Purpose: Serious clinical deterioration precedes most cardiopulmonary arrests, and there is evidence that organized responses to this deterioration may prevent a substantial proportion of in-hospital deaths. We aimed to increase the utilization of our medical crisis response team (Condition C) to impact this source of mortality.
Methods: We have examined the change in numbers of Condition Cs and the main alternative response strategy (sequential stat pages) after the implementation of 4 strategies to increase Condition C utilization: (1) immediate reviews of all sequential STAT pages, (2) feedback to caregivers responsible for delays in Condition C activation, (3) creation of objective criteria for invoking a crisis response, and (4) dissemination of objective criteria through posting in units, e-mail, and in-service oral presentations.
Results: Over a 3-year period, interventions were followed by increased use of organized responses to medical crises (Condition Cs) and decreased numbers of disorganized responses (sequential STAT pages). The interventions that involved objective definition and dissemination of criteria for initiating the Condition C response were followed by 19.2 more Condition Cs monthly (95% confidence interval [CI], 12.1-26.3; P<0001) and 5.7 fewer sequential STAT pages monthly (95% CI, 3.2-8.2). The interventions that involved giving feedback to medical personnel based on review of their care were not associated with changes in the measures.
Conclusion: Utilization of an important patient safety measure may be increased by focused interventions at an urban tertiary care hospital.
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http://dx.doi.org/10.1053/jcrc.2003.50002 | DOI Listing |
J Biopharm Stat
December 2024
Chiesi Farmaceutici, Statistical Methodology, Parma, Italy.
Determining the probability of success of a clinical trial using a prior distribution on the treatment effect can significantly enhance decision-making by the sponsor. In a group sequential design, the probability of success calculated at the design stage can be updated to incorporate the information disclosed by the Data Monitoring Committee (DMC), usually consisting in a simple statement that advises to continue or to stop the trial, either for efficacy or futility, following pre-specified rules defined in the protocol. We define the "probability of success post interim" as the probability of success conditioned on the assumption that the DMC recommends continuing the trial after an interim analysis.
View Article and Find Full Text PDFStat Methods Med Res
November 2024
School of Mathematical Sciences, Queen Mary University of London, London, UK.
Covariate-adjusted response adaptive (CARA) designs are effective in increasing the expected number of patients receiving superior treatment in an ongoing clinical trial, given a patient's covariate profile. There has recently been extensive research on CARA designs with parametric distributional assumptions on patient responses. However, the range of applications for such designs becomes limited in real clinical trials.
View Article and Find Full Text PDFPharm Stat
November 2024
Fairholme, Upper Street, Tilmanstone, Kent, UK.
The topic of this article is pre-posterior distributions of success or failure. These distributions, determined before a study is run and based on all our assumptions, are what we should believe about the treatment effect if we are told only that the study has been successful, or unsuccessful. I show how the pre-posterior distributions of success and failure can be used during the planning phase of a study to investigate whether the study is able to discriminate between effective and ineffective treatments.
View Article and Find Full Text PDFStat Med
December 2024
Institute of Statistics and Big Data, Renmin University of China, Beijing, China.
In clinical trials, subjects are usually recruited sequentially. According to the outcomes amassed thus far in a trial, the response-adaptive randomization (RAR) design has been shown to be an advantageous treatment assignment procedure that skews the treatment allocation proportion to pre-specified objectives, such as sending more patients to a more promising treatment. Unfortunately, there are circumstances under which very few data of the primary endpoints are collected in the recruitment period, such as circumstances relating to public health emergencies and chronic diseases, and RAR is thus difficult to apply in allocating treatments using available outcomes.
View Article and Find Full Text PDFStat Med
December 2024
Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.
Results from randomized control trials (RCTs) may not be representative when individuals refuse to be randomized or are excluded for having a preference for which treatment they receive. If trial designs do not allow for participant treatment preferences, trials can suffer in accrual, adherence, retention, and external validity of results. Thus, there is interest surrounding clinical trial designs that incorporate participant treatment preferences.
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