The impact of team-based primary care on health care services utilization and costs: Quebec’s family medicine groups
Bibliographic record
Abstract
We investigate the effects on health care costs and utilization of team-based primary care delivery: Quebec's Family Medicine Groups (FMGs). FMGs include extended hours, patient enrolment and multidisciplinary teams, but they maintain the same remuneration scheme (fee-for-service) as outside FMGs. In contrast to previous studies, we examine the impacts of organizational changes in primary care settings in the absence of changes to provider payment and outside integrated care systems. We built a panel of administrative data of the population of elderly and chronically ill patients, characterizing all individuals as FMG enrollees or not. Participation in FMGs is voluntary and we address potential selection bias by matching on GP propensity scores, using inverse probability of treatment weights at the patient level, and then estimating difference-in-differences models. We also use appropriate modelling strategies to account for the distributions of health care cost and utilization data. We find that FMGs significantly decrease patients' health care services utilization and costs in outpatient settings relative to patients not in FMGs. The number of primary care visits decreased by 11% per patient per year among FMG enrolees and specialist visits declined by 6%. The declines in costs were of roughly equal magnitude. We found no evidence of an effect on hospitalizations, their associated costs, or the costs of ED visits. These results provide support for the idea that primary care organizational reforms can have impacts on the health care system in the absence of changes to physician payment mechanisms. The extent to which the decline in GP visits represents substitution with other primary care providers warrants further investigation.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".