Patient Empowerment and Nursing Clinical Workflows Enhanced by Integrated Bedside Terminals
Bibliographic record
Abstract
BACKGROUND: Integrated bedside terminals (IBTs) were implemented at Humber River Hospital with the goal of supporting patient independence and autonomy and improving nursing workflows. The IBTs provide access to a range of convenience and entertainment services as well as access to personal health information. Due to the novelty of the technology, there is a paucity of empirical data on patients' use of, satisfaction with and perceptions of bedside terminals. AIM: The purpose of this study was to evaluate the impact of IBTs on patient empowerment and nursing workflows. METHODS: A mixed methods design was employed using a cross-sectional patient survey and semi-structured interviews with nurses. The patient survey assessed patient empowerment and satisfaction with the range of services offered through the IBT. Patient scores were summarized using descriptive statistics. Additionally, face-to-face interviews with nurses were used to illicit feedback regarding the IBTs' impacts on nursing workflows. RESULTS: In total, 113 patients and 11 nurses participated in the study. Analysis of patient satisfaction surveys indicated that the IBTs enhanced the patient experience and increased self-care management. Nurses reported that the IBTs helped patients feel comfortable and entertained and helped enhance the nurse-patient relationship. However, nurses also expressed concern that elderly patients were less inclined to use the IBT. CONCLUSION: The results from the present study suggest that the IBT system has the potential to empower patients and decrease demands on nurses. Patients' notes incorporated into the IBT may provide the necessary level of involvement to garner a greater sense of patient empowerment. The IBT does not replace the need for nurses to deliver information to patients in a manner that supports their trust.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".