All Stories

  1. Building a Time-Series Model to Predict Hospitalization Risks in Home Health Care: Insights Into Development, Accuracy, and Fairness
  2. Leveraging Artificial Intelligence/Machine Learning Models to Identify Potential Palliative Care Beneficiaries: A Systematic Review
  3. Developing a clinical decision support framework for integrating predictive models into routine nursing practices in home health care for patients with heart failure
  4. Exploring home healthcare clinicians’ needs for using clinical decision support systems for early risk warning
  5. Agreement between patient‐reported and clinically documented symptoms of acute myeloid leukemia: Study protocol
  6. Fairness gaps in Machine learning models for hospitalization and emergency department visit risk prediction in home healthcare patients with heart failure
  7. Development and Testing of the Relational and Structural Components of Innovativeness Across Academia and Practice for Healthcare Progress Scale
  8. Prediction of Cancer Symptom Trajectory Using Longitudinal Electronic Health Record Data and Long Short-Term Memory Neural Network
  9. Predicting emergency department visits and hospitalizations for patients with heart failure in home healthcare using a time series risk model
  10. Home Healthcare Patients With Distinct Psychological, Cognitive, and Behavioral Symptom Profiles and At-Risk Subgroup for Hospitalization and Emergency Department Visits Using Latent Class Analysis
  11. Uncovering hidden trends: identifying time trajectories in risk factors documented in clinical notes and predicting hospitalizations and emergency department visits during home health care
  12. Validation of Nursing Outcomes Classification: Knowledge and Self-management for Cardiac Disease
  13. Linking nursing outcomes classification to the self‐ and family management framework
  14. The identification of clusters of risk factors and their association with hospitalizations or emergency department visits in home health care
  15. Factors associated with poor self-management documented in home health care narrative notes for patients with heart failure
  16. Longitudinal Subgrouping of Patients With Cancer Based on Symptom Experiences: An Integrative Review
  17. Clinical notes: An untapped opportunity for improving risk prediction for hospitalization and emergency department visit during home health care
  18. Documentation of hospitalization risk factors in electronic health records (EHRs): a qualitative study with home healthcare clinicians
  19. Detecting Language Associated With Home Healthcare Patient’s Risk for Hospitalization and Emergency Department Visit
  20. Identifying Heart Failure Symptoms and Poor Self-Management in Home Healthcare: A Natural Language Processing Study
  21. A Review of Web-Based COVID-19 Resources for Palliative Care Clinicians, Patients, and Their Caregivers
  22. Are We Getting What We Really Want? A Systematic Review of Concordance Between Physician Orders for Life-Sustaining Treatment (POLST) Documentation and Subsequent Care Delivered at End-of-Life
  23. Improved readability and functions needed for mHealth apps targeting patients with heart failure: An app store review
  24. Multimorbidity and Cancer: Using Electronic Health Record (EHR) Data to Cluster Patients in Multimorbidity Phenotypes (GP735)
  25. Effectiveness of Nursing Interventions using Standardized Nursing Terminologies: An Integrative Review
  26. Multimorbidity and Cancer: Using Electronic Health Record (EHR) Data to Cluster Patients in Multimorbidity Phenotypes (S787)
  27. Multimorbidity, cancer, and symptoms: Using electronic health record data to cluster patients in multimorbidity phenotypes.
  28. Warming of Irrigation Fluids for Prevention of Perioperative Hypothermia During Arthroscopy: A Systematic Review and Meta-analysis
  29. Factors Associated With End-of-Life Planning in Huntington Disease
  30. Effect of Perception of Career Ladder System on Job Satisfaction, Intention to Leave among Perioperative Nurses
  31. Clustering and prediction of cancer symptom trajectories using longitudinal nursing documentation data