Identifying diverse concepts of discharge failure patients at emergency department in the USA: a large-scale retrospective observational study

Abstract

ObjectivesIdentifying patients who are at high risk for discharge failure allows for implementation of interventions to improve their care. However, discharge failure is currently defined in literature with great variability, making targeted interventions more difficult. We aim to derive a screening tool based on the existing diverse discharge failure models.Design, setting and participantsThis is a single-centre retrospective cohort study in the USA. Data from all patients discharged from the emergency department were collected from 1 January 2015 through 31 December 2017 and followed up within 30 days.MethodsScoring systems were derived using modified Framingham methods. Sensitivity, specificity and area under the receiver operational characteristic (AUC) were calculated and compared using both the broad and restricted discharge failure models.ResultsA total of 227 627 patients were included. TheScreening forHealthcare fOllow-UpTool (SHOUT) scoring system was derived based on the broad and restricted discharge failure models and applied back to the entire study cohort. A sensitivity of 80% and a specificity of 71% were found in SHOUT scores to identify patients with broad discharge failure with AUC of 0.83 (95% CI 0.83 to 0.84). When applied to a 3-day restricted discharge failure model, a sensitivity of 86% and a specificity of 60% were found to identify patients with AUC of 0.79 (95% CI 0.78 to 0.80).ConclusionThe SHOUT scoring system was derived and used to screen and identify patients that would ultimately become discharge failures, especially when using broad definitions of discharge failure. The SHOUT tool was internally validated and can be used to identify patients across a wide spectrum of discharge failure definitions.

Development and Internal Validation of a Model Predicting Safe, Early Discharge Among Patients Presenting to the Emergency Department with an Infection.

“…[ [59][60][61][62] Also, in the Netherlands, if a patient is known in a tertiary care center, like ours, readmission to another hospital is very unlikely due to the complexity of their condition.…”

“…Multiple studies analyzed ED discharge safety, using short-term outcomes, like readmission or death, following ED discharge. [59][60][61][62] Two of these studies proposed a model for the prediction of safe ED discharge, with AUCs ranging from 0.68 to 0.83. [60,61] Both the models predicting early discharge and the models predicting safe ED discharge include patient characteristics, like age and the presence of comorbidities, and most include arrival by ambulance, GP referral and vital signs measured closest to discharge.…”

“…[59][60][61][62] Two of these studies proposed a model for the prediction of safe ED discharge, with AUCs ranging from 0.68 to 0.83. [60,61] Both the models predicting early discharge and the models predicting safe ED discharge include patient characteristics, like age and the presence of comorbidities, and most include arrival by ambulance, GP referral and vital signs measured closest to discharge. [36,57,58,60,61] However, only one incorporated repeated vital sign measurements [35], and none included biomarkers for organ dysfunction, components of various clinical scoring systems or the clinical impression score.…”

“…[60,61] Both the models predicting early discharge and the models predicting safe ED discharge include patient characteristics, like age and the presence of comorbidities, and most include arrival by ambulance, GP referral and vital signs measured closest to discharge. [36,57,58,60,61] However, only one incorporated repeated vital sign measurements [35], and none included biomarkers for organ dysfunction, components of various clinical scoring systems or the clinical impression score. The studies that did analyze the safety of ED discharges used endpoints that differ from study to study, with some utilizing ED readmission [61,62] and others ward, ICU admission or death [59,60].…”

“…[36,57,58,60,61] However, only one incorporated repeated vital sign measurements [35], and none included biomarkers for organ dysfunction, components of various clinical scoring systems or the clinical impression score. The studies that did analyze the safety of ED discharges used endpoints that differ from study to study, with some utilizing ED readmission [61,62] and others ward, ICU admission or death [59,60]. In summary, available studies either analyzed predictors for early discharge or predictors for safe discharge.…”