Back to search

Article

Discordant Care as a Computable Phenotype for Real-Time Detection of Routine Protocol Completion Without Cognitive Patient Engagement in the ICU: Retrospective Cohort Study

2026-02-26

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Background</h4> Quality measurement in intensive care emphasizes task completion—whether assessments were documented and protocols followed. Electronic health record (EHR) systems capture these signals in real time, yet current metrics cannot distinguish task completion from cognitive clinical engagement. A prior analysis demonstrated that omission of orientation assessment predicted a 4.29...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
2bded1ab-b7e8-5724-9ac0-83d912b2ecc1
DOI
10.64898/2026.02.24.26347021
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Discordant Care as a Computable Phenotype for Real-Time Detection of Routine Protocol Completion Without Cognitive Patient Engagement in the ICU: Retrospective Cohort StudyDOI 10.64898/2026.02.24.26347021
First-Day Documentation Patterns and Mortality or Continued ICU Occupancy Across Four Critical Care Datasets: A Fixed-Window Retrospective StudySemantic proximity
[1]¿p#1 Biomarker- or Phenotype-Guided Sedation in the Intensive Care Unit: A Systematic Review and Meta-analysis of Patient-Centered OutcomesSemantic proximity
Delirium Severity Trajectories and Outcomes in ICU Patients. Defining a Dynamic Symptom Phenotype.Semantic proximity
Care Phenotypes In Critical CareSemantic proximity
An Electronic Phenotype Series for Measuring Adherence to the Wake Up and Breathe Protocol in Mechanically Ventilated ICU PatientsSemantic proximity
Natural language processing diagnosed behavioural disturbance phenotypes in the intensive care unit: characteristics, prevalence, trajectory, treatment, and outcomes.Semantic proximity
Association Between the Confusion Assessment Method for the Intensive Care Unit (CAM- ICU) and Prolonged Mechanical Ventilation Following Major Cardiac SurgerySemantic proximity
Clinical utility of automatic phenotype annotation in unstructured clinical notes: intensive care unit use.Semantic proximity
A Common Longitudinal Intensive Care Unit data Format (CLIF) to enable multi-institutional federated critical illness researchSemantic proximity
Observation-process features are associated with larger domain shift in sepsis mortality prediction: a cross-database evaluation using MIMIC-IV and eICU-CRDSemantic proximity
Delirium and High Sedation Levels are Common in Critically Ill Patients with COVID-19 and Associated with Poor Long-Term OutcomesSemantic proximity
Multinational Validation of the Intensive Documentation Index for ICU Mortality Prediction: Temporal Resolution and ICU MortalitySemantic proximity
Select a neighboring publication to make it the new centre.