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

A clinical prediction model for safe early discharge of patients with an infection at the emergency department

BACKGROUND

Every hospital admission is associated with healthcare costs and a risk of adverse events. The need to identify patients who do not require hospitalization has emerged with the profound increase in hospitalization rates due to infectious diseases during the last decades, especially during the COVID-19 pandemic. This study aimed to identify predictors of safe early discharge (SED) in patients presenting to the emergency department (ED) with a suspected infection meeting the Systemic Inflammatory Response Syndrome (SIRS) criteria.

METHODS

We conducted a prospective cohort study on adult non-trauma patients with a suspected infection and at least two SIRS criteria. We defined SED as hospital discharge within 24 h (e.g. direct ED discharge or rapid ward discharge) without disease-related readmission to our hospital or death during the first seven days. A prediction model for SED was developed using multivariate logistic regression analysis and tested with k-fold cross-validation.

RESULTS

We included 1381 patients, of whom 1027 (74.4 %) were hospitalized for longer than 24 h or re-admitted within seven days and 354 (25.6 %) met SED criteria. Parameters associated with SED were relatively young age, absence of comorbidities, living independently, yellow or green triage urgency, lack of ambulance transport or general practitioner referral, normal clinical impression scores, and risk scores (i.e., qSOFA, PIRO, MEDS, NEWS, and SIRS), normal vital sign measurements and absence of kidney and respiratory failure. The model performance metrics showed an area under the curve of 0.824. The validation showed a minimal drop in performance and indicated a good fit.

CONCLUSION

We developed and validated a model to identify patients with an infection at the ED who can be safely discharged early.

Novel Discharge Center for Transition of Care in Vulnerable Emergency Department Treat and Release Patients

Introduction The majority of emergency department (ED) patients are discharged following evaluation and treatment. Most patients are recommended to follow up with a primary care provider (PCP) or specialist. However, there is considerable variation between providers and EDs in discharge process practices that might facilitate such follow-up (e.g., simply discharging patients with follow-up physician names/contact information vs. making appointments for patients). Patients who do not follow up with their PCPs or specialists are more likely to be readmitted within 30 days than those who do. Furthermore, vulnerable patients have difficulty arranging transitional care appointments due to poor health literacy, inadequate insurance, appointment availability, and self-efficacy. Our innovative ED discharge process utilizes an Emergency Department Discharge Center (EDDC) staffed by ED Care Coordinators and assists patients with scheduling post-discharge appointments to improve rates of follow-up with outpatient providers. This study describes the structure and activities of the EDDC, characterizes the EDDC patient population, and demonstrates the volume and specialties of appointments scheduled by EDDC Care Coordinators. The impact of the EDDC on operational metrics (72-hour returns, 30-day admissions, and length-of-stay [LOS]) and the impact of the EDDC on patient satisfaction are evaluated. Methods The Long Island Jewish Medical Center (LIJMC) EDDC is an intervention developed in July 2020 within a 583-bed urban hospital serving a racially, ethnically, and socio-economically diverse population, with many patients having limited access to healthcare. Data from the Emergency Medicine Service Line (EMSL), an ED Care Coordinator database, and manual chart review were collected from July 2020 to July 2021 to examine the impact of the EDDC on 72-hour returns, 30-day admissions, and Press Ganey's® "likelihood to recommend ED" score (a widely used patient satisfaction survey question). The EDDC pilot cohort was compared to non-EDDC discharged patients during the same period. Results In unadjusted analysis, EDDC patients were moderately less likely to return to the ED within 72 hours (5.3% vs. 6.5%; p = 0.0044) or be admitted within 30 days (3.4% vs. 4.2%). The program was particularly beneficial for uninsured and elderly patients. For both EDDC and non-EDDC patients, most revisits and 30-day admissions were for the same chief complaint as the index visit. The length-of-stay increased by ~10 minutes with no impact on satisfaction with ED visits. Musculoskeletal conditions (~20%) and specialties (~15%) were the most commonly represented. Approximately 10% of referrals were to obtain a PCP. Nearly 90% were to new providers or specialties. Most scheduled appointments occurred within a week.  Conclusion This novel EDDC program, developed to facilitate outpatient follow-up for discharged ED patients, produced a modest but statistically significant difference in 72-hour returns and 30-day admissions for patients with EDDC-scheduled appointments vs. those referred to outpatient providers using the standard discharge process. ED LOS increased by ~10 minutes for EDDC vs. non-EDDC patients, with no difference in satisfaction. Future analyses will investigate impacts on 72-hour returns, 30-day admissions, LOS, and satisfaction after adjusting for characteristics such as age, insurance, having a PCP, and whether the scheduled appointment was attended.

Characteristics of Emergency Department Patient Visits Referred for Follow-Up Medical Care After Discharge, National Hospital Ambulatory Medicare Care Survey-United States, 2018

Objective

To describe characteristics of a nationally representative sample of patient visits that ended with a referral for follow-up medical care after discharge from hospital emergency department (ED) visits.

Methods

We used 2018 National Hospital Ambulatory Medical Care Survey data to identify patient characteristics associated with higher rates of visits with referrals for follow-up medical care after ED discharge from nonfederal short-stay and general hospitals throughout the United States. Referral included categories of all disposition variables that indicated referral to a source of care consistent with the patient's clinical condition at ED discharge.

Results

Approximately 97 million of 130 million visits (29 700/100 000 US resident population) were referred for follow-up medical care during 2018. Visit referral rates were higher among females (33 100) than among males (26 300/100 000 population); higher among Black patients (61 700) than among White patients (25 600/100 000 population); highest in the South (33 200/100 000 population); and similar rates in Nonmetropolitan (29 900/100 000 population) and Metropolitan Statistical Areas (30 200/100 000 population). Visit referral rates were higher for patients with Medicaid/Children's Health Insurance Program (CHIP) (66 900) than those with Medicare (31 500) or private insurance (14 000/100 000 population). Abnormal clinical findings and injuries were the discharge diagnoses most often referred for follow-up medical care.

Conclusion

Higher visit referral rates were observed among female sex, non-Hispanic Black race, Medicaid/CHIP, abnormal clinical findings, and injuries. Future studies might reveal reasons that prompted higher referral rates among various patients' characteristics.

A Scoping Review of Emergency Department Discharge Risk Stratification

INTRODUCTION

Although emergency department (ED) discharge presents patient-safety challenges and opportunities, the ways in which EDs address discharge risk in the general ED population remains disparate and largely uncharacterized. In this study our goal was to conduct a review of how EDs identify and target patients at increased risk at time of discharge.

METHODS

We conducted a literature search to explore how EDs assess patient risk upon discharge, including a review of PubMed and gray literature. After independently screening articles for inclusion, we recorded study characteristics including outcome measures, patient risk factors, and tool descriptions. Based on this review and discussion among collaborators, major themes were identified.

RESULTS

PubMed search yielded 384 potentially eligible articles. After title and abstract review, we screened 235 for potential inclusion. After full text and reference review, supplemented by Google Scholar and gray literature reviews, we included 30 articles for full review. Three major themes were elucidated: 1) Multiple studies include retrospective risk assessment, whereas the use of point-of-care risk assessment tools appears limited; 2) of the point-of-care tools that exist, inputs and outcome measures varied, and few were applicable to the general ED population; and 3) while many studies describe initiatives to improve the discharge process, few describe assessment of post-discharge resource needs.

CONCLUSION

Numerous studies describe factors associated with an increased risk of readmission and adverse events after ED discharge, but few describe point-of-care tools used by physicians for the general ED population. Future work is needed to investigate standardized tools that assess ED discharge risk and patients' needs upon ED discharge.