AIMC Topic: Patient Readmission
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Using Natural Language Processing in the LACE Index Scoring Tool to Predict Unplanned Trauma and Surgical Readmissions in South Africa.
World journal of surgery
Mar 9, 2025
BACKGROUND: Unplanned and potentially avoidable readmission within 30 days post discharge is a major financial burden.
Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study.
JMIR medical informatics
Mar 5, 2025
BACKGROUND: Unplanned readmissions increase unnecessary health care costs and reduce the quality of care. It is essential to plan the discharge care from the beginning of hospitalization to reduce the risk of readmission. Machine learning-based readm...
Using Machine Learning to Improve Readmission Risk in Surgical Patients in South Africa.
International journal of environmental research and public health
Feb 26, 2025
Unplanned readmission within 30 days is a major challenge both globally and in South Africa. The aim of this study was to develop a machine learning model to predict unplanned surgical and trauma readmission to a public hospital in South Africa from ...
Enhancing readmission prediction model in older stroke patients by integrating insight from readiness for hospital discharge: Prospective cohort study.
International journal of medical informatics
Feb 22, 2025
BACKGROUND: The 30-day hospital readmission rate is a key indicator of healthcare quality and system efficiency. This study aimed to develop machine-learning (ML) models to predict unplanned 30-day readmissions in older patients with ischemic stroke ...
Utilization of machine learning algorithm in the prediction of rehospitalization during one-year post traumatic spinal cord injury.
Spinal cord
Feb 15, 2025
STUDY DESIGN: Retrospective cohort study.
Preoperative anemia is an unsuspecting driver of machine learning prediction of adverse outcomes after lumbar spinal fusion.
The spine journal : official journal of the North American Spine Society
Jan 30, 2025
BACKGROUND CONTEXT: Preoperative risk assessment remains a challenge in spinal fusion operations. Predictive modeling provides data-driven estimates of postsurgical outcomes, guiding clinical decisions and improving patient care. Moreover, automated ...
The Adelaide Score: prospective implementation of an artificial intelligence system to improve hospital and cost efficiency.
ANZ journal of surgery
Jan 3, 2025
BACKGROUND: The Adelaide Score is an artificial intelligence system that integrates objective vital signs and laboratory tests to predict likelihood of hospital discharge.
Enhancing Clinical Decision Making by Predicting Readmission Risk in Patients With Heart Failure Using Machine Learning: Predictive Model Development Study.
JMIR medical informatics
Dec 31, 2024
BACKGROUND: Patients with heart failure frequently face the possibility of rehospitalization following an initial hospital stay, placing a significant burden on both patients and health care systems. Accurate predictive tools are crucial for guiding ...
Predicting the likelihood of readmission in patients with ischemic stroke: An explainable machine learning approach using common data model data.
International journal of medical informatics
Dec 26, 2024
BACKGROUND: Ischemic stroke affects 15 million people worldwide, causing five million deaths annually. Despite declining mortality rates, stroke incidence and readmission risks remain high, highlighting the need for preventing readmission to improve ...
Machine Learning Algorithms Exceed Comorbidity Indices in Prediction of Short-Term Complications After Hip Fracture Surgery.
The Journal of the American Academy of Orthopaedic Surgeons
Nov 19, 2024
BACKGROUND: Hip fractures are among the most morbid acute orthopaedic injuries often due to accompanying patient frailty. The purpose of this study was to determine the reliability of assessing surgical risk after hip fracture through machine learnin...
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