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dc.contributor.authorDecker, Caroleeng
dc.contributor.authorArnold, Suzanne V.eng
dc.contributor.authorOlabiyi, Olawaleeng
dc.contributor.authorAhmad, Homaaeng
dc.contributor.authorGialde, Elizabetheng
dc.contributor.authorLuark, Jamieeng
dc.contributor.authorRiggs, Lisaeng
dc.contributor.authorDeJaynes, Terryeng
dc.contributor.authorSoto, Gabriel E.eng
dc.contributor.authorSpertus, John A.eng
dc.date.issued2008-12-31eng
dc.description.abstractAbstract Background In the setting of coronary angiography, generic consent forms permit highly variable communication between patients and physicians. Even with the existence of multiple risk models, clinicians have been unable to readily access them and thus provide patients with vague estimations regarding risks of the procedure. Methods We created a web-based vehicle, PREDICT, for embedding patient-specific estimates of risk from validated multivariable models into individualized consent documents at the point-of-care. Beginning August 2006, outpatients undergoing coronary angiography at the Mid America Heart Institute received individualized consent documents generated by PREDICT. In February 2007 this approach was expanded to all patients undergoing coronary angiography within the four Kansas City hospitals of the Saint Luke's Health System. Qualitative research methods were used to identify the implementation challenges and successes with incorporating PREDICT-enhanced consent documents into routine clinical care from multiple perspectives: administration, information systems, nurses, physicians, and patients. Results Most clinicians found usefulness in the tool (providing clarity and educational value for patients) and satisfaction with the altered processes of care, although a few cardiologists cited delayed patient flow and excessive patient questions. The responses from administration and patients were uniformly positive. The key barrier was related to informatics. Conclusion This preliminary experience suggests that successful change in clinical processes and organizational culture can be accomplished through multidisciplinary collaboration. A randomized trial of PREDICT consent, leveraging the accumulated knowledge from this first experience, is needed to further evaluate its impact on medical decision-making, patient compliance, and clinical outcomes.eng
dc.description.versionPeer Reviewedeng
dc.identifier.citationImplementation Science. 2008 Dec 31;3(1):58eng
dc.identifier.urihttp://dx.doi.org/10.1186/1748-5908-3-58eng
dc.identifier.urihttp://hdl.handle.net/10355/15029eng
dc.rights.holderCarole Decker et al.; licensee BioMed Central Ltd.eng
dc.titleImplementing an innovative consent form: the PREDICT experienceeng
dc.typeJournal Articleeng


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