What is the potential for formal patient registration in Canadian primary care? The scale of informal registration' in Manitoba
Bibliographic record
Abstract
OBJECTIVES: Registration of patients with a physician is increasingly being considered across Canada as part of a reform of the primary health care system. This study aims to determine how much 'informal registration' currently exists; that is, to identify the number/proportion of patients who, given existing utilization patterns, already receive the majority of their care from one practice, in order to assess the potential for formal registration. METHODS: Administrative data were used to classify patients (n = 528,905) as being informally registered with a clinic if they received the majority of their care (75% or more of their total ambulatory visits) from the same practice over a three-year period (1994-1996). The proportion and number of informally registered patients were examined. RESULTS: Substantial variability emerged across practices in the proportion of informally registered patients (15-68%) and the number of informally registered patients per physician (544-1378 patients per full-time equivalent physician). Informal registration was higher among rural practices (60%) than among urban practices (38%). CONCLUSIONS: While formal registration of patients with physicians is increasingly being considered in Canada as a means to improve the primary care system, the potential disruption to both patients and physicians in moving towards registration should not be underestimated. The relatively low levels of existing informal registration suggest a need to enhance access by, for example, providing after-hours services.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".