AIMC Topic: Patient Discharge

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Development of machine learning algorithms for prediction of discharge disposition after elective inpatient surgery for lumbar degenerative disc disorders.

Neurosurgical focus
OBJECTIVEIf not anticipated and prearranged, hospital stay can be prolonged while the patient awaits placement in a rehabilitation unit or skilled nursing facility following elective spine surgery. Preoperative prediction of the likelihood of postope...

An intelligent algorithm for optimizing emergency department job and patient satisfaction.

International journal of health care quality assurance
Purpose Resilience engineering, job satisfaction and patient satisfaction were evaluated and analyzed in one Tehran emergency department (ED) to determine ED strengths, weaknesses and opportunities to improve safety, performance, staff and patient sa...

Predicting Risk of 30-Day Readmissions Using Two Emerging Machine Learning Methods.

Studies in health technology and informatics
Decades-long research efforts have shown that Heart Failure (HF) is the most expensive diagnosis for hospitalizations and the most frequent diagnosis for 30-day readmissions. If risk stratification for readmission of HF patients could be carried out ...

Estimating a Bias in ICD Encodings for Billing Purposes.

Studies in health technology and informatics
ICD encoded diagnoses are a popular criterion for eligibility algorithms for study cohort recruitment. However, "official" ICD encoded diagnoses used for billing purposes are afflicted with a bias originating from legal issues. This work presents an ...

Comparison of Machine Learning Algorithms for the Prediction of Preventable Hospital Readmissions.

Journal for healthcare quality : official publication of the National Association for Healthcare Quality
A diverse universe of statistical models in the literature aim to help hospitals understand the risk factors of their preventable readmissions. However, these models are usually not necessarily applicable in other contexts, fail to achieve good discr...

A long journey to short abbreviations: developing an open-source framework for clinical abbreviation recognition and disambiguation (CARD).

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The goal of this study was to develop a practical framework for recognizing and disambiguating clinical abbreviations, thereby improving current clinical natural language processing (NLP) systems' capability to handle abbreviations in clin...

Uncovering Hidden Topics in Hong Kong Clinical Research Through Hospital Authority Convention Publications.

Studies in health technology and informatics
Uncovering clinical research trends allows us to understand the direction of healthcare services and is essential for longer-term healthcare planning. The Hospital Authority Convention is a mainstream annual healthcare conference that gathers up-to-d...

Improving Prediction of Suicide and Accidental Death After Discharge From General Hospitals With Natural Language Processing.

JAMA psychiatry
IMPORTANCE: Suicide represents the 10th leading cause of death across age groups in the United States (12.6 cases per 100 000) and remains challenging to predict. While many individuals who die by suicide are seen by physicians before their attempt, ...

Design, development and first validation of a transcoding system from ICD-9-CM to ICD-10 in the IT.DRG Italian project.

Studies in health technology and informatics
In Italy, ICD-9-CM is currently used for coding health conditions at hospital discharge, but ICD-10 is being introduced thanks to the IT-DRG Project. In this project, one needed component is a set of transcoding rules and associated tools for easing ...