Clinician perspectives on reasons for, implications and management of unplanned patient returns to the Emergency Department: A descriptive study

Hutchinson, Claire; Curtis, Kate; McCloughen, Andrea; Fethney, Judith; Wiseman, Glen; Hutchinson, Laura

doi:10.1016/j.ienj.2021.101125

Cited by 4 publications

(6 citation statements)

References 41 publications

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“…Second, because high-risk ED revisit is multifactorial, some features were not collected, which may cause information bias, particularly for qualitative features. One study indicated that the patient being told to ‘return if unwell’ (22.7%) and being seen faster after returning to the ED (12.5%) were associated with ED revisit 21 ; however, this information could not be obtained from medical records. Third, the patients in this study were those who had both the index and return ED visit in our hospital.…”

Section: Discussionmentioning

confidence: 99%

Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study

Sung,

Ho,

Fan

et al. 2024

BMJ Health Care Inform

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BackgroundHigh-risk emergency department (ED) revisit is considered an important quality indicator that may reflect an increase in complications and medical burden. However, because of its multidimensional and highly complex nature, this factor has not been comprehensively investigated. This study aimed to predict high-risk ED revisit with a machine-learning (ML) approach.MethodsThis 3-year retrospective cohort study assessed adult patients between January 2019 and December 2021 from National Taiwan University Hospital Hsin-Chu Branch with high-risk ED revisit, defined as hospital or intensive care unit admission after ED return within 72 hours. A total of 150 features were preliminarily screened, and 79 were used in the prediction model. Deep learning, random forest, extreme gradient boosting (XGBoost) and stacked ensemble algorithm were used. The stacked ensemble model combined multiple ML models and performed model stacking as a meta-level algorithm. Confusion matrix, accuracy, sensitivity, specificity and area under the receiver operating characteristic curve (AUROC) were used to evaluate performance.ResultsAnalysis was performed for 6282 eligible adult patients: 5025 (80.0%) in the training set and 1257 (20.0%) in the testing set. High-risk ED revisit occurred for 971 (19.3%) of training set patients vs 252 (20.1%) in the testing set. Leading predictors of high-risk ED revisit were age, systolic blood pressure and heart rate. The stacked ensemble model showed more favourable prediction performance (AUROC 0.82) than the other models: deep learning (0.69), random forest (0.78) and XGBoost (0.79). Also, the stacked ensemble model achieved favourable accuracy and specificity.ConclusionThe stacked ensemble algorithm exhibited better prediction performance in which the predictions were generated from different ML algorithms to optimally maximise the final set of results. Patients with older age and abnormal systolic blood pressure and heart rate at the index ED visit were vulnerable to high-risk ED revisit. Further studies should be conducted to externally validate the model.

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Section: Discussionmentioning

confidence: 99%

Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study

Sung,

Ho,

Fan

et al. 2024

BMJ Health Care Inform

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“…Theoretical scaffolding encompasses foregrounding a study with a particular position and is informed by existing literature and a relevant disciplinary orientation (Thorne, 2016). Scaffolding for this study was informed by a published literature review on the return patient population (Hutchinson et al, 2019), a cross-sectional study of return visits (Hutchinson et al, 2019(Hutchinson et al, , 2021, a staff survey reporting perspectives on return visits (Hutchinson et al, 2022) and the authors' disciplinary knowledge and local familiarity with the study site.…”

Section: Designmentioning

confidence: 99%

“…The most common reasons for return, evident in ED clinical notes, are related to disease progression or ongoing symptoms (Hutchinson et al, 2022). Other studies that include nursing, medical and clerical perspectives on the reasons why patients return unplanned to the ED report that in addition to clinical deterioration, a perceived gap in initial or subsequent care, or a breakdown in communication with the clinician at the initial visit, may also contribute to return (Hutchinson et al, 2022). Few studies report directly on the perspectives of returning patients about their return visit to ED, and these studies are predominantly from the United States of America (USA) (Hutchinson et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Monitoring the rate of return visits is a key performance indicator used across Australia to measure quality of care provided in the ED but does not capture the reasons why patients return. Several studies report clinician perspectives on contributing factors to return visits, but these are generally speculative and are often informed by reviews of clinical notes written by ED physicians and nurses (Hutchinson et al, 2022). The most common reasons for return, evident in ED clinical notes, are related to disease progression or ongoing symptoms (Hutchinson et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Several studies report clinician perspectives on contributing factors to return visits, but these are generally speculative and are often informed by reviews of clinical notes written by ED physicians and nurses (Hutchinson et al, 2022). The most common reasons for return, evident in ED clinical notes, are related to disease progression or ongoing symptoms (Hutchinson et al, 2022). Other studies that include nursing, medical and clerical perspectives on the reasons why patients return unplanned to the ED report that in addition to clinical deterioration, a perceived gap in initial or subsequent care, or a breakdown in communication with the clinician at the initial visit, may also contribute to return (Hutchinson et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Patients' experiences and reasons for unplanned return visits to the emergency department: A qualitative study

Hutchinson

Curtis

McCloughen

2023

Journal of Advanced Nursing

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Aims The aim of this study was to explore the reasons for and experiences of patients who make an unplanned return visit to the emergency department. Design This study forms the qualitative phase of a larger explanatory sequential mixed methods study and is informed by interpretive description. The paper was prepared using the consolidated criteria for reporting qualitative research. Methods Semi‐structured patient interviews were conducted over a 3‐month period (July–September 2021). Data were analysed using reflexive thematic analysis. Results Interviews from 13 participants generated findings related to experiences at and following their initial visit that contributed to their decision to return to the emergency department. Four themes were developed: (1) Patients experience barriers to feeling heard and having their concerns addressed; (2) Patients have little choice but to place their trust in clinicians; (3) Patients unexpectedly experience persistent symptoms which cannot be managed at home; and (4) Patients develop a sense of urgency about having their condition treated. Conclusion A negative experience at the initial ED visit may have dual conflicting impacts. It can contribute to patients' perceived need for a return visit because they are ill‐equipped to manage their condition at home, and it can also contribute to their initial reluctance to return to the ED when symptoms persist. Nurses and other clinicians working in ED need to actively build patient's experiential trust through clear communication, timely consultation and shared decision‐making at discharge, which in turn can increase patient's confidence and capability to self‐manage their condition. This study adds to the current body of literature about return visits by highlighting that a more positive experience of ED may assist patients to make better‐informed decisions about when and how to seek treatment and minimize unnecessary and unplanned return visits. Whilst not an intended topic for exploration in this study, the COVID‐19 pandemic influenced patients' experiences at both initial and return ED visits and limited their ability to access primary healthcare options. These experiences contributed to patients' decisions to make a return visit.

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Characteristics of patients who return unplanned to the ED, and factors that contribute to their decision to return: Integrated results from an explanatory sequential mixed methods inquiry

Hutchinson,

Curtis,

McCloughen

2024

Australasian Emergency Care

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Clinician perspectives on reasons for, implications and management of unplanned patient returns to the Emergency Department: A descriptive study

Cited by 4 publications

References 41 publications

Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study

Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study

Patients' experiences and reasons for unplanned return visits to the emergency department: A qualitative study

Characteristics of patients who return unplanned to the ED, and factors that contribute to their decision to return: Integrated results from an explanatory sequential mixed methods inquiry

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