Implementing and evaluating a program to facilitate chronic disease prevention and screening in primary care: a mixed methods program evaluation
Bibliographic record
Abstract
BACKGROUND: The objectives of this paper are to describe the planned implementation and evaluation of the Building on Existing Tools to Improve Chronic Disease Prevention and Screening in Primary Care (BETTER 2) program which originated from the BETTER trial. The pragmatic trial, informed by the Chronic Care Model, demonstrated the effectiveness of an approach to Chronic Disease Prevention and Screening (CDPS) involving the use of a new role, the prevention practitioner. The desired goals of the program are improved clinical outcomes, reduction in the burden of chronic disease, and improved sustainability of the health-care system through improved CDPS in primary care. METHODS/DESIGN: The BETTER 2 program aims to expand the implementation of the intervention used in the original BETTER trial into communities across Canada (Alberta, Ontario, Newfoundland and Labrador, the Northwest Territories and Nova Scotia). This proactive approach provides at-risk patients with an intervention from the prevention practitioner, a health-care professional. Using the BETTER toolkit, the prevention practitioner determines which CDPS actions the patient is eligible to receive, and through shared decision-making and motivational interviewing, develops a unique and individualized 'prevention prescription' with the patient. This intervention is 1) personalized; 2) addressing multiple conditions; 3) integrated through linkages to local, regional, or national resources; and 4) longitudinal by assessing patients over time. The BETTER 2 program brings together primary care providers, policy/decision makers and researchers to work towards improving CDPS in primary care. The target patient population is adults aged 40-65. The reach, effectiveness, adoption, implementation, maintain (RE-AIM) framework will inform the evaluation of the program through qualitative and quantitative methods. A composite index will be used to quantitatively assess the effectiveness of the prevention practitioner intervention. The CDPS actions comprising the composite index include the following: process measures, referral/treatment measures, and target/change outcome measures related to cardiovascular disease, diabetes, cancer and associated lifestyle factors. DISCUSSION: The BETTER 2 program is a collaborative approach grounded in practice and built from existing work (i.e., integration not creation). The program evaluation is designed to provide an understanding of issues impacting the implementation of an effective approach for CDPS within primary care that may be adapted to become sustainable in the non-research setting.
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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 | 0.131 | 0.080 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".