Methods of detection of adverse events in critical care: a protocol for a systematic review
BMJ open, ISSN: 2044-6055, Vol: 14, Issue: 11, Page: e085545-null
2024
- 1Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures1
- Readers1
Article Description
INTRODUCTION: Adverse events, defined as unintended patient harm contributed to by healthcare, continue to increase morbidity, mortality and cost. Critically ill patients are at high risk of adverse events; however, the optimal approach to detection in this setting is unknown. Numerous approaches have been used, including voluntary reporting, chart reviews and trigger tools. The objective of this systematic review is to gain insight into the capacity of individual methods to detect adverse events in the intensive care unit (ICU), to inform implementation, and to facilitate quality improvement. METHODS AND ANALYSIS: Ovid MEDLINE, Ovid EMBASE, CINAHL, the Cochrane Library and Google Scholar were searched on 2 October 2023 for randomised controlled trials and observational studies evaluating the implementation or ongoing use of one or more systems of detection of adverse events in ICUs (neonatal to adult). Outcomes will include the total number of adverse events identified by detection method per 100 patient days (primary outcome), categories of adverse events, associated harm and whether detection informed quality improvement. A risk of bias assessment will be performed. The results will provide insight into each method's capacity to detect adverse events in addition to their associated severity. ETHICS AND DISSEMINATION: Ethics approval was not required as patient data will not be collected. A manuscript will be submitted to a peer-reviewed scientific journal. PROSPERO REGISTRATION NUMBER: CRD42024466584.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85211233066&origin=inward; http://dx.doi.org/10.1136/bmjopen-2024-085545; http://www.ncbi.nlm.nih.gov/pubmed/39613427; https://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2024-085545; https://dx.doi.org/10.1136/bmjopen-2024-085545; https://bmjopen.bmj.com/content/14/11/e085545
BMJ
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know