Team-based care intervention: views and perspectives from patients and healthcare professionals
Bibliographic record
Abstract
Abstract Background Blood pressure (BP) control is poor in European countries. Team-based care (TBC) intervention involving different healthcare professionals has the potential to improve BP control. Within a patient-centered approach, we evaluated patients' and healthcare professionals' opinion about a TBC intervention involving nurses, pharmacists, and physicians (MD). Methods As part of the TBC study, a pragmatic randomized controlled study to evaluate the impact of a TBC interprofessional intervention on BP control, we collected opinion of patients and team-based members (nurses, community pharmacists, and MD) at the end of study period using specific questionnaires. A mean TBC-satisfaction score was computed, assessing various aspects of the intervention, and ranged from 0 to 60, where a higher score represents a greater satisfaction. Results All patients (100%), pharmacists (100%), MD (92%) and nurses (80%) were satisfied with TBC intervention. Most patients considered that TBC can help improving BP control (92%), drug intake (71%), and lifestyle habits (84%). Furthermore, patients reported that TBC improved their relationship with nurses (66%), pharmacists (55%), and MD (50%). Patients also reported that their discussion with nurses (95%) and pharmacists (89%) helped improve medication intake. Healthcare professionals considered that TBC improve the quality of care (91%) and an added value for the management of chronic disease (79%). Mean TBC-satisfaction score was higher among MD [42 (SD: 9)] and pharmacists [45 (SD: 6)] compared with nurses [36 (SD: 9)]. Conclusions Overall, patients and healthcare professionals were highly satisfied regarding TBC engaging different healthcare professionals in a primary care setting. Key messages TBC intervention seem to be well appreciated by patients and healthcare professionals. Favourable patients’ and healthcare professionals’ perspectives will help implementing TBC intervention.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".