No abstract

These findings suggest that overlapping graphs do not yield the performance advantage that many health professionals assume, either for novices or experienced nurses, even when the Seagull Sign is used.

Our findings suggest that several individual design features can affect novice chart-users' ability to detect patient deterioration. More broadly, the study further demonstrates the need to evaluate chart designs empirically.

Aims To identify the potential sources of inaccuracy in manually measured adult respiratory rate (RR) data and quantify their effects. Design Quantitative systematic review with meta‐analyses where appropriate. Data Sources Medline, CINAHL, and Cochrane Library (from database inception to 31 July 2019). Review Methods Studies presenting data on individual sources of inaccuracy in the manual measurement of adult RR were analysed, assessed for quality, and grouped according to the source of inaccuracy investigated. Quantitative data were extracted and synthesized and meta‐analyses performed where appropriate. Results Included studies (N = 49) identified five sources of inaccuracy. The awareness effect creates an artefactual reduction in actual RR, and observation methods involving shorter counts cause systematic underscoring. Individual RR measurements can differ substantially in either direction between observations due to inter‐ or intra‐observer variability. Value bias, where particular RRs are over‐represented (suggesting estimation), is a widespread problem. Recording omission is also widespread, with higher average rates in inpatient versus triage/admission contexts. Conclusion This review demonstrates that manually measured RR data are subject to several potential sources of inaccuracy. Impact RR is an important indicator of clinical deterioration and commonly included in track‐and‐trigger systems. However, the usefulness of RR data depends on the accuracy of the observations and documentation, which are subject to five potential sources of inaccuracy identified in this review. A single measurement may be affected by several factors. Hence, clinicians should interpret recorded RR data cautiously unless systems are in place to ensure its accuracy. For nurses, this includes counting rather than estimating RRs, employing 60‐s counts whenever possible, ensuring patients are unaware that their RR is being measured, and documenting the resulting value. For any given site, interventions to improve measurement should take into account the local organizational and cultural context, available resources, and the specific measurement issues that need to be addressed.