Purpose: To evaluate accessibility and appropriateness of the Crash Outcomes Data Evaluation Systems (CODES) databases for prehospital trauma triage decision-rule development for people age 65 years and older.
Design And Methods: This informatics feasibility study included five steps for evaluating the accessibility of CODES databases. Eight criteria were used to evaluate the appropriateness of these databases for older person prehospital trauma triage decision-rule development.
Findings: Only 4 of the 33 states funded for CODES database development released their data to the study team during the 13-month data-acquisition period. Potential predictor variables (of life-threatening injury) and outcome variables (need for trauma center care) were identified for each database. Several databases had large amounts of missing data. Codebooks were available but descriptions of data validation procedures were unavailable.
Conclusions: At this time, limited access to and development of CODES databases and missing data preclude the usefulness of these databases for older person triage decision rule development. Although adequate funding must be appropriated for continued CODES development, and commitment from individual states is essential, these databases offer great promise as a mechanism for decision-rule development to guide triage decision-making. Investigators should systematically evaluate large databases before using them in secondary analyses for clinical decision rule development.
Clinical Relevance: Nurses participate in the planning, development, and implementation of health information systems in various settings. They also assume important roles in prehospital care as direct care providers, EMS administrators, participants of local and state EMS councils where emergency care problems are discussed and policies are formulated, and through use at state and federal levels.
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http://dx.doi.org/10.1111/j.1547-5069.2008.00219.x | DOI Listing |
Int J Syst Evol Microbiol
January 2025
Department of Veterinary Medicine, College of Veterinary Medicine, National Chung Hsing University, Taichung, Taiwan, ROC.
In 1997, the name (Blackall 1989) comb. nov. was proposed by Chun on transfer of the species to the newly established genus as its type species.
View Article and Find Full Text PDFMethods Inf Med
January 2025
Artificial Intelligence Lab, Mimos Berhad, Kuala Lumpur, Malaysia.
Objective: This is the first Malaysian machine learning model to detect and disambiguate abbreviations in clinical notes. The model has been designed to be incorporated into MyHarmony, a Natural Language Processing system, that extracts clinical information for healthcare management. The model utilizes word embedding to ensure feasibility of use, not in real-time but for secondary analysis, within the constraints of low-resource settings.
View Article and Find Full Text PDFJMIR Form Res
December 2024
Northwestern University Feinberg School of Medicine, 625 N. Michigan Avenue, Suite 2700, Chicago, IL 60611, Chicago, US.
Background: Patient-reported outcome measures (PROMs) are crucial for informed medical decisions and evaluating treatments. However, they can be burdensome for patients and sometimes lack the reliability clinicians need for clear clinical interpretations.
Objective: Patient-reported outcome measures (PROMs) are crucial for informed medical decisions and evaluating treatments.
Appl Clin Inform
January 2025
Pediatrics, Ohio State University College of Medicine, Columbus, United States.
Objective: To review pediatric artificial intelligence (AI) implementation studies from 2010-2021 and analyze reported performance measures.
Methods: We searched PubMed/Medline, Embase CINHAL, Cochrane Library CENTRAL, IEEE and Web of Science with controlled vocabulary.
Inclusion Criteria: AI intervention in a pediatric clinical setting that learns from data (i.
Health Care Manage Rev
January 2025
Background: Public reporting of home health care agencies' performance metrics, including patient satisfaction, care processes, and health outcomes, aims to inform customer decisions and encourage agencies to improve the quality of services. However, there is limited research that examines the heterogeneous performance of home health care agencies.
Purposes: The aim of this study was to analyze the performance of home health care agencies by identifying distinct subgroups of agencies with similar performance profiles and describing the relationships between agency characteristics and such subgroups.
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