A5101678200- Healthcare Technology and Patient Monitoring
- Electronic Health Records Systems
- Sepsis Diagnosis and Treatment
- Patient Safety and Medication Errors
- Machine Learning in Healthcare
- Emergency and Acute Care Studies
- Clinical Reasoning and Diagnostic Skills
- Healthcare Operations and Scheduling Optimization
- Quality and Safety in Healthcare
- Respiratory Support and Mechanisms
- Palliative Care and End-of-Life Issues
- Intensive Care Unit Cognitive Disorders
- Healthcare Systems and Technology
- Cardiac, Anesthesia and Surgical Outcomes
- Family and Patient Care in Intensive Care Units
- Hospital Admissions and Outcomes
- Cardiac Arrest and Resuscitation
- Artificial Intelligence in Healthcare and Education
- Non-Invasive Vital Sign Monitoring
- COVID-19 Clinical Research Studies
- Health Sciences Research and Education
- Heart Failure Treatment and Management
- COVID-19 diagnosis using AI
- Hemodynamic Monitoring and Therapy
- Nursing Diagnosis and Documentation
Mayo Clinic in Arizona
2015-2024
Mayo Clinic
2015-2024
WinnMed
2013-2023
RELX Group (United States)
2023
Mayo Clinic in Florida
2010-2021
Sheba Medical Center
2017
Creative Research Enterprises (United States)
2016
Mater Misericordiae Hospital
2013
Maya Educational Foundation
2012
St. Luke's Hospital
2012
The care of critically ill patients generates large quantities data. Increasingly, these data are presented to the provider within an electronic medical record. manner in which organized and can impact on ability users synthesis that into meaningful information. objective this study was test hypothesis novel user interfaces, prioritize display high-value providers system-based packages, reduce task load, result fewer errors cognition compared with established interfaces do not.Randomized...
To identify whether delays in rapid response team activation contributed to worse patient outcomes (mortality and morbidity).Retrospective observational cohort study including all activations 2012.Tertiary academic medical center.All those 18 years old or older who had a call activated. Vital sign data were abstracted from individual electronic records for the 24 hours before took place. Patients considered have delayed if more than 1 hour passed between first appearance record of an...
Understanding temporal dynamics of COVID-19 symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation notes from 77,167 patients subjected PCR testing. By contrasting Electronic Health Record (EHR)-derived COVID-19-positive (COVID pos ; n = 2,317) versus COVID-19-negative neg 74,850) week preceding testing date, identify anosmia/dysgeusia (27.1-fold), fever/chills...
Background: To improve the safety of ventilator care and decrease risk ventilator-induced lung injury, we designed tested an electronic algorithm that incorporates patient characteristics settings, allowing near-real-time notification bedside providers about potentially injurious settings. Methods: Electronic medical records consecutive patients who received invasive ventilation were screened in three Mayo Clinic Rochester intensive units. The computer system alerted via text paging Alert...
Information overload in electronic medical records can impede providers' ability to identify important clinical data and may contribute error. An understanding of the information requirements ICU providers will facilitate development systems that prioritize presentation high-value reduce overload. Our objective was determine needs physicians, compared available within an record.Prospective observational study retrospective chart review.Three ICUs (surgical, medical, mixed) at academic...
Objectives: To develop and verify a digital twin model of critically ill patient using the causal artificial intelligence approach to predict response specific treatment during first 24 hours sepsis. Design: Directed acyclic graphs were used define explicitly relationship among organ systems treatments used. A hybrid agent-based modeling, discrete-event simulation, Bayesian network was simulate effect across multiple stages interactions major (cardiovascular, neurologic, renal, respiratory,...
Abstract Objectives Inpatients with language barriers and complex medical needs suffer disparities in quality of care, safety, health outcomes. Although in-person interpreters are particularly beneficial for these patients, they underused. We plan to use machine learning predictive analytics reliably identify patients prioritize them interpreters. Materials methods This qualitative study used stakeholder engagement through semi-structured interviews understand the perceived risks benefits...
The introduction of electronic medical records (EMR) and computerized physician order entry (CPOE) into the intensive care unit (ICU) is transforming way health providers currently work. challenge facing developers EMR's to create products which add value systems delivery. As become more prevalent, potential impact they have on quality safety, both negative positive, will be amplified. In this paper we outline key barriers effective use EMR describe methodology, using a worked example...
To use a handover assessment tool for identifying patient information corruption and objectively evaluating interventions designed to reduce errors improve medical decision making. The continuous monitoring, intervention, evaluation of the in modern intensive care unit practice generates large quantities information, platform on which decisions are made. Information corruption, defined as distortion/omission compared with record, may result judgment errors. Identifying these lead quality...
Purpose: The strategy used to improve effective checklist use in intensive care unit (ICU) setting is essential for success. This study aimed test the hypothesis that an electronic could reduce ICU provider workload, errors, and time completion, as compared a paper checklist. Methods: was simulation-based conducted at academic tertiary hospital. All participants completed checklists 6 patients: 3 using identical In both scenarios, had full access existing medical record system. outcomes...
Abstract Objective Access to palliative care (PC) is important for many patients with uncontrolled symptom burden from serious or complex illness. However, who could benefit PC do not receive it early enough at all. We sought address this problem by building a predictive model into comprehensive clinical framework the aims (i) identify in-hospital likely consult, and (ii) intervene on such contacting their team. Materials Methods Electronic health record data 68 349 inpatient encounters in...