Protocol for determining primary healthcare practice characteristics, models of practice and patient accessibility using an exploratory census survey with linkage to administrative data in Nova Scotia, Canada
Bibliographic record
Abstract
INTRODUCTION: There is little evidence on how primary care providers (PCPs) model their practices in Nova Scotia (NS), Canada, what services they offer or what accessibility is like for the average patient. This study will create a database of all family physicians and primary healthcare nurse practitioners in NS, including information about accessibility and the model of care in which they practice, and will link the survey data to administrative health databases. METHODS AND ANALYSIS: 3 census surveys of all family physicians, primary care nurse practitioners (ie, PCPs) and their practices in NS will be conducted. The first will be a telephone survey conducted during typical daytime business hours. At each practice, the person answering the telephone will be asked questions about the practice's accessibility and model of care. The second will be a telephone survey conducted after typical daytime business hours to determine what out-of-office services PCP practices offer their patients. The final will be a tailored fax survey that will collect information that could not be obtained in the first 2 surveys plus new information on scope of practice, practice model and willingness to participate in research. Survey data will be linked with billing data from administrative health databases. Multivariate regression analysis will be employed to assess whether access and availability outcome variables are associated with PCP and model of practice characteristics. Negative binomial regression analysis will be employed to assess the association between independent variables from the survey data and health system use outcomes from administrative data. ETHICS AND DISSEMINATION: This study has received ethical approval from the Nova Scotia Health Authority and the Health Data Nova Scotia Data Access Committee. Dissemination approached will include stakeholder engagement at local and national levels, conference presentations, peer-reviewed publications and a public website.
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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 | 0.051 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.068 | 0.012 |
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".