OBJECTIVE: Inpatient length of stay (LOS) is an important measure of hospital activity,
health care resource consumption, and patient acuity. This research work aims at …

Objectives Evaluating whether future studies to develop prediction models for early
readmissions based on health insurance claims data available at the time of a …

Objective The study sought to evaluate the expected clinical utility of automatable prediction
models for increasing goals-of-care discussions (GOCDs) among hospitalized patients at …

Background: Electronic health records (EHRs) offer the opportunity to transform quality
improvement by using clinical data for comparing hospital performance without the burden …

Background General medical wards admit high-risk patients. Artificial intelligence algorithms
can use big data for developing models to assess patients' risk stratification. The aim of this …

Urban living in modern large cities has significant adverse effects on health, increasing the
risk of several chronic diseases. We focus on the two leading clusters of chronic diseases …

Objective Hospital capacity management depends on accurate real-time estimates of
hospital-wide discharges. Estimation by a clinician requires an excessively large amount of …

Objective This study aimed to assess the performance improvement for machine learning-
based hospital length of stay (LOS) predictions when clinical signs written in text are …

Objectives: The study sought to derive and validate risk-prediction tools from a large
nationwide registry linked with Medicare claims data. Background: Few clinical models have …

Background The electronic medical record (EMR) is one of the most promising components
of health information technology. However, the overall impact of EMR adoption on outcomes …