Dataset Information

Odds of return: a prospective study using provider assessment to predict short-term patient return visits to the emergency department.

ABSTRACT:

Objective

Previous studies have assessed patient-level characteristics associated with emergency department (ED) return visits, but none have used provider assessment. We prospectively investigate whether clinical providers could accurately predict ED return visits.

Methods

Prospective cohort study.

Setting

Single academically affiliated urban county hospital.

Participants

Discharged ED patients over a 14-month period with a provider assessment of the likelihood of patient return within 7 days of ED discharge.

Main outcome measures

The primary outcome of interest was a return visit to the ED within 7 days. Additional outcome measures included a return visit within 72 hours and a return visit resulting in admission. We also measured the accuracy of provider gestalt, and provide measures of sensitivity, specificity, predictive values, and likelihood ratios.

Results

Of the 11 922 ED discharges included in this study, providers expected 2116 (17.7%) to result in a return visit within 7 days. Providers were much more likely to perceive a return visit if the patient left against medical advice (OR: 5.97, 95% CI: 4.67 to 7.62), or was homeless (OR: 5.69, 95% CI: 5.14 to 6.29). Patients who actually returned were also more likely to be homeless, English speaking and to have left the ED against medical advice on the initial encounter. The strongest predictor of a return visit at both 72 hours and 7 days in multivariable modelling was provider assessment (OR: 3.77, 95% CI: 3.25 to 4.37; OR: 3.72, 95% CI: 3.29 to 4.21, respectively). Overall sensitivity and specificity of provider gestalt as a measure of patient return within 7 days were 47% and 87%, respectively. The positive and negative likelihood ratios were 3.51 and 0.61, respectively.

Conclusions

Clinician assessment was the strongest predictor of a return visit in this dataset. Clinician assessment may be used as a way to screen patients during the index visit and enrol them in efforts to decrease return visits.

SUBMITTER: Fruhan S

PROVIDER: S-EPMC8638466 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundUnscheduled emergency department return visits (EDRVs) are key indicators for monitoring the quality of emergency medical care. A high return rate implies that the medical services provided by the emergency department (ED) failed to achieve the expected results of accurate diagnosis and effective treatment. Older adults are more susceptible to diseases and comorbidities than younger adults, and they exhibit unique and complex clinical characteristics that increase the difficulty of clinical diagnosis and treatment. Older adults also use more emergency medical resources than people in other age groups. Many studies have reviewed the causes of EDRVs among general ED patients; however, few have focused on older adults, although this is the age group with the highest rate of EDRVs.ObjectiveThis aim of this study is to establish a model for predicting unscheduled EDRVs within a 72-hour period among patients aged 65 years and older. In addition, we aim to investigate the effects of the influencing factors on their unscheduled EDRVs.MethodsWe used stratified and randomized data from Taiwan's National Health Insurance Research Database and applied data mining techniques to construct a prediction model consisting of patient, disease, hospital, and physician characteristics. Records of ED visits by patients aged 65 years and older from 1996 to 2010 in the National Health Insurance Research Database were selected, and the final sample size was 49,252 records.ResultsThe decision tree of the prediction model achieved an acceptable overall accuracy of 76.80%. Economic status, chronic illness, and length of stay in the ED were the top three variables influencing unscheduled EDRVs. Those who stayed in the ED overnight or longer on their first visit were less likely to return. This study confirms the results of prior studies, which found that economically underprivileged older adults with chronic illness and comorbidities were more likely to return to the ED.ConclusionsMedical institutions can use our prediction model as a reference to improve medical management and clinical services by understanding the reasons for 72-hour unscheduled EDRVs in older adult patients. A possible solution is to create mechanisms that incorporate our prediction model and develop a support system with customized medical education for older patients and their family members before discharge. Meanwhile, a reasonably longer length of stay in the ED may help evaluate treatments and guide prognosis for older adult patients, and it may further reduce the rate of their unscheduled EDRVs.