Tool to improve patient-provider interactions in adult primary care
Bibliographic record
Abstract
Objective To assess whether an intervention to help patients prioritize goals for their visit would improve patient-provider communication and clinical outcomes. Design Randomized controlled pilot study. Setting Primary care clinic. Participants There were 120 adult hypertensive patients enrolled. Intervention Patients were randomized to receive either usual care or a previsit patient activation card developed through a series of focus groups that prompted patients to articulate their needs and set priorities for their clinic visit. Encounters were audiorecorded, transcribed, and assessed using duplicate ratings of patient activation and decision making. Main outcome measures The primary outcome was change in medication adherence as measured by pill count at 4 and 12 weeks after the initial visit. Secondary outcomes evaluated patient-provider interaction quality (patient satisfaction, patient activation, shared decision making, patient trust, and physicians’ perceived difficulty of the encounter), functional status, and blood pressure control. Results Of the 120 enrolled patients, 106 completed the baseline visit (mean age of 66 years, 53% women, 57% Black, 36% White). Participants had multiple comorbidities (median number of medications = 8). During the visit, there was greater patient activation in the intervention arm than in the control arm (4.4 vs 3.8, P = .047; ratings were based on a scale from 1 to 10). However, after the visit there were no differences in medication adherence (4 weeks: 45.8% vs 49.5%; 12 weeks: 49.4% vs 51.1%), blood pressure control (4 weeks: 133/78 mm Hg vs 131/77 mm Hg; 12 weeks: 129/77 mm Hg vs 129/76 mm Hg), or encounter satisfaction (78.6% vs 73.8% fully satisfied; P = .63). There were also no differences in shared decision making, patients’ trust, or perceived difficulty of the encounter. Conclusion A single previsit tool designed to prompt patients to set a prioritized agenda improved patient activation during the visit, but did not affect the quality of the interaction or postvisit patient-centred outcomes.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".