Dataset Information

Discharge Against Medical Advice in Acute Ischemic Stroke: the Risk of 30-Day Unplanned Readmission.

ABSTRACT:

Background

Discharge against medical advice may be associated with more readmissions.

Objective

To evaluate DAMA in patients with acute ischemic stroke (AIS) and identify the relationship between DAMA and 30-day unplanned readmissions.

Design

A retrospective cohort study.

Participants

The National Readmission Database was used to identify inpatients with a primary diagnosis of AIS who were either discharged home or DAMA between 2010 and 2017 in the USA.

Measures

Demographic features, hospital type, comorbidities, stroke risk factors, severity indices, and treatments were compared between patients discharged routinely and DAMA. Multivariable logistic regression was used to evaluate predictors of DAMA, and a double robust inverse probability of treatment weighting method was used to assess the association between DAMA and 30-day unplanned readmissions.

Key results

Overall, 1,335,484 patients with AIS were included, of whom 2.09% (n = 27,892) were DAMA. The prevalence of DAMA in AIS patients increased from 1.65 in 2010 to 2.57% in 2017. The rates of 30-day unplanned readmissions for DAMA and non-DAMA patients were 16.81% and 7.78%, respectively. Patients with drug abuse, alcohol abuse, smoking, prior stroke, psychoses, and intravenous thrombolysis had greater odds of DAMA. DAMA was associated with all-cause readmissions (OR, 2.04; 95% CI, 2.01-2.07) and remained a strong predictor for transient ischemic attack/stroke-specific and cardiac-specific causes of readmissions.

Conclusions

Although the DAMA rate is low in AIS patients, DAMA is a risk factor for all-cause and recurrent stroke-specific readmissions. Future studies are needed to address issues around compliance and engagement with health care to reduce DAMA.

SUBMITTER: Lin Z

PROVIDER: S-EPMC8131431 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Discharge Against Medical Advice in Acute Ischemic Stroke: the Risk of 30-Day Unplanned Readmission.

Lin Zhen Z Han Hedong H Wu Cheng C Wei Xin X Ruan Yiming Y Zhang Chenxu C Cao Yang Y He Jia J

Journal of general internal medicine 20210208 5

<h4>Background</h4>Discharge against medical advice may be associated with more readmissions.<h4>Objective</h4>To evaluate DAMA in patients with acute ischemic stroke (AIS) and identify the relationship between DAMA and 30-day unplanned readmissions.<h4>Design</h4>A retrospective cohort study.<h4>Participants</h4>The National Readmission Database was used to identify inpatients with a primary diagnosis of AIS who were either discharged home or DAMA between 2010 and 2017 in the USA.<h4>Measures</ ...[more]

PMID: 33559060

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Project description:ImportanceHospital readmissions contribute to higher expenditures and may sometimes reflect suboptimal patient care. Individuals discharged against medical advice (AMA) are a vulnerable patient population and may have higher risk for readmission.ObjectivesTo determine odds of readmission and mortality for patients discharged AMA vs all others, to characterize patient and hospital-level factors associated with readmissions, and to quantify their overall cost burden.Design, setting, and participantsNationally representative, all-payer cohort study using the 2014 National Readmissions Database. Eligible index admissions were nonobstetrical/newborn hospitalizations for patients 18 years and older discharged between January 2014 and November 2014. Admissions were excluded if there was a missing primary diagnosis, discharge disposition, length of stay, or if the patient died during that hospitalization. Data were analyzed between January 2018 and June 2018.ExposuresDischarge AMA and non-AMA discharge.Main outcomes and measuresThirty-day all-cause readmission and in-hospital mortality rate.ResultsThere were 19.9 million weighted index admissions, of which 1.5% resulted in an AMA discharge. Within the AMA cohort, 85% were younger than 65 years, 63% were male, 55% had Medicaid or other (including uninsured) coverage, and 39% were in the lowest income quartile. Thirty-day all-cause readmission was 21.0% vs 11.9% for AMA vs non-AMA discharge (P < .001), and 30-day in-hospital mortality was 2.5% vs 5.6% (P < .001), respectively. Individuals discharged AMA were more likely to be readmitted to a different hospital compared with non-AMA patients (43.0% vs 23.9%; P < .001). Of all 30-day readmissions, 19.0% occurred within the first day after AMA discharge vs 6.1% for non-AMA patients (P < .001). On multivariable regression, AMA discharge was associated with a 2.01 (95% CI, 1.97-2.05) increased adjusted odds of readmission and a 0.80 (95% CI, 0.74-0.87) decreased adjusted odds of in-hospital mortality compared with non-AMA discharge. Nationwide readmissions after AMA discharge accounted for more than 400 000 inpatient hospitalization days at a total cost of $822 million in 2014.Conclusions and relevanceIndividuals discharged AMA have higher odds of 30-day readmission at significant cost to the health care system and lower in-hospital mortality rates compared with non-AMA patients. Patients discharged AMA are also more likely to be readmitted to different hospitals and to have earlier bounce-back readmissions, which may reflect dissatisfaction with their initial episode of care.

Project description:ObjectiveUnplanned hospital readmissions following surgical interventions are associated with adverse events and contribute to increasing health care costs. Despite numerous studies defining risk factors following lower extremity bypass surgery, evidence regarding readmission after endovascular interventions is limited. This study aimed to identify predictors of 30-day unplanned readmission following infrainguinal endovascular interventions.MethodsWe identified all patients undergoing an infrainguinal endovascular intervention in the targeted vascular module of the American College of Surgeons National Surgical Quality Improvement Program between 2012 and 2014. Perioperative outcomes were stratified by symptom status (chronic limb-threatening ischemia [CLI] vs claudication). Patients who died during index admission and those who remained in the hospital after 30 days were excluded. Indications for unplanned readmission related to the index procedure were evaluated. Multivariable logistic regression was used to identify preoperative and in-hospital (during index admission) risk factors of 30-day unplanned readmission.ResultsThere were 4449 patients who underwent infrainguinal endovascular intervention, of whom 2802 (63%) had CLI (66% tissue loss) and 1647 (37%) had claudication. The unplanned readmission rates for CLI and claudication patients were 16% (n = 447) and 6.5% (n = 107), respectively. Mortality after index admission was higher for readmitted patients compared with those not readmitted (CLI, 3.4% vs 0.7% [P < .001]; claudication, 2.8% vs 0.1% [P < .01]). Approximately 50% of all unplanned readmissions were related to the index procedure. Among CLI patients, the most common indication for readmission related to the index procedure was wound or infection related (42%), whereas patients with claudication were mainly readmitted for recurrent symptoms of peripheral vascular disease (28%). In patients with CLI, predictors of unplanned readmission included diabetes (odds ratio, 1.3; 95% confidence interval, 1.01-1.6), congestive heart failure (1.6; 1.1-2.5), renal insufficiency (1.7; 1.3-2.2), preoperative dialysis (1.4; 1.02-1.9), tibial angioplasty/stenting (1.3; 1.04-1.6), in-hospital bleeding (1.9; 1.04-3.5), in-hospital unplanned return to the operating room (1.9; 1.1-3.5), and discharge other than to home (1.5; 1.1-2.0). Risk factors for those with claudication were dependent functional status (3.5; 1.4-8.7), smoking (1.6; 1.02-2.5), diabetes (1.5; 1.01-2.3), preoperative dialysis (3.6; 1.6-8.3), procedure time exceeding 120 minutes (1.8; 1.1-2.7), in-hospital bleeding (2.9; 1.2-7.4), and in-hospital unplanned return to the operating room (3.4; 1.2-9.4).ConclusionsUnplanned readmission after endovascular treatment is relatively common, especially in patients with CLI, and is associated with substantially increased mortality. Awareness of these risk factors will help providers identify patients at high risk who may benefit from early surveillance, and prophylactic measures focused on decreasing postoperative complications may reduce the rate of readmission.

Project description:BackgroundReducing the 30-day unplanned hospital readmission rate is a goal for physicians and policymakers in order to improve quality of care. However, data on the readmission rate of critically ill patients in Japan and knowledge of the predictors associated with readmission are lacking. We investigated predictors associated with 30-day rehospitalization for medical and surgical adult patients separately.MethodsPatient data from 502 acute care hospitals with intensive care unit (ICU) facilities in Japan were retrospectively extracted from the Japanese Diagnosis Procedure Combination (DPC) database between April 2012 and February 2014. Factors associated with unplanned hospital readmission within 30 days of hospital discharge among medical and surgical ICU survivors were identified using multivariable logistic regression analysis.ResultsOf 486,651 ICU survivors, we identified 5583 unplanned hospital readmissions within 30 days of discharge following 147,423 medical hospitalizations (3.8% readmitted) and 11,142 unplanned readmissions after 339,228 surgical hospitalizations (3.3% readmitted). The majority of unplanned hospital readmissions, 60.9% of medical and 63.1% of surgical case readmissions, occurred within 15 days of discharge. For both medical and surgical patients, the Charlson comorbidity index score; category of primary diagnosis during the index admission (respiratory, gastrointestinal, and metabolic and renal); hospital length of stay; discharge to skilled nursing facilities; and having received a packed red blood cell transfusion, low-dose steroids, or renal replacement therapy were significantly associated with higher unplanned hospital readmission rates.ConclusionsFrom patient data extracted from a large Japanese national database, the 30-day unplanned hospital readmission rate after ICU stay was 3.4%. Further studies are required to improve readmission prediction models and to develop targeted interventions for high-risk patients.

Project description:BackgroundExisting readmission reduction solutions tend to focus on complementing inpatient care with enhanced care transition and postdischarge interventions. These solutions are initiated near or after discharge, when clinicians' impact on inpatient care is ending. Preventive intervention during hospitalization is an underexplored area that holds potential for reducing readmission risk. However, it is challenging to predict readmission risk at the early stage of hospitalization because few data are available.ObjectiveThe objective of this study was to build an early prediction model of unplanned 30-day hospital readmission using a large and diverse sample. We were also interested in identifying novel readmission risk factors and protective factors.MethodsWe extracted the medical records of 96,550 patients in 205 participating Cerner client hospitals across four US census regions in 2016 from the Health Facts database. The model was built with index admission data that can become available within 24 hours and data from previous encounters up to 1 year before the index admission. The candidate models were evaluated for performance, timeliness, and generalizability. Multivariate logistic regression analysis was used to identify readmission risk factors and protective factors.ResultsWe developed six candidate readmission models with different machine learning algorithms. The best performing model of extreme gradient boosting (XGBoost) achieved an area under the receiver operating characteristic curve of 0.753 on the development data set and 0.742 on the validation data set. By multivariate logistic regression analysis, we identified 14 risk factors and 2 protective factors of readmission that have never been reported.ConclusionsThe performance of our model is better than that of the most widely used models in US health care settings. This model can help clinicians identify readmission risk at the early stage of hospitalization so that they can pay extra attention during the care process of high-risk patients. The 14 novel risk factors and 2 novel protective factors can aid understanding of the factors associated with readmission.

Dataset Information

Discharge Against Medical Advice in Acute Ischemic Stroke: the Risk of 30-Day Unplanned Readmission.

Background

Objective

Design

Participants

Measures

Key results

Conclusions

Publications

Discharge Against Medical Advice in Acute Ischemic Stroke: the Risk of 30-Day Unplanned Readmission.

Similar Datasets

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