Prediction of emergency department revisits using area-level social determinants of health measures and health information exchange information
JR Vest, O Ben-Assuli - International journal of medical informatics, 2019 - Elsevier
Introduction Interoperable health information technologies, like electronic health records
(EHR) and health information exchange (HIE), provide greater access to patient information …
(EHR) and health information exchange (HIE), provide greater access to patient information …
Prognostic utilization of models based on the APACHE II, APACHE IV, and SAPS II scores for predicting in-hospital mortality in emergency department
Background This study was designed to evaluate and compare the prognostic value of the
APACHE II, APACHE IV, and SAPSII scores for predicting in-hospital mortality in the ED on a …
APACHE II, APACHE IV, and SAPSII scores for predicting in-hospital mortality in the ED on a …
Acquisition of patients' EHR information under ED congestion–an empirical investigation
We examine the information acquisition process regarding a patient's status under
emergency department (ED) congestion conditions. We focus on two key information …
emergency department (ED) congestion conditions. We focus on two key information …
Recurrence of SARS-CoV-2 PCR positivity in COVID-19 patients: a single center experience and potential implications
ABSTRACT IMPORTANCE How to appropriately care for patients who become PCR-
negative for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still not …
negative for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still not …
Risk prediction and segmentation models used in the United States for assessing risk in whole populations: a critical literature review with implications for nurses' role …
Objective We sought to assess the current state of risk prediction and segmentation models
(RPSM) that focus on whole populations. Materials Academic literature databases (ie …
(RPSM) that focus on whole populations. Materials Academic literature databases (ie …
Predicting 72-hour emergency department revisits
G Pellerin, K Gao, L Kaminsky - The American journal of emergency …, 2018 - Elsevier
Objectives To develop a predictive model that hospitals or healthcare systems can use to
identify patients at high risk of revisiting the ED within 72 h so that appropriate interventions …
identify patients at high risk of revisiting the ED within 72 h so that appropriate interventions …
Too much information? The use of extraneous information to support decision‐making in emergency settings
Decision‐makers in emergency settings need to employ the breadth of evidence available
so as to inform critical judgments, yet the acute time pressure suggests that in some cases …
so as to inform critical judgments, yet the acute time pressure suggests that in some cases …
Predicting health-related social needs in Medicaid and Medicare populations using machine learning
J Holcomb, LC Oliveira, L Highfield, KO Hwang… - Scientific reports, 2022 - nature.com
Providers currently rely on universal screening to identify health-related social needs
(HRSNs). Predicting HRSNs using EHR and community-level data could be more efficient …
(HRSNs). Predicting HRSNs using EHR and community-level data could be more efficient …
Home care aides' observations and machine learning algorithms for the prediction of visits to emergency departments by older community-dwelling individuals …
JH Veyron, P Friocourt, O Jeanjean, L Luquel… - PLoS …, 2019 - journals.plos.org
Background Older individuals receiving home assistance are at high risk for emergency
visits and unplanned hospitalization. Anticipating their health difficulties could prevent these …
visits and unplanned hospitalization. Anticipating their health difficulties could prevent these …
[HTML][HTML] The association between emergency department revisit and elderly patients
DY Guo, KH Chen, IC Chen, KY Lu, YC Lin… - Journal of Acute …, 2020 - ncbi.nlm.nih.gov
Background Emergency department (ED) revisits may be associated with a higher
percentage of adverse events and increased costs. Our hospital is a university affiliation …
percentage of adverse events and increased costs. Our hospital is a university affiliation …