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

Emma Wallace, Susan M. Smith, Rafael Perera-Salazar, Paul Vaucher, Colin McCowan, Gary Collins, Jan Verbakel, Monica Lakhanpaul, Tom Fahey, Int Diagnostic Prognosis Predictio

    Research output: Contribution to journalArticlepeer-review

    87 Citations (Scopus)

    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.

    Original languageEnglish
    Article number62
    Pages (from-to)-
    Number of pages7
    JournalBMC Medical Informatics and Decision Making
    Volume11
    DOIs
    Publication statusPublished - 14 Oct 2011

    Keywords

    • OTTAWA ANKLE RULES
    • RANDOMIZED CONTROLLED-TRIAL
    • ACUTE CARDIAC ISCHEMIA
    • EMERGENCY-DEPARTMENTS
    • QUALITY-IMPROVEMENT
    • PNEUMONIA
    • MULTICENTER
    • GUIDELINES
    • DIAGNOSIS
    • RISK

    Fingerprint

    Dive into the research topics of 'Framework for the impact analysis and implementation of Clinical Prediction Rules (CPRs)'. Together they form a unique fingerprint.

    Cite this