Effect of Home Monitoring via Mobile App on the Number of In-Person Visits Following Ambulatory Surgery
Bibliographic record
Abstract
Importance: In the age of information and patient-centered care, new methods of delivering postoperative care must be developed and evaluated. Objective: To determine whether follow-up care delivered via a mobile app can be used to avert in-person follow-up care visits compared with conventional, in-person follow-up care in the first 30 days following ambulatory surgery. Design, Setting, and Participants: A randomized clinical trial was conducted from February 1 to August 31, 2015, among ambulatory patients undergoing breast reconstruction at an academic ambulatory care hospital. Patients were randomly assigned to receive follow-up care via a mobile app or at an in-person visit during the first 30 days after the operation. Analysis was intention-to-treat. Main Outcomes and Measures: The primary end point was the number of in-person follow-up visits during the first 30 days after the operation. Secondary end points were the number of telephone calls and emails to health care professionals, patient-reported convenience and satisfaction scores, and rates of complications. Results: Of the 65 women in the study (mean [SD] age, 47.7 [13.4] years), 32 (49%) were in the mobile app group, and 33 (51%) were in the in-person follow-up care group. Those in the mobile app group attended a mean of 0.66 in-person visits, vs 1.64 in-person visits in the in-person follow-up care group, for a difference of 0.40 times fewer in-person visits (95% CI, 0.24-0.66; P < .001) and sent more emails to their health care professionals during the first 30 days after the operation (mean, 0.65 vs 0.15; incidence rate ratio, 4.13; 95% CI, 1.55-10.99; P = .005) than did patients in the in-person follow-up care group. This statistically significant difference was maintained at 3 months postoperatively. The mobile app group reported higher convenience scores than the in-person follow-up care group (incidence rate ratio, 1.39; 95% CI, 1.09-1.77; P = .008). There was no difference between groups in the number of telephone communications, satisfaction scores, or complication rates. Conclusions and Relevance: Patients undergoing ambulatory breast reconstruction can use follow-up care via a mobile app to avert in-person follow-up visits during the first 30 days after the operation. Mobile app follow-up care affects neither complication rates nor patient-reported satisfaction scores, but it improves patient-reported convenience scores. Trial Registration: clinicaltrials.gov Identifier: NCT02318953.
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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 | 0.018 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".