AIMC Topic: Patient Readmission

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Development of Electronic Health Record-Based Prediction Models for 30-Day Readmission Risk Among Patients Hospitalized for Acute Myocardial Infarction.

JAMA network open Jan 4, 2021
IMPORTANCE: In the US, more than 600 000 adults will experience an acute myocardial infarction (AMI) each year, and up to 20% of the patients will be rehospitalized within 30 days. This study highlights the need for consideration of calibration in th...
Retrospective Studies Electronic Health Records Female Hospitalization Humans Machine Learning Aged Male United States Patient Readmission Predictive Value of Tests Calibration Myocardial Infarction
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Reply: In machine learning, the devil is in the details.

The Journal of thoracic and cardiovascular surgery Nov 15, 2020
Humans Machine Learning Patient Readmission
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Machine-learning algorithms for predicting hospital re-admissions in sickle cell disease.

British journal of haematology Nov 10, 2020
Reducing preventable hospital re-admissions in Sickle Cell Disease (SCD) could potentially improve outcomes and decrease healthcare costs. In a retrospective study of electronic health records, we hypothesized Machine-Learning (ML) algorithms may out...
Humans Patient Readmission Young Adult Adult Male Adolescent Anemia, Sickle Cell Middle Aged Risk Assessment Machine Learning Algorithms Female Hospitalization Aged Aged, 80 and over
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Predicting preventable hospital readmissions with causal machine learning.

Health services research Oct 30, 2020
OBJECTIVE: To assess both the feasibility and potential impact of predicting preventable hospital readmissions using causal machine learning applied to data from the implementation of a readmissions prevention intervention (the Transitions Program).
Female Risk Factors Aged Risk Assessment Severity of Illness Index Male Middle Aged Machine Learning Retrospective Studies Electronic Health Records Humans Continuity of Patient Care Patient Readmission Health Services Research Diagnostic Techniques and Procedures Health Status Age Factors Sex Factors
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Combining structured and unstructured data for predictive models: a deep learning approach.

BMC medical informatics and decision making Oct 29, 2020
BACKGROUND: The broad adoption of electronic health records (EHRs) provides great opportunities to conduct health care research and solve various clinical problems in medicine. With recent advances and success, methods based on machine learning and d...
Humans Neural Networks, Computer Deep Learning Patient Readmission Machine Learning Electronic Health Records
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The Use of Artificial Neural Network to Predict Surgical Outcomes After Inguinal Hernia Repair.

The Journal of surgical research Oct 21, 2020
BACKGROUND: Inguinal hernia repair is one of the most commonly performed surgical procedures. We developed and validated an artificial neural network (ANN) model for the prediction of surgical outcomes and the analysis of risk factors for inguinal he...
Elective Surgical Procedures Feasibility Studies Patient Readmission Hospital Mortality Logistic Models Treatment Outcome Quality Improvement Herniorrhaphy Hernia, Inguinal Young Adult Adult Male Postoperative Complications Adolescent Middle Aged Risk Assessment Risk Factors Aged Aged, 80 and over Humans Neural Networks, Computer Female
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How Good Is Machine Learning in Predicting All-Cause 30-Day Hospital Readmission? Evidence From Administrative Data.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research Sep 7, 2020
OBJECTIVES: Hospital readmission is a main cost driver for healthcare systems, but existing works often had poor or moderate predictive results. Although the available information differs in different studies, improving prediction is different from t...
Humans Machine Learning Patient Readmission Sensitivity and Specificity Quebec Male Middle Aged Logistic Models Algorithms Female Risk Factors
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Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital.

Applied clinical informatics Sep 2, 2020
BACKGROUND: Hospital readmissions are a key quality metric, which has been tied to reimbursement. One strategy to reduce readmissions is to direct resources to patients at the highest risk of readmission. This strategy necessitates a robust predictiv...
Medical Informatics Risk Time Factors Humans Decision Support Systems, Clinical Machine Learning Hospitals Patient Readmission
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Machine learning and readmission: Do we need new methods to solve old problems?

The Journal of thoracic and cardiovascular surgery Aug 28, 2020
Humans Patient Readmission Machine Learning Algorithms
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REPLY: THE STANDARDIZATION AND AUTOMATION OF MACHINE LEARNING FOR BIOMEDICAL DATA.

The Journal of thoracic and cardiovascular surgery Aug 28, 2020
Reference Standards Machine Learning Patient Readmission Humans Automation
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