Efficiency of electronic signout for ED-to-inpatient admission at a non-teaching hospital

Abstract

Admission handoff is a high-risk component of patient care. Previous studies have shown that a standardized physician electronic signout ("eSignout") may improve ED-to-inpatient handoff safety and efficiency in teaching hospitals. This model has not yet been studied in non-teaching hospitals. The objectives of the study were to determine the efficiency of an eSignout platform at a community affiliate hospital by comparing ED length of stay (LOS) for a 5-month period before and after implementation and to compare the quality assurance (QA) events among admitted patients for the same time period. A retrospective, interventional study was conducted with the main outcome measures including ED LOS with calculation of 95% CI, mean comparison (t test), and number of QA events before and after implementation of the eSignout model. Prior to eSignout implementation, 1045 patients were admitted [mean ED LOS 330.0 min (95% CI 318.6-341.4)]. Following implementation, 1106 patients were admitted [mean ED LOS 338.9 min (95% CI 327.4-350.4, p = 0.2853)]. Nine pre-implementation QA events and six post-implementation events were identified. Use of a physician eSignout in a non-teaching hospital had no statistically significant effect on ED LOS for the admitted patients. The effect of an electronic interdepartmental handoff tool for patient safety and clinical operations in the non-teaching setting is unclear.

What is the effect of electronic clinical handovers on patient outcomes? A systematic review

“…Ryan et al 22 also reported a reduced median length of stay from 5 to 4 days ( p = 0.047). Singleton et al 24 and Chen et al 17 however showed no statistically significant change in length of stay following implementation of e-handovers.…”

“…Nazar et al 19 failed to clearly describe their aims for their study and also lost 69 per cent of their participants to follow up, well over the 20 per cent threshold for high bias. Singleton et al 24 failed to utilise a large enough sample size to provide confidence in the findings. All studies provided a clear description of their e-handover and used the same e-handover format throughout their individual study.…”

“…Frequency of adverse events was reported in three studies; however, each study defined adverse events differently, so the results are expectedly inconsistent. Chen et al 17 and Singleton et al 24 report no statistically significant difference in adverse events before and after implementation of e-handovers. However, Nazar et al 19 found patients were 3.1, 3.0 or 2.8 times less likely to be readmitted to hospital within 30, 60 or 90 days, respectively, post-intervention.…”

“…26,27 A variety of outcome measures were reported, which will be compared under the following subheadings: length of stay, adverse events, time to procedure and handover completeness (see Table 3). 16 Chen et al 17 Clarke et al 18 Nazar et al 19 Patel et al 20 Raptis et al 21 Ryan et al 22 Singleton et al 24 Wilberforce et al 23 Length of stay. Length of stay was reported in three studies, with conflicting results.…”

“…MACE itself however is a problematic term in that it is inconsistently defined among the literature and ranges from a patient requiring stent thrombosis to cardiac death. 28 Singleton et al 24 do not list their entire definition of adverse events. They state that quality assurance (QA) events are automatically triggered by adverse events such as ED-to-ICU (intensive care unit) transfer, or death within 24 h. Non-automated QA events include physician complaints for communication errors and diagnostic error.…”