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The objective is therefore to create a risk score for ADEs in an orthopedic and traumatological surgery department.
The study is an prospective, observational, cohort trial. A first step will consist of: (i) a collection of PIs carried out in an orthopedic and traumatological surgery department for 1 month, (ii) a score of the clinical impact of Pharmacist Interventions using the Clinical, Econnomic and organisationnal scale by method of consensus and (iii) a statistical analysis. Statistical analysis consists of (i) logistic regression modeling, (ii) performance measurement by discrimination and calibration, and internal validation by resampling. In a second step, external validation using a new sample will be performed.
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Pharmaceutical means for clinical pharmacy activities and pharmaceutical analysis are limited. Several methods can be used to increase the efficiency of resources allocated to clinical pharmacy activities. We hypothesize that highlighting patients at risk for iatrogenic drug events (ADEs) by applying a predictive score of ADE could be a way to increase the efficiency of clinician pharmacist interventions.
b. Assumption (s) and objective (s) The use of a predictive score of ADE in hospitalized patients in orthopedic surgery would make it possible to prioritize clinical pharmacy actions according to the resources allocated. The objective is therefore to create a risk score for ADEs in an orthopedic and traumatological surgery department. The secondary objective is to evaluate its superiority over other predictive models such as the age or the Physical Status Score physical status score used by anesthetists.
c. Methodology The study is an prospective, observational, cohort trial. A first step will consist of: (i) a collection of PIs carried out in an orthopedic and traumatological surgery department for 1 month, (ii) a score of the clinical impact of Pharmacist Interventions (NPS) using the Clinical, Econnomic and organisationnal scale by method of consensus and (iii) a statistical analysis. Statistical analysis consists of (i) logistic regression modeling, (ii) performance measurement by discrimination and calibration, and internal validation by resampling. In a second step, external validation using a new sample will be performed.
d. Expected results and prospects The usefulness of clinical pharmacy activities is now demonstrated, however an improvement in their efficiency is needed. The prospects are the integration of the risk score in the dispensing assistance software connected to the computerized patient record as well as extending the score to other types of surgery.
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500 participants in 2 patient groups
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