Framework for the impact analysis and implementation of Clinical Prediction Rules (CPRs)

Hdl Handle:
http://hdl.handle.net/10147/189812
Title:
Framework for the impact analysis and implementation of Clinical Prediction Rules (CPRs)
Authors:
Wallace, Emma; Smith, Susan M; Perera-Salazar, Rafael; Vaucher, Paul; McCowan, Colin; Collins, Gary; Verbakel, Jan; Lakhanpaul, Monica; Fahey, Tom; (IDAPP) group, International Diagnostic and Prognosis Prediction group
Citation:
BMC Medical Informatics and Decision Making. 2011 Oct 14;11(1):62
Issue Date:
14-Oct-2011
URI:
http://hdl.handle.net/10147/189812
Abstract:
Abstract Clinical Prediction Rules (CPRs) are tools that quantify the contribution of symptoms, clinical signs and available diagnostic tests, and in doing so stratify patients according to the probability of having a target outcome or need for a specified treatment. Most focus on the derivation stage with only a minority progressing to validation and very few undergoing impact analysis. Impact analysis studies remain the most efficient way of assessing whether incorporating CPRs into a decision making process improves patient care. However there is a lack of clear methodology for the design of high quality impact analysis studies. We have developed a sequential four-phased framework based on the literature and the collective experience of our international working group to help researchers identify and overcome the specific challenges in designing and conducting an impact analysis of a CPR. There is a need to shift emphasis from deriving new CPRs to validating and implementing existing CPRs. The proposed framework provides a structured approach to this topical and complex area of research.
Item Type:
Journal Article

Full metadata record

DC FieldValue Language
dc.contributor.authorWallace, Emma-
dc.contributor.authorSmith, Susan M-
dc.contributor.authorPerera-Salazar, Rafael-
dc.contributor.authorVaucher, Paul-
dc.contributor.authorMcCowan, Colin-
dc.contributor.authorCollins, Gary-
dc.contributor.authorVerbakel, Jan-
dc.contributor.authorLakhanpaul, Monica-
dc.contributor.authorFahey, Tom-
dc.contributor.author(IDAPP) group, International Diagnostic and Prognosis Prediction group-
dc.date.accessioned2011-11-17T10:47:07Z-
dc.date.available2011-11-17T10:47:07Z-
dc.date.issued2011-10-14-
dc.identifierhttp://dx.doi.org/10.1186/1472-6947-11-62-
dc.identifier.citationBMC Medical Informatics and Decision Making. 2011 Oct 14;11(1):62-
dc.identifier.urihttp://hdl.handle.net/10147/189812-
dc.description.abstractAbstract Clinical Prediction Rules (CPRs) are tools that quantify the contribution of symptoms, clinical signs and available diagnostic tests, and in doing so stratify patients according to the probability of having a target outcome or need for a specified treatment. Most focus on the derivation stage with only a minority progressing to validation and very few undergoing impact analysis. Impact analysis studies remain the most efficient way of assessing whether incorporating CPRs into a decision making process improves patient care. However there is a lack of clear methodology for the design of high quality impact analysis studies. We have developed a sequential four-phased framework based on the literature and the collective experience of our international working group to help researchers identify and overcome the specific challenges in designing and conducting an impact analysis of a CPR. There is a need to shift emphasis from deriving new CPRs to validating and implementing existing CPRs. The proposed framework provides a structured approach to this topical and complex area of research.-
dc.titleFramework for the impact analysis and implementation of Clinical Prediction Rules (CPRs)-
dc.typeJournal Article-
dc.language.rfc3066en-
dc.rights.holderWallace et al.; licensee BioMed Central Ltd.-
dc.description.statusPeer Reviewed-
dc.date.updated2011-11-15T16:08:40Z-
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