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Patient Readmission

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Patient Coded Severity and Payment Penalties Under the Hospital Readmissions Reduction Program: A Machine Learning Approach.

Medical care Nov 1, 2020
OBJECTIVE: The objective of this study was to examine variation in hospital responses to the Centers for Medicare and Medicaid's expansion of allowable secondary diagnoses in January 2011 and its association with financial penalties under the Hospita...
Severity of Illness Index United States Medicare Humans Machine Learning Policy Centers for Medicare and Medicaid Services, U.S. Insurance Claim Review Hospital Bed Capacity Patient Readmission Clinical Coding Diagnosis-Related Groups
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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
Patient Readmission Humans Machine Learning Cohort Studies
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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.
Humans Machine Learning Male Risk Factors Middle Aged Aged Cohort Studies Patient Discharge Adult Patient Readmission Retrospective Studies Spinal Diseases Female
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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.
Patient Discharge Patient Readmission Postoperative Period Inpatients Spinal Fusion Lumbar Vertebrae Adult Male Middle Aged Female Postoperative Complications Risk Factors Comorbidity Aged Case-Control Studies Humans Databases, Factual Machine Learning Retrospective Studies
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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 Humans Patient Readmission Machine Learning Patient Safety
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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 Machine Learning Demography Logistic Models Patient Readmission
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Machine Learning Comes of Age: Local Impact versus National Generalizability.

Anesthesiology May 1, 2020
Algorithms Forecasting Patient Readmission Machine Learning Humans Data Analysis
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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...
Humans Machine Learning Hospitalization Emergency Service, Hospital 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.
Female Humans Patient Readmission Male Retrospective Studies Risk Factors Machine Learning Electronic Health Records Nursing Care Aged Data Analysis Middle Aged Risk Management
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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...
Patient Readmission Electronic Health Records Humans Unified Medical Language System Natural Language Processing Machine Learning Vocabulary, Controlled Data Mining
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