Pre-Post Analysis of the Impact of British Columbia Nurse Practitioner Primary Care Clinics on Patient Health and Care Experience
Bibliographic record
Abstract
ABSTRACT Objective This study aims to evaluate the impact of a primary care nurse-practitioner-led clinic model piloted in British Columbia (Canada) on patients’ health and care experience. Design The study relies on a quasi-experimental longitudinal design based on a pre-and-post survey of patients receiving care in NP-Led clinics. The pre-rostering survey (T0) was focused on patients’ health status and care experiences preceding being rostered to the NP clinic. One year later, patients were asked to complete a similar survey (T1) focused on the care experiences with the NP clinic. Setting To solve recurring problems related to poor primary care accessibility, British Columbia opened four pilot NP-led clinics in 2020. Each clinic has the equivalent of approximately six full-time NPs, four other clinicians plus support staff. Clinics are located in four cities ranging from core urban to peri rural. Participants Recruitment was conducted by the clinic’s clerical staff or by their care provider. A total of 437 usable T0 surveys and 254 matched and usable T1 surveys were collected. Primary outcome measures The survey instrument was focused on five core dimensions of patients’ primary care experience (accessibility, continuity, comprehensiveness, responsiveness, and outcomes of care) as well as on the SF-12 Short-form Health Survey. Results Scores for all dimensions of patients’ primary care experience increased significantly: Accessibility (T0=5.9, T1=7.9, p<0.000), Continuity (T0=5.5, T1=8.8, p<0.000), Comprehensiveness (T0=5.6, T1=8.4, p<0.000), Responsiveness (T0=7.2, T1=9.5, p<0.000), Outcomes of care (T0=5.0, T1=8.3, p<0.000). SF-12 Physical health T-scores also rose significantly (T0=44.8, T1=47.6, p<0.000) but no changes we found in the mental health T scores (T0=45.8, T1=46.3 p=0.709). Conclusions Our results suggest that the NP-Led primary care model studied here likely constitutes an effective approach to improve primary care accessibility and quality. Strengths and limitations This study evaluates the impact of a primary care nurse-practitioner-led clinic model piloted in British Columbia (Canada) on patients’ health and care experience The study rests on a pre-post survey without a control group therefore the differences observed could be caused by external factors Data collection took place between 2020 and 2022, during the Covid-19 pandemic. Only four NP-PCC clinics exist and participation in the survey was voluntary and uncompensated limiting the number of respondents
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".