Experiences of an interprofessional follow-up program in primary care practice
Bibliographic record
Abstract
BACKGROUND: An integrative cooperation of different healthcare professional is a key component for high quality health services. With an aging population and many with long-term conditions, more health tasks and follow-up care are being transferred to primary care and locally where people live. Interprofessional collaboration among providers of different professional designations will be of increasing importance to optimizing primary care capacity in years to come. There is a call for further exploration of models of interprofessional collaboration that might be applicable in Norwegian primary care. The aim of this study was to explore experiences of interprofessional collaboration between primary care physicians and nurses working in primary care by applying an intervention for people with type 2 diabetes. Specifically, this study was designed to strengthen and gain deeper insight into interprofessional collaboration between primary care physicians and nurses in primary care settings. METHODS: We applied Interpretive Description as a research strategy. The participants within this study were primary care physicians and nurses from four different primary care practices in the western and eastern parts of Norway. We used semi-structured telephone interviews for collecting the data between January and September 2021. RESULTS: The analysis revealed two key features of the primary care physicians and the nurses experience with interprofessional collaboration in primary care practices. The first involved managing the influence of discrepancies in their expectations of IPC and the second involved becoming aware of the competence they developed that allowed for better complementarity consultation. CONCLUSIONS: This study indicates that interprofessional collaboration in primary care practice requires that primary care physicians and nurses clarify their expectations and, in turn, determine how flexible they can become in changing their usual primary care practices. Moreover, findings reveal that nurses and primary care physicians had discrepancies in expectations of how interprofessional collaboration should be carried out in primary care practice. However, both the nurses and primary care physicians appreciated the blending of complementary competencies and skills that facilitated a more collaborative care practice. They experienced that this interprofessional collaboration represented an essential quality improvement in the primary care services. TRIAL REGISTRATION: The trial is registered 03/09/2019 in ClinicalTrials.gov (ID: NCT04076384).
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".