Challenges developing evidence-based algorithms for the trauma reception and resuscitation project |
| |
Authors: | Geraldine A. Lee Angela Murray Rosie Bushnell Louise E. Niggemeyer |
| |
Affiliation: | 1. Sussex Health Outcomes Research and Education in Cancer, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, BN1 9QG, England, UK;2. Cochrane Institute of Primary Care and Public Health, Cardiff University, Heath Park, Cardiff, CF14 4YS, Wales, UK;3. MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Cambridge, CB2 0SR, England, UK;4. Wales Cancer Research Network, NISCHR Clinical Research Centre, 3rd Floor, 12 Cathedral Road, Cardiff CF11 9LJ, Wales, UK;1. Department of Economics and Business, University of Sassari, Italy;2. Department of Political and International Sciences, University of Siena, Italy;3. Department of Economics and Statistics, University of Siena, Italy |
| |
Abstract: | A project based at the Alfred Emergency and Trauma Centre in Melbourne, Australia aimed to standardise trauma resuscitation, documentation and interventions by developing best practice algorithms. The primary study objective was to demonstrate a reduction in management errors using a real-time computer based algorithm (the study group) compared to the control group in an open randomised controlled interventional study. A baseline control group was also used for comparison with usual (current) practice. In order to examine the existing evidence and algorithms in trauma care, nine teams of emergency nurses and doctors were formed. Specific literature searches performed by each team revealed a paucity of evidence supporting clinical practice in the trauma setting for procedures. Subsequently, the multidisciplinary teams worked together and developed algorithms based on best practice. The process revealed three main areas of challenges in the development of algorithms: (i) clinical, (ii) research and (iii) nursing challenges. The completion of the project demonstrated benefits in the real-time computer based algorithm with a reduction in the error rate per patient from the baseline control group to the intervention study group (2.30 vs. 2.13, p = 0.04) and error-free resuscitations increasing from 16% to 21.8% (p = .049). This project supported the implementation of a real-time computer based algorithm system with improved protocol compliance and reduced errors and morbidity. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|