Optimizing Research Data Acquisition with Smart Pill Bottles (SPBs), the ORDAS Trial: A Feasibility and Implementation Study Protocol
Bibliographic record
Abstract
Abstract Introduction Clinical trials are fundamental to advancing all areas of medicine. Despite their importance, trials are often expensive and time-consuming due to the need for extensive human resources, with limitations in cohort sizes and potential biases from loss of follow-up. Smart pill bottles (SPBs) offer a promising innovation by automating data collection, which could reduce costs and improve the granularity and accuracy of data. This technology may provide a more efficient alternative to traditional methods, streamlining data acquisition in clinical research. Objectives This proof-of-concept study aims to assess the feasibility of using smart pill bottles (SPBs) to collect data on opioid consumption in a postoperative setting, comparing their cost- efficiency and data quality to traditional methods. We hypothesize that SPBs will be readily adopted by users and enable the collection of highly granular data with fewer missing data points, while reducing the costs associated with human resource-based data collection. Material and Methods This single-center, single-arm trial will enroll 69 patients aged 18 and above undergoing major abdominal surgery via laparotomy. Following recruitment, patients will complete web-based questionnaires assessing pain, comorbidities, and quality of life. Postoperatively, patients will receive an SPB, the Thess Therapy Smart System manufactured by Thess Corporate (France) and provided by AppMed Inc. (Canada) to monitor opioid consumption at home for up to 90 days. At the end of the study period, participants will use the web-based platform to complete the same questionnaires, an opioid compliance checklist and a product satisfaction survey. The primary outcome will be the percentage of patients who successfully use the SPB throughout the study period. Secondary outcomes will include the extent of automated data collection, data granularity, project costs, the incidence of persistent opioid consumption, and patient satisfaction with the SPB. Trial registration clinicaltrials.gov (July 25th, 2024). Unique protocol ID: 2025-3801. NCT number: NCT06522698 .
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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 | 0.166 | 0.154 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 0.011 |
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".