Inpatient vs. Outpatient: A Systematic Review of Information Needs throughout the Heart Failure Patient Journey
Bibliographic record
Abstract
The objective of this systematic review was to identify and describe information needs for individuals with heart failure (HF) throughout their patient journey. Six databases were searched (APA PsycINFO, CINAHL Ultimate, Embase, Emcare Nursing, Medline ALL, and Web of Science Core Collection) from inception to February 2023. Search strategies were developed utilizing the PICO framework. Potential studies of any methodological design were considered for inclusion through a snowball hand search. Data from the included articles were extracted by a reviewer, and the extraction accuracy was independently cross-checked by another author. Quality appraisal was assessed using the Mixed-Methods Appraisal Tool. A narrative synthesis was used to analyze all the outcomes according to the Synthesis Without Meta-analysis reporting guidelines. Twenty-five studies (15 quantitative and 10 qualitative) were included. Socioeconomic, cultural, and demographic factors influencing information needs were considered. The top three information needs for outpatients included general HF information, signs and symptoms and disease management strategies. For inpatients, medications, risk factors, and general HF were reported as the top needs. These divergent needs emphasize the importance of tailored education at different stages. Additionally, the review identified gaps in global representation, with limited studies from Africa and South America, underscoring the need for inclusive research. The findings caution against overgeneralization due to varied reporting methods. Practical implications call for culturally sensitive interventions to address nuanced HF patients' needs, while future research must prioritize standardized reporting, consider diverse patient journey timepoints, and minimize biases for enhanced reliability and applicability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".