Design This phase will comprise the latter stages of analysis of results of the field study,
preparation of reports to inform the expert panel, a two day seminar to consider the findings of the field study and assembly of the final QI set with associated recommendations. A formal report will be prepared for general scrutiny in addition to publication for the peer-reviewed Inhibitors,research,lifescience,medical literature. A formal procedure for selection of the final QI set will follow the expert panel deliberations, similar to that used in assembly of the Assessing Care Of Vulnerable Elders (ACOVE) indicators [59]. This process involves two rounds of anonymous ratings on a risk-benefit scale with a teleconference group discussion Inhibitors,research,lifescience,medical occurring between rounds [60,61]. Data analysis Primary analysis will be to evaluate the new QIs. The QIs will be adjusted for ascertainment and selection bias through risk adjustment procedures [58]. The determination of appropriate case-mix and risk adjustment procedures will involve simple bi-variable descriptive statistics (correlations, mean differences). Good candidates for adjustment will be included as matching criteria in the QI
adjustment process. The QI adjustment method will use a procedure that has the advantage of being quasi-parametric, Inhibitors,research,lifescience,medical involving matching individual PF-06463922 ic50 patients in target EDs to randomly selected patients from other EDs. This counterfactual Inhibitors,research,lifescience,medical contrast will include a re-sampling procedure and allow QIs to be expressed as odds ratios or expected proportions given an overall average rate and an empirically based replication (i.e. confidence) interval. Relative to extant methods of risk adjustment this approach is relatively simple, can be implemented in clinical populations of small size and represents as perfect as possible adjustment for differences Inhibitors,research,lifescience,medical in patient mix across clinical
settings. The reliability of QI scores will be evaluated by multiple bootstrapped split-half correlations of patient samples and time-to-time correlations of repeated QI scores. This is a unit-level analysis, where for each ED we will use a bootstrapping data augmentation approach to generate 20 random half samples of patients. Consideration of the issues specific to patients with cognitive impairment, nursing home residents and those patients requiring palliative care will result in an additional analysis of QI data to much identify whether any QIs are specifically significant for these sub-groups. Comparisons with SAEM QIs will use standard methods for comparing correlation coefficients for the contrasting reliability coefficients, and cross tabulations of tertiles of QIs in similar domains for the validity assessment. Voting Following the final expert panel, the indicators will be presented to the expert panel in a summary document. In the document, each indicator will be described in relation to the agreed name, denominator, numerator and exclusion criteria.
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