Web22 mrt. 2024 · The objectives of this study were to (1) determine the incidence and causes of 30-day readmission rates for patients with diabetes listed as either the primary … Web12 feb. 2016 · Machine learning methods have been leveraged on public health data to build a system for identifying diabetic patients facing a high risk of future readmission. …
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Web21 mrt. 2024 · The rate of 30-day readmissions primarily due to diabetic ketoacidosis was 20.2 percent, involving 18,553 patients, he reported. Women were more likely than men … Web8 jan. 2024 · January 08, 2024 - Providers understand that high hospital readmission rates spell trouble for patient outcomes. But excessive rates may also threaten a hospital's financial health, especially in a value-based reimbursement environment. Readmissions are already one of the costliest episodes to treat, with hospital costs reaching $41.3 …
Web2 mrt. 2024 · Download Citation On Mar 2, 2024, N. Satheesh Kumar and others published Prediction of Diabetic Patients with High Risk of Readmission using Smart Decision Support Framework Find, read and ... The patients’ general demographic data, such as sex, age, and race as well as the clinical records of drug use, clinical operations, admission times, and others were analyzed as shown below. Nearly half (46.15%) of the total patients were male, while the majority of patients (76.49%) were white Americans … Meer weergeven The data analyzed were acquired from the Health Facts Database (Cerner Corporation, US), which includes 130 hospitalized … Meer weergeven At the initial stage of the clinical data analysis modeling, there are often hundreds of characteristic variables but only a few … Meer weergeven Before the analysis of readmission, the overall analysis and data preprocessing performed of the hospitalization conditions in the dataset … Meer weergeven In this study, three ML models were selected and compared. The random forest (RF) algorithm is a basic classification algorithm built by a decision tree (DT). … Meer weergeven
WebThe overall goal is to reduce the number of early hospital readmissions by identifying the key risk factors that cause hospital readmissions. This is especially important in Intensive Care Unit ... Predicting 30-Day Hospital … Web8 mrt. 2024 · Abstract. Background. American hospitals spent over $41 billion on diabetic patients in 2011 who got readmitted within 30 days of discharge [1]. Researchers have attempted to find predictors of readmission rate [2] and among other factors, medication change upon admission has also been shown to be associated with lower readmission …
WebObjective: To assess factors predictive of all-cause, 30 day hospital readmission among patients with type 2 diabetes in the United States. Methods: A retrospective, case-control …
Web17 feb. 2024 · Intensive care is a critical area of medicine having a multidisciplinary nature requiring all types of healthcare professionals. Given the critical environment of intensive care units (ICUs), the need to use information technologies, like decision support systems, to improve healthcare services and ICU management is evident. It is proven that … law johnsonWebVarious time frames are used for identifying readmissions: 48 hours, 1. 7 days, 2. 15 days, 3, 4. and 30 days after discharge of an initial stay. 5 , 6 7. ... among patients with Medicare, followed by patients with Medicaid, no insurance, and ... Diabetes mellitus with complications (6.9) Respiratory failure; insufficiency; arrest (adult) ... law journal rankingWeb2011, it was found that more 3 million patients were readmitted within 30 days from discharge date. In 2012, there were 23,700 cases of re-admissions due to unchecked diabetes alone costing around $251 million. I Although, identifying patients who are expected to be readmitted in 30 days of discharge is a complex task for hospitals. law johnWebThe prevalence of diabetes diagnoses is projected to increase from 9.1% of the U.S. population in 2014 to 13% in 2030 and 17% in 2060. 3 Approximately 90% to 95% of people with diabetes have... law journal ranking leeWebObjective To identify patient and hospital predictors of recurrent diabetic ketoacidosis (DKA) admissions in adults in the USA with type 1 diabetes, focusing on socioeconomic indicators. Research design and methods This cross-sectional study used the National Readmission Database to identify adult patients with type 1 diabetes admitted for DKA … law joint custodyWeb11 apr. 2024 · During the readmissions, 26,757 patients (79.1%) died, representing a cumulative in-hospital mortality of 47,945 ... (NHS) and follow for 1 year identifying all their readmissions to study readmission rates for CSD and mortality in readmissions. ... renal failure (39.5%), diabetes (34.8%), and valvular and rheumatic heart disease (32 ... law jones funeral home savanna illinoisWebPatient-facing mobile apps to treat high-need, high-cost populations: a scoping ... 2016. 43 * 2016: Identifying Challenges and Opportunities in Human-AI Collaboration in Healthcare. SY Park, PY Kuo, A Barbarin, E Kaziunas, A ... Predicting 30-day hospital readmissions using artificial neural networks with medical code embedding. W Liu, C ... law jones funeral savanna il