Thirty-day hospital readmission rate amongst older adults correlates with an increased number of medications, but not with Beers medications

Objective The objective is to determine the 30-day hospital readmission rate following a hospitalization due to pediatric lupus nephritis of recent onset and characterize the risk factors associated with these early readmissions. Methods The study included 76 children hospitalized from 01/01/2008 to 4/30/2017 due to a new diagnosis of lupus nephritis. We calculated the 30-day hospital readmission rate and compared the characteristics of the patients that were readmitted to patients that were not readmitted using univariable and multivariable analysis. Results The 30-day readmission rate was 17.1%. Factors that predicted hospital readmission in unavailable analysis were male gender (38.5 vs 14.3%, p = 0.04), not receiving pulse steroids (30.8 vs 3.2%, p = < .001), receiving diuretic treatment (69.2 vs 34.9%, p = .02), receiving albumin infusions (46.2 vs 12.7%, p = .004), stage 2 hypertension on day one of admission (76.9 vs 41.3%, p = .02), a higher white blood cell count on discharge (13.7 × 103/mm3 vs 8.8 × 103/mm 3 , p = .023), need for non-angiotensin converting enzyme (ACE) antihypertensive drugs (76.9 vs 46%, p = .042), and being discharged on nonsteroidal anti-inflammatory drugs (NSAIDs) (23.1 vs 4.8%, p = .025). Multivariable analysis demonstrated an increased risk of readmission for patients not treated with intravenous pulse methylprednisolone (IVMP) (OR = 17.5 (1.81–168.32) p = .013), and for those who required intravenous albumin assisted diuresis for hypervolemia (OR=6.25 (1.29–30.30) p = .022). Conclusion In all, 17% of children hospitalized due to new onset lupus nephritis were readmitted within 30 days of discharge. Absence of IVMP and receiving intravenous albumin assisted diuresis during initial hospitalization increase the risk of early readmission in new onset pediatric lupus nephritis.

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Predictive analytics for 30-day hospital readmissions

Mathematical Foundations of Computing ◽

10.3934/mfc.2021035 ◽

2021 ◽

Vol 0 (0) ◽

pp. 0

Author(s):

Lu Xiong ◽

Tingting Sun ◽

Randall Green

Keyword(s):

Hospital Readmission ◽

Readmission Rate ◽

Hospital Admissions ◽

Predictive Analytics ◽

Hospital Readmissions ◽

Day Hospital ◽

Process Data ◽

Data Set ◽

Hospital Readmission Rate ◽

The Cost

<p style='text-indent:20px;'>The 30-day hospital readmission rate is the percentage of patients who are readmitted within 30 days after the last hospital discharge. Hospitals with high readmission rates would have to pay penalties to the Centers for Medicare & Medicaid Services (CMS). Predicting the readmissions can help the hospital better allocate its resources to reduce the readmission rate. In this research, we use a data set from a hospital in North Carolina during the years from 2011 to 2016, including 71724 hospital admissions. We aim to provide a predictive model that can be helpful for related entities including hospitals, health insurance actuaries, and Medicare to reduce the cost and improve the clinical outcome of the healthcare system. We used R to process data and applied clustering, generalized linear model (GLM) and LASSO regressions to predict the 30-day readmissions. It turns out that the patient's age is the most important factor impacting hospital readmission. This research can help hospitals and CMS reduce costly readmissions.</p>

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Impact of oral anticoagulants on 30-day readmission: a study from a single academic centre

BMJ evidence-based medicine ◽

10.1136/bmjebm-2018-111026 ◽

2018 ◽

Vol 24 (1) ◽

pp. 10-14 ◽

Cited By ~ 3

Author(s):

Mukul Bhattarai ◽

Tamer Hudali ◽

Robert Robinson ◽

Mohammad Al-Akchar ◽

Carrie Vogler ◽

...

Keyword(s):

Logistic Regression ◽

Risk Factor ◽

Length Of Stay ◽

Hospital Readmission ◽

Readmission Rate ◽

Warfarin Therapy ◽

Oral Anticoagulants ◽

Emergency Department Visits ◽

Day Hospital ◽

The Impact

Researchers are extensively searching for modifiable risk factors including high-risk medications such as anticoagulation to avoid rehospitalisation. The influence of oral anticoagulant therapy on hospital readmission is not known. We investigated the impact of warfarin and direct oral anticoagulants (DOACs) on all cause 30-day hospital readmission retrospectively in an academic centre. We study the eligible cohort of 1781 discharges over 2-year period. Data on age, gender, diagnoses, 30-day hospital readmission, discharge medications and variables in the HOSPITAL score (Haemoglobin level at discharge, Oncology at discharge, Sodium level at discharge, Procedure during hospitalisation, Index admission, number of hospital Admissions, Length of stay) and LACE index (Length of stay, Acute/emergent admission, Charlson comorbidity index score, Emergency department visits in previous 6 months), which have higher predictability for readmission were extracted and matched for analysis. Warfarin was the most common anticoagulant prescribed at discharge (273 patients) with a readmission rate of 20% (p<0.01). DOACs were used by 94 patients at discharge with a readmission rate of 4% (p=0.219). Multivariate logistic regression showed an increased risk of readmission with warfarin therapy (OR 1.36, p=0.045). Logistic regression did not show DOACs to be a risk factor for hospital readmission. Our data suggests that warfarin therapy is a risk factor for all-cause 30-day hospital readmission. DOAC therapy is not found to be associated with a higher risk of hospital readmission. Warfarin anticoagulation may be an important target for interventions to reduce hospital readmissions.

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Age Based Trends for Unplanned Pediatric Rehospitalizations in the United States

10.1101/2021.11.13.21266306 ◽

2021 ◽

Author(s):

Nupur Amritphale ◽

Amod Amritphale ◽

Deepa Vasireddy ◽

Mansi Batra ◽

Mukul Sehgal ◽

...

Keyword(s):

Hospital Readmission ◽

Readmission Rate ◽

Age Groups ◽

The United States ◽

Unplanned Readmission ◽

Post Discharge ◽

Readmission Rates ◽

Discharge Care ◽

Hospital Readmission Rate ◽

Bowel Diseases

BACKGROUND AND OBJECTIVES: Hospital readmission rate helps to highlight the effectiveness of post- discharge care. There remains a paucity of plausible age based categorization especially for ages below one year for hospital readmission rates. METHODS: Data from 2017 Healthcare cost and utilization project National readmissions database was analyzed for ages 0-18 years. Logistic regression analysis was performed to identify predictors for unplanned early readmissions. RESULTS: We identified 5,529,389 inpatient pediatric encounters which were further divided into age group cohorts. The overall rate of readmissions was identified at 3.2%. Beyond infancy, the readmission rate was found to be 6.7%. Across all age groups, the major predictors of unplanned readmission were cancers, diseases affecting transplant recipients and sickle cell patients. It was determined that reflux, milk protein allergy, hepatitis and inflammatory bowel diseases were significant comorbidities leading to readmission. Anxiety, depression and suicidal ideation depicted higher readmission rates in those older than 13 years. Across ages 1-4 yrs, dehydration, asthma and bronchitis were negative predictors of unplanned readmission. CONCLUSIONS: Thirty-day unplanned readmissions remain a problem leading to billions of tax-payer-dollars lost per annum. Effective strategies for mandatory outpatient follow-up may help the financial aspect of care while also enhancing the quality of care.

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