge base and inference engine was verified using ten scenarios and heuristics of user interface evaluated by four experts. We are currently evaluating the effects of the system on nurses’ workflow and patient outcomes.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.