Cost‐effectiveness of a nurse practitioner‐family physician model of care in a nursing home: controlled before and after study
Bibliographic record
Abstract
AIMS: To examine the cost-effectiveness of a nurse practitioner-family physician model of care compared with family physician-only care in a Canadian nursing home. BACKGROUND: As demand for long-term care increases, alternative care models including nurse practitioners are being explored. DESIGN: Cost-effectiveness analysis using a controlled before-after design. METHODS: The study included an 18-month 'before' period (2005-2006) and a 21-month 'after' time period (2007-2009). Data were abstracted from charts from 2008-2010. We calculated incremental cost-effectiveness ratios comparing the intervention (nurse practitioner-family physician model; n = 45) to internal (n = 65), external (n = 70) and combined internal/external family physician-only control groups, measured as the change in healthcare costs divided by the change in emergency department transfers/person-month. We assessed joint uncertainty around costs and effects using non-parametric bootstrapping and cost-effectiveness acceptability curves. RESULTS: Point estimates of the incremental cost-effectiveness ratio demonstrated the nurse practitioner-family physician model dominated the internal and combined control groups (i.e. was associated with smaller increases in costs and emergency department transfers/person-month). Compared with the external control, the intervention resulted in a smaller increase in costs and larger increase in emergency department transfers. Using a willingness-to-pay threshold of $1000 CAD/emergency department transfer, the probability the intervention was cost-effective compared with the internal, external and combined control groups was 26%, 21% and 25%. CONCLUSION: Due to uncertainty around the distribution of costs and effects, we were unable to make a definitive conclusion regarding the cost-effectiveness of the nurse practitioner-family physician model; however, these results suggest benefits that could be confirmed in a larger study.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".