Changing nursing practice within primary health care innovations: the case of advanced access model
Bibliographic record
Abstract
Abstract Background The advanced access (AA) model has attracted much interest across Canada and worldwide as a means of ensuring timely access to health care. While nurses contribute significantly to improving access in primary healthcare, little is known about the practice changes involved in this innovative model. This study explores the experience of nurse practitioners and registered nurses with implementation of the AA model, and identifies factors that facilitate or impede change. Methods We used a longitudinal qualitative approach, nested within a multiple case study conducted in four university family medicine groups in Quebec that were early adopters of AA. We conducted semi-structured interviews with two types of purposively selected nurses: nurse practitioners (NPs) (n = 6) and registered nurses (RNs) (n = 5). Each nurse was interviewed twice over a 14-month period. One NP was replaced by another during the second interviews. Data were analyzed using thematic analysis based on two principles of AA and the Niezen & Mathijssen Network Model (2014). Results Over time, RNs were not able to review the appointment system according to the AA philosophy. Half of NPs managed to operate according to AA. Regarding collaborative practice, RNs were still struggling to participate in team-based care. NPs were providing independent and collaborative patient care in both consultative and joint practice, and were assuming leadership in managing patients with acute and chronic diseases. Thematic analysis revealed influential factors at the institutional, organizational, professional, individual and patient level, which acted mainly as facilitators for NPs and barriers for RNs. These factors were: 1) policy and legislation; 2) organizational policy support (leadership and strategies to support nurses’ practice change); facility and employment arrangements (supply and availability of human resources); Inter-professional collegiality; 3) professional boundaries; 4) knowledge and capabilities; and 5) patient perceptions. Conclusions Our findings suggest that healthcare decision-makers and organizations need to redefine the boundaries of each category of nursing practice within AA, and create an optimal professional and organizational context that supports practice transformation. They highlight the need to structure teamwork efficiently, and integrate and maximize nurses’ capacities within the team throughout AA implementation in order to reduce waiting times.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.020 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".