Factors associated with emergency department visit within 30 days after discharge

Where Patients Live Matter in Emergency Department Visits in Home Health Care: Rural/Urban Status and Neighborhood Socioeconomic Status

An increasing body of evidence highlights the importance of an individual's place of residence on their health and functional outcomes. This study is based on Outcome and Assessment Information Set data to assess the differences in emergency department visits among Medicare home health care patients by patients' residence location (rural/urban status and neighborhood socioeconomic status). Compared to urban patients, a disproportionately higher proportion of rural patients lived in more or most disadvantaged neighborhoods (83.9% vs. 41.3%). Using linear probability regression models, patients in rural areas (coefficient = .02, p < .001) and disadvantaged neighborhoods (less disadvantaged: coefficient = .02, p < .001; more disadvantaged: coefficient = .034, p < .001; most disadvantaged: coefficient = .042, p < .001) were more likely to experience emergency department visits. Policymakers should consider utilizing area-based target interventions to mitigate gaps in home health care. Also, given that the majority of rural patients reside in disadvantaged neighborhoods, neighborhood characteristics should be considered in addressing rural-urban disparities and improving home health care.

Factors associated with emergency room readmission after elective surgery for ovarian carcinoma

BACKGROUND

Hospital readmission is a quality metric of hospital care and has been studied in ovarian carcinoma, but its evaluation has several limitations. Also, emergency room (ER) readmission is considered an adverse effect because it represents patient costs. Therefore, our objective was to determine the rate of ER readmission, its causes, and associated factors.

METHODS

A retrospective study of 592 patients with ovarian carcinoma who underwent upfront surgery, neoadjuvant therapy, or surgery for recurrent disease. An analysis of factors associated with ER readmission, hospital readmission, and surgical complications was performed, including multivariate analysis to assess for case-mix factors.

RESULTS

Of 592 patients, the median age was 51 years, and the predominant type of treatment was the neoadjuvant approach (52.9%); 46% underwent upfront surgeries and six surgeries for recurrence. The ratio to ER readmission was 11.8% (70 patients), of whom 12 patients were admitted more than once. The factors associated with ER readmission were prolonged surgery, intraoperative bleeding, extended hospital stay, the time of the day when the surgery was performed, and post-surgical complications. The hospital readmissions were 4.2%, and the overall morbidity was 17.6%. In the multivariate analysis, the only factor associated with ER readmission was the presence of surgical complications (OR = 39.01). The factors independently associated with hospital readmission were the entrance to the intensive care unit (OR = 1.37), the presence of surgical complications (OR = 2.85), and ER readmission (OR = 1.45).

CONCLUSION

ER readmission is an adverse event representing the presence of symptoms/complications in patients. Evaluating the ER readmission independently of the readmission to the hospital is critical because it will allow modifying medical care behaviors to prevent patients from unnecessarily returning to the hospital after a hospital discharge to manage preventable medical problems.

TRIAL REGISTRATION

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Thirty-day hospital readmission prediction model based on common data model with weather and air quality data

Although several studies have attempted to develop a model for predicting 30-day re-hospitalization, few attempts have been made for sufficient verification and multi-center expansion for clinical use. In this study, we developed a model that predicts unplanned hospital readmission within 30 days of discharge; the model is based on a common data model and considers weather and air quality factors, and can be easily extended to multiple hospitals. We developed and compared four tree-based machine learning methods: decision tree, random forest, AdaBoost, and gradient boosting machine (GBM). Above all, GBM showed the highest AUC performance of 75.1 in the clinical model, while the clinical and W-score model showed the best performance of 73.9 for musculoskeletal diseases. Further, PM10, rainfall, and maximum temperature were the weather and air quality variables that most impacted the model. In addition, external validation has confirmed that the model based on weather and air quality factors has transportability to adapt to other hospital systems.

Predictors of Medication-Related Emergency Department Admissions Among Patients with Cardiovascular Diseases at Mbarara Regional Referral Hospital, South-Western Uganda

BACKGROUND

Medication-related emergency department admissions impose a huge and unnecessary burden on the healthcare system. We sought to determine the prevalence and predictors of medication-related emergency department admissions, among patients with cardiovascular diseases at Mbarara Regional Referral Hospital, Uganda.

METHODS

Institutional research ethics approval was secured to conduct a cross-sectional study at the Mbarara Regional Referral Hospital emergency department, between February and September, 2020. All eligible and consenting patients were enrolled in a consecutive manner after a preliminary diagnosis was made by the attending physician. Structured questionnaire interview and comprehensive medication history reviews were used to identify medication therapy problems, in collaboration with a resident physician present on duty. We used sequential categorization for medication therapy problem(s). Descriptive and logistic regression analyses were used to determine prevalence and predictors of medication-related emergency department admissions.

RESULTS

Out of the 128 patients interviewed, 105 (82%) patient admissions were associated with a medication therapy problem: ineffectiveness of drug therapy (53.3%, 56), medication non-adherence (42.9%, 45), and adverse drug reactions (3.8%, 4). Out of a total of 90 incidences of medication non-adherence, 34.4% (31/90) were due to lack of understanding of patient medication regimen, and 27.8% (25/90) due to unaffordable cost of medicines. Female gender (AOR = 4.31 [1.43, 13.03 at 95% CI]; P-value = 0.010]) and a history of tobacco use (AOR = 9.58 [1.14, 80.28 at 95% CI]; P-value = 0.037) were statistically significant predictors of medication-related emergency department admissions in adjusted analysis.

CONCLUSION

Four in five emergency department admissions were associated with medication-related causes, majorly due to ineffectiveness of drug therapy. Knowledge gap on patient medication regimens was the most prevalent cause for medication non-adherence. Female gender and previous or current tobacco use was an independent risk factor for medication-related admissions.

Emergency department visits and hospital readmissions in an Argentine health system

BACKGROUND AND GOAL OF STUDY

The scope of health in the Sustainable Development Goals is much broader than the Millennium Development Goals, spanning functions such as health-system access and quality of care. Hospital readmission rate and ED-visits within 30 days from discharge are considered low-cost quality indicators. This work assesses an indicator of quality of care in a tertiary referral hospital in Argentina, using data available from clinical records.

PURPOSE

To estimate the rate of ED-visits and the hospital readmission rate (HRR) after a first hospitalization (First-H), and to identify associated factors.

METHODS

This retrospective cohort included patients who had a First-H in Hospital Italiano de Buenos Aires between 2014-2015. Follow-up occurred from discharge until ED-visit, readmission, death, disaffiliation from health insurance, or 13 months. We present HRR at 30 days and ED-visits rate at 72 h, using the Cox proportional-hazards regression model to explore associated factors, and reporting adjusted hazard ratios (HR) with their respective 95 %CI.

RESULTS

The study comprised 10,598 hospitalizations (median age was 68 years). Of these, 5966 had at least one consultation to the ED during follow up, resulting in a 24 h rate of consultations to ED of 1.51 % (95 %CI 1.29-1.72); at 48 h 3.18 % (95 %CI 2.86-3.54); at 72 h 4.71 % (95 %CI 4.32-5.13). In multivariable models, factors associated for 72 h ED-visits were: age (aHR 1.06), male (aHR 1.14), Charlson Comorbidity Index (aHR 1.16), unscheduled hospitalization (aHR 1.39), prior consultation with the ED (aHR 1.08) and long hospital stay (aHR 1.39). Meanwhile, 2345 patients had at least one hospital readmission (98 % unscheduled), resulting a 24 h rate of 0.5 % (95 %CI 0.42-0.71), at 48 h 0.98 % (95 %CI 0.80-1.18), at 72 h 1.4 % (95 %CI 1.2-1.6); at 30 days 7.7 % (95 %CI 7.2-8.2); at 90 days 13 % (95 %CI 12.4-13.8); and one-year 22.5 % (95 %CI 21.7-23.4). Associated factors for HRR at 30 days were: age (HR 1.16), male (HR 1.09), Charlson comorbidities score (HR 1.27), social service requirement during First-H (HR 1.37), unscheduled First-H (HR 1.16), previous ED-visits (HR 1.03) and length of stay (HR 1.08).

CONCLUSION

Priorities efforts to improve must include greater attention to patients' readiness prior discharge, to explore causes of preventable readmissions, and better support for patient self-management.

Association between Inpatient Delirium and Hospital Readmission in Patients ≥ 65 Years of Age: A Retrospective Cohort Study

BACKGROUND

Delirium affects more than seven million hospitalized adults in the United States annually. However, its impact on postdischarge healthcare utilization remains unclear.

OBJECTIVE

To determine the association between delirium and 30-day hospital readmission.

DESIGN

A retrospective cohort study.

SETTING

A general community medical and surgical hospital.

PATIENTS

All adults who were at least 65 years old, without a history of delirium or alcohol-related delirium, and were hospitalized from September 2010 to March 2015.

MEASUREMENTS

The patients deemed at risk for or displaying symptoms of delirium were screened by nurses using the Confusion Assessment Method with a followup by a staff psychiatrist for a subset of screen-positive patients. Patients with delirium confirmed by a staff psychiatrist were compared with those without delirium. The primary outcome was the 30-day readmission rate. The secondary outcomes included emergency department (ED) visits 30 days postdischarge, mortality during hospitalization and 30 days postdischarge, and discharge location.

RESULTS

The cohort included 718 delirious patients and 7,927 nondelirious patients. Using an unweighted multivariable logistic regression, delirium was determined to be significantly associated with the increased odds of readmission within 30 days of discharge (odds ratio (OR): 2.60; 95% CI, 1.96-3.44; P < .0001). Delirium was also significantly (P < .0001) associated with ED visits within 30 days postdischarge (OR: 2.18; 95% CI: 1.77-2.69) and discharge to a facility (OR: 2.52; 95% CI: 2.09-3.01).

CONCLUSIONS

Delirium is a significant predictor of hospital readmission, ED visits, and discharge to a location other than home. Delirious patients should be targeted to reduce postdischarge healthcare utilization.

Receipt of Vasopressors Is Positively Associated With the Length of the Actively Dying Process in Hospitalization

BACKGROUND

End-of-life care is important in general hospitalization care. However, the clinical impact of using vasopressors on the length of the actively dying process is still controversial.

METHODS

We reviewed patients who were hospitalized in general wards and died before discharge. We classified the patients into 2 groups: those who received vasopressors (RVs) and those who did not receive vasopressors (NRV). We analyzed the factors associated with the length of hospital stay (LOS) and the length of the actively dying process.

RESULTS

In all, 745 participants, 10.01% of all admitted patients, were analyzed. Of them, 225 patients were RV group, and the remaining 520 were NRV group. Age and gender were comparable in the 2 groups. The use of vasopressors was associated with an admission diagnosis of sepsis and absence of Do-Not-Resuscitate consent and parenteral use of morphine. In multivariable analysis, a high Barthel index score, the absence of cancer and cardiopulmonary resuscitation (CPR), and no receipt of vasopressors were independent factors for LOS. For the length of the actively dying process, a longer duration of inotropic agent, the receipt of vasopressors, and the absence of CPR were independent factors.

CONCLUSION

In-hospital mortality is not uncommon during hospitalization in a general ward. The length of the actively dying process is extended by the use of vasopressors. Further prospective study is required for cautious evaluation of the pros and cons of using vasopressors at the end of life during hospitalization.