Case Study: Lessons Learned when Embedding Evidence-Based Knowledge in a Nurse Care Planning and Documentation System

Case Study: Lessons Learned when Embedding Evidence-Based Knowledge in a Nurse Care Planning and Documentation System

Judy Murphy (Aurora Health Care, USA), Ellen Harper (Cerner Corporation, USA), Elizabeth C. Devine (University of Wisconsin-Milwaukee, USA), Laura J. Burke (Aurora Health Care, USA) and Mary L. Hook (Aurora Health Care, USA)
DOI: 10.4018/978-1-60960-034-1.ch014
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A partnership between Aurora Health Care, Cerner Corporation, and the University of Wisconsin-Milwaukee College of Nursing that focused on the design of an informatics solution that aimed to allow evidenced based information to be available to nurses at the point of care and promote engagement in the electronic recording of patient data is described. The process of determining need, building the solution, integrating into nurse practice, and evaluation is laid out.
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Project Background

The need to use research and other sources of best evidence to support clinical decision-making is well documented in the literature (Melnyk & Fineout-Overholt, 2005; Sackett, Rosenberg, Gray, Haynes, & Richardson, 1996). But, even when high quality evidence and guidelines are available, they are not always used in practice (van Achterberg, Schoonhoven & Grol, 2008). Based largely on studies with physicians, it has been found that using computerized information systems, reminders, and decision-support can improve clinical practice as well as the adoption of innovations and evidence-based care (Kawamoto, Houlihan, Balas, & Lobach, 2005; van Achterberg et al., 2008).

Clinical decision-support has been defined broadly by the organizations such as the Healthcare Information and Management Systems Society (HIMSS) and the American Medical Informatics Association (AMIA). In an AMIA position paper which is a report of the Joint Clinical Decision Support Workgroup, Teich, Osheroff, Pifer, Sittig, and Jenders (2005) asserted that clinical decision-support provides intelligently filtered clinical knowledge and patient information at the appropriate time and in the appropriate manner in order to enhance care. They stated that clinical decision-support includes such things as alerts, reminders, structured forms, pick lists, guideline support, and reference information.

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