Impact of Consumer Wearables Data on Pediatric Surgery Clinicians’ Management: Multi-Institutional Scenario-Based Usability Study
Bibliographic record
Abstract
BACKGROUND: At present, parents lack objective methods to evaluate their child's postoperative recovery following discharge from the hospital. As a result, clinicians are dependent upon a parent's subjective assessment of the child's health status and the child's ability to communicate their symptoms. This subjective nature of home monitoring contributes to unnecessary emergency department (ED) use as well as delays in treatment. However, the integration of data remotely collected using a consumer wearable device has the potential to provide clinicians with objective metrics for postoperative patients to facilitate informed longitudinal, remote assessment. OBJECTIVE: This multi-institutional study aimed to evaluate the impact of adding actual and simulated objective recovery data that were collected remotely using a consumer wearable device to simulated postoperative telephone encounters on clinicians' management. METHODS: In total, 3 simulated telephone scenarios of patients after an appendectomy were presented to clinicians at 5 children's hospitals. Each scenario was then supplemented with wearable data concerning or reassuring against a postoperative complication. Clinicians rated their likelihood of ED referral before and after the addition of wearable data to evaluate if it changed their recommendation. Clinicians reported confidence in their decision-making. RESULTS: In total, 34 clinicians participated. Compared with the scenario alone, the addition of reassuring wearable data resulted in a decreased likelihood of ED referral for all 3 scenarios (P<.01). When presented with concerning wearable data, there was an increased likelihood of ED referral for 1 of 3 scenarios (P=.72, P=.17, and P<.001). At the institutional level, there was no difference between the 5 institutions in how the wearable data changed the likelihood of ED referral for all 3 scenarios. With the addition of wearable data, 76% (19/25) to 88% (21/24 and 22/25) of clinicians reported increased confidence in their recommendations. CONCLUSIONS: The addition of wearable data to simulated telephone scenarios for postdischarge patients who underwent pediatric surgery impacted clinicians' remote patient management at 5 pediatric institutions and increased clinician confidence. Wearable devices are capable of providing real-time measures of recovery, which can be used as a postoperative monitoring tool to reduce delays in care and avoidable health care use.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".