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Search Results for Predict
Abstract Number: 138
Hospital Medicine 2018; April 8-11; Orlando, Fla.
Background: Chronic Obstructive Pulmonary Disease (COPD) is a lung disease characterized by chronic, irreversible airway obstruction that can precipitate into acute exacerbations (AECOPD) of cough, dyspnea and sputum production, often requiring hospitalization. Hospital systems aiming to improve outcomes for patients with AECOPD are testing innovative approaches to care in the acute care setting. To enroll […]
Abstract Number: 154
Hospital Medicine 2020, Virtual Competition
Background: Increased risk of venous thromboembolism (VTE) has been noted among cancer patients as compared to non-cancer. Cancer associated thrombosis caused three folds increased hospitalizations, increased inpatient/outpatient medical and prescription claims, and increased total health care costs per patient. Our objective was to study demographic, clinical and laboratory risk factors for venous thromboembolism (VTE) among […]
Abstract Number: 163
SHM Converge 2024
Background: We conducted a pilot study in an acute care hospital and developed the Saga Fall Risk Model 2 (SFRM2), a fall prediction model comprising eight items: Bedriddenness rank, age, sex, emergency admission, admission to the neurosurgery department, history of falls, independence of eating, and use of hypnotics. Bedriddenness rank is an official scale of […]
Abstract Number: 176
Hospital Medicine 2019, March 24-27, National Harbor, Md.
Background: Patients hospitalized with hematologic malignancy are particularly vulnerable to infection. Clostridium difficile infection (CDI) has become the most common cause of healthcare-associated infections in U. S. hospitals, and the excess healthcare costs related to CDI are estimated to be as much as 4. 8 billion dollars for acute care facilities alone. We sought to […]
Abstract Number: 181
SHM Converge 2021
Background: Venous thromboembolism (VTE) is a significant cause of morbidity and mortality for hospitalized patients. There are approximately 900,000 new VTE events and 100,000 VTE-related deaths every year. In the United States, more deaths occur due to VTE than breast cancer, AIDS, and motor vehicle accidents combined. VTE are considered preventable events with appropriate prophylaxis; […]
Abstract Number: 181
Hospital Medicine 2020, Virtual Competition
Background: Despite the introduction of Early Warning Scores (EWSs), clinical deterioration (CD) remains an actual problem on the general ward. A next step to counter CD would be to intensify measurement from intermittent 8 hours to continuous measurements. This leads to big data sets of patient monitoring data with great potential. Use of advanced predictive […]
Abstract Number: 191
Hospital Medicine 2018; April 8-11; Orlando, Fla.
Background: Bronchiolitis is one of the leading causes of hospitalization in patients less than 2 years old. It can be a source of frustration for providers as numerous interventions that have been trialed throughout the years have not been shown to be effective. Albuterol is one such intervention as wheezing is a common clinical finding […]
Abstract Number: 230
SHM Converge 2023
Background: Several electronic health record (EHR) mortality prediction models have been developed to promote early goals of care discussions (GOCD) but only a few models were evaluated prospectively. We aimed to implement a real-time 30-day inpatient mortality prediction model previously developed at our facility and evaluate its effect on GOCD in seriously ill transferred patients. […]
Abstract Number: 231
Hospital Medicine 2017, May 1-4, 2017; Las Vegas, Nev.
Background: Sepsis is a leading cause of death among hospitalized patients. Early detection of sepsis has the potential to reduce mortality by facilitating timely evidence-based interventions. Past studies have used electronic health records (EHR) to trigger alerts at the onset of sepsis, or to predict general clinical deterioration. In this study we describe the impact […]
Abstract Number: 232
Hospital Medicine 2017, May 1-4, 2017; Las Vegas, Nev.
Background: Sepsis is a leading cause of mortality among hospitalized patients. Early detection and intervention reduces sepsis-related mortality. We implemented a novel early warning system (EWS 2.0) based on a machine-learning algorithm to prospectively identify patients with increased risk of severe sepsis or septic shock. Validation suggested excellent predictive characteristics, including a positive likelihood ratio […]