Effect of SMS Ward Round Notifications on Inpatient Experience in Acute Medical Settings: Retrospective Cohort Study
Bibliographic record
Abstract
Background: Ward rounds are an essential component of inpatient care. Patient participation in rounds is increasingly encouraged, despite the occasional complicated circumstances, especially in acute care settings. Objective: This study aimed to evaluate the effect of real-time ward round notifications using SMS text messaging on the satisfaction of inpatients in an acute medical ward. Methods: Since January 2021, a service implementing real-time ward round notifications via text messaging (WR-SMS) has been operational at a tertiary-care medical center in Korea. To assess its impact, we conducted a retrospective cohort study of patients admitted to the acute medical unit who participated in a patient experience survey. Patient satisfaction was compared between patients admitted in 2020 (pre-WR-SMS group) and 2021 (post-WR-SMS group). Results: From January 2020 to December 2021, a total of 100 patients were enrolled (53 patients in the pre-WR-SMS group and 47 patients in the post-WR-SMS group). Compared with the pre-WR-SMS group, the post-WR-SMS group showed significantly greater satisfaction about being informed about round schedules (mean 3.43, SD 0.910 vs mean 3.89, SD 0.375; P<.001) and felt more emotionally supported during admission (mean 3.49, SD 0.800 vs mean 3.87, SD 0.397; P<.001). Regarding other questionnaire scores, the post-WR-SMS group showed an overall, although statistically insignificant, improvement compared with the pre-WR-SMS group. Conclusions: Real-time round notifications using a user-friendly SMS may improve inpatient satisfaction effectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".