GP turnover in a multiprofessional team-based primary care system: evidence from Sweden
Bibliographic record
Abstract
BACKGROUND: GP recruitment and retention difficulties challenge the traditional general practice model. Task-shifting and relieving GPs from financial risk have been suggested to make primary care more attractive. In Sweden's multiprofessional team-based primary care system, GPs usually work as salaried employees and there is extensive task-shifting. Salaried employment facilitates mobility, potentially leading to high turnover. The opportunity to work on fixed contracts can also increase turnover rates. AIM: To describe practice turnover rates and examine associations with practice characteristics in a Swedish region. DESIGN AND SETTING: Analysis of observational register data from Skåne, Sweden (1.4 million residents). METHOD: Turnover rates were calculated for 157 primary care practices in 2010-2018. The main dataset included all physicians - permanent and temporary workers - regularly providing care in each month. To understand the role of temporary workers, a supplementary analysis was performed on permanently employed GPs and registrars at 80 public practices in 2019. Associations between turnover and practice characteristics were examined in bivariate analyses and multiple regressions. RESULTS: Annual practice turnover rates ranged between 20-40% (mean 30%), showing no time trend. The high rates mainly reflected the use of temporary GPs; in the supplementary analysis of permanent GPs and registrars, the mean annual turnover rate in 2019 was 13-15%. Turnover was higher for practices with socially deprived patients or high workload. Private practices had lower turnover conditional on the higher workload. CONCLUSION: The results indicate that a primary care system with salaried GPs facilitates GP mobility, which in turn creates barriers to continuity of care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".