MétaCan
Menu
Back to cohort
Record W2598817971 · doi:10.1001/jamasurg.2017.0111

Effect of Home Monitoring via Mobile App on the Number of In-Person Visits Following Ambulatory Surgery

2017· article· en· W2598817971 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJAMA Surgery · 2017
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineAmbulatoryMobile appsSmartphone appSurgeryEmergency medicineMedical emergencyWorld Wide Web

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.284
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it