Effect of Smartphone App Postoperative Home Monitoring After Oncologic Surgery on Quality of Recovery
Bibliographic record
Abstract
Importance: There has been an increase in health care-focused smartphone apps, including those for encouraging healthy behaviors and managing chronic conditions, but app-assisted postsurgical care has yet to be fully explored. Objective: To compare quality of recovery and patient satisfaction between conventional in-person follow-up and smartphone app-assisted follow-up for patients following Enhanced Recovery After Surgery Society (ERAS) protocols. Design, Setting, and Participants: This randomized clinical trial, conducted from June 2019 to April 2021, included women older than 18 years undergoing oncologic breast reconstruction or major gynecologic oncology surgery following ERAS protocols with the care of 2 surgeons at an academic tertiary care center. Interventions: Patients were randomized 1:1 to receive smartphone app-assisted follow-up or conventional in-person follow-up. The smartphone group used a surgeon-monitored app to record Quality of Recovery 15 (QoR15) scores, European Organisation for Research and Treatment of Cancer-selected adverse events, drain outputs, and surgical site photographs over 6 weeks. Patient satisfaction scores were assessed using validated Patient Satisfaction Questionnaire III (PSQ-III) subscales at 2 and 6 weeks postoperatively. The conventional follow-up group also completed the QoR15 and PSQ-III questionnaires at these intervals. Main Outcomes and Measures: The primary outcomes were quality of recovery and patient satisfaction, as measured by the QoR15 and PSQ-III, respectively. Secondary outcomes were costs of follow-up; the number of contacts with the medical system, complications, and surgeons' contacts with patients; and surgeons' perceptions of app-assisted care. Results: Of 72 patients included in the trial, 36 underwent breast reconstruction (mean [SD] age, 45.30 [9.13] years) and 36 underwent gynecologic oncology surgery (mean [SD] age, 54.90 [11.18] years). Three patients dropped out (2 who underwent breast reconstruction [1 in the app group, 1 in the control group], 1 who underwent gynecologic oncology surgery [control group]). The app group had significantly higher mean (SD) QoR15 scores than the control group (2 weeks: 127.58 [22.03] vs 117.68 [17.52], P = .02; 6 weeks: 136.64 [17.53] vs 129.76 [16.42], P = .03). Patients were equally satisfied between groups in all subsets of the PSQ-III at these intervals. The mean (SD) number of complications was similar in both groups, and a similar number of surgeon contacts per patient occurred (1.6 [1.2] vs 2.1 [2.0], P = .16). Surgeons appreciated early identification of complications with the app. Conclusions and Relevance: In this randomized clinical trial, postoperative follow-up for patients undergoing breast reconstruction and gynecologic oncology surgery using smartphone app-assisted monitoring led to improved quality of recovery and equal satisfaction with care compared with conventional in-person follow-up. Trial Registration: ClinicalTrials.gov Identifier: NCT03456167.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".