AIMC Topic: Patient Readmission

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Commentary: Machine Learning With Feature Domains Elucidates Candidate Drivers of Hospital Readmission Following Spine Surgery in a Large Single-Center Patient Cohort.

Neurosurgery Sep 15, 2020
Humans Machine Learning Cohort Studies Patient Readmission
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Machine Learning With Feature Domains Elucidates Candidate Drivers of Hospital Readmission Following Spine Surgery in a Large Single-Center Patient Cohort.

Neurosurgery Sep 15, 2020
BACKGROUND: Unplanned hospital readmissions constitute a significant cost burden in healthcare. Identifying factors contributing to readmission risk presents opportunities for actionable change to reduce readmission rates.
Risk Factors Aged Adult Machine Learning Retrospective Studies Female Patient Discharge Patient Readmission Spinal Diseases Male Middle Aged Cohort Studies Humans
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Machine Learning for Predictive Modeling of 90-day Readmission, Major Medical Complication, and Discharge to a Facility in Patients Undergoing Long Segment Posterior Lumbar Spine Fusion.

Spine Aug 15, 2020
STUDY DESIGN: Retrospective case control study.
Female Risk Factors Aged Databases, Factual Retrospective Studies Postoperative Complications Comorbidity Case-Control Studies Adult Male Middle Aged Humans Machine Learning Postoperative Period Lumbar Vertebrae Patient Discharge Patient Readmission Inpatients Spinal Fusion
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Comparison of Machine Learning Algorithms for Classifying Adverse-Event Related 30-Day Hospital Readmissions: Potential Implications for Patient Safety.

Studies in health technology and informatics Jun 26, 2020
Studies in the last decade have focused on identifying patients at risk of readmission using predictive models, in an objective to decrease costs to the healthcare system. However, real-time models specifically identifying readmissions related to hos...
Hospitals Patient Readmission Machine Learning Patient Safety Humans
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Comparison of Unplanned 30-Day Readmission Prediction Models, Based on Hospital Warehouse and Demographic Data.

Studies in health technology and informatics Jun 16, 2020
Anticipating unplanned hospital readmission episodes is a safety and medico-economic issue. We compared statistics (Logistic Regression) and machine learning algorithms (Gradient Boosting, Random Forest, and Neural Network) for predicting the risk of...
Reproducibility of Results Logistic Models Patient Readmission Demography Machine Learning
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Machine Learning Comes of Age: Local Impact versus National Generalizability.

Anesthesiology May 1, 2020
Humans Machine Learning Data Analysis Forecasting Algorithms Patient Readmission
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Machine Learning Prediction of Postoperative Emergency Department Hospital Readmission.

Anesthesiology May 1, 2020
BACKGROUND: Although prediction of hospital readmissions has been studied in medical patients, it has received relatively little attention in surgical patient populations. Published predictors require information only available at the moment of disch...
Machine Learning Hospitalization Emergency Service, Hospital Humans Patient Discharge Patient Readmission
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Leveraging Electronic Health Records and Machine Learning to Tailor Nursing Care for Patients at High Risk for Readmissions.

Journal of nursing care quality Jan 1, 2020
BACKGROUND: Electronic health record-derived data and novel analytics, such as machine learning, offer promising approaches to identify high-risk patients and inform nursing practice.
Middle Aged Risk Management Patient Readmission Machine Learning Nursing Care Data Analysis Humans Risk Factors Retrospective Studies Electronic Health Records Aged Female Male
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Development and application of a high throughput natural language processing architecture to convert all clinical documents in a clinical data warehouse into standardized medical vocabularies.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: Natural language processing (NLP) engines such as the clinical Text Analysis and Knowledge Extraction System are a solution for processing notes for research, but optimizing their performance for a clinical data warehouse remains a challen...
Natural Language Processing Data Mining Patient Readmission Humans Machine Learning Electronic Health Records Unified Medical Language System Vocabulary, Controlled
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Machine Learning-based Risk of Hospital Readmissions: Predicting Acute Readmissions within 30 Days of Discharge.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
The objective of this study was to design and develop a 30-day risk of hospital readmission predictive model using machine learning techniques. The proposed risk of readmission predictive model was then validated with the two most commonly used risk ...
Length of Stay Retrospective Studies Humans Patient Discharge Logistic Models Risk Factors Machine Learning Patient Readmission Comorbidity Emergency Service, Hospital
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