Automated Intraoperative Short Messaging Service Updates: Quality Improvement Initiative to Relieve Caregivers’ Worries
Bibliographic record
Abstract
BACKGROUND: Undergoing a surgical procedure is anxiety provoking for patients and their caregivers. During the intraoperative period, caregivers seek out informational updates from health care professionals, a situation complicated by COVID-19 health measures that require caregivers to wait outside the hospital. Short messaging service (SMS)-based communication that allows caregivers to follow their loved ones through surgery has shown promise in relieving anxiety and improving satisfaction with overall care. This form of communication is also well accepted by health care professionals and may be effective at relieving staff burden. OBJECTIVE: Here, we describe a quality improvement initiative of a standardized and integrated intraoperative SMS-based system to improve communication between surgical teams and caregivers. The main goal was to improve satisfaction with care, while the secondary goal was to reduce caregiver anxiety. METHODS: The initiative followed the framework of the Model for Improvement. A large tertiary care hospital offered the SMS to caregivers who were waiting for loved ones undergoing surgery. SMS messages were integrated into the clinical information system software and sent at key points during the surgical journey to phone numbers provided by caregivers. A satisfaction survey was sent to caregivers 1 business day after surgery. Data were collected between February 16 and July 14, 2021. RESULTS: Of the 8129 surgeries scheduled, caregivers waiting for 6149 (75.6%) surgeries agreed to receive SMS messages. A total of 34,129 messages were sent. The satisfaction survey was completed by 2088 (34%) of the 6149 caregivers. Satisfaction with messages was high, with the majority of respondents reporting that the messages received were adequate (1476/2085, 70.8%), clear (1545/2077, 74.4%), informative (1488/2078, 71.6%), and met their needs (1234/2077, 59.4%). The overall satisfaction score was high (4.5 out of 5), and caregivers reported that receiving text messages resulted in a reduction in anxiety (score=8.2 out of 10). Technical errors were reported by 69 (3.3%) caregivers. Suggestions for improvements included having messages sent more often; providing greater patient details, including the patient's health status; and the service being offered in other languages. CONCLUSIONS: This digital health initiative provided SMS messages that were systematically sent to caregivers waiting for their loved ones undergoing surgery, just as COVID-19 restrictions began preventing waiting onsite. The messages were used across 15 surgical specialties and have since been implemented hospital-wide. Digital health care innovations have the capacity to improve family-centered communication; what patients and their families find useful and appreciate will ultimately determine their success.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".