Evaluating the integration of chronic disease prevention and management services into primary health care
Bibliographic record
Abstract
BACKGROUND: The increasing number of patients with chronic diseases represents a challenge for health care systems. The Chronic Care Model suggests a multi-component remodelling of chronic disease services to improve patient outcomes. To meet the complex and ongoing needs of patients, chronic disease prevention and management (CDPM) has been advocated as a key feature of primary care producing better outcomes, greater effectiveness and improved access to services compared to other sectors. The objective of this study is to evaluate the adaptation and implementation of an intervention involving the integration of chronic disease prevention and management (CDPM) services into primary health care. METHODS/DESIGN: The implementation of the intervention will be evaluated using descriptive qualitative methods to collect data from various stakeholders (decision-makers, primary care professionals, CDPM professionals and patients) before, during and after the implementation. The evaluation of the effects will be based on a combination of experimental designs: a randomized trial using a delayed intervention arm (n = 326), a before-and-after design with repeated measures (n = 163), and a quasi-experimental design using a comparative cohort (n = 326). This evaluation will utilize self-report questionnaires measuring self-efficacy, empowerment, comorbidity, health behaviour, functional health status, quality of life, psychological well-being, patient characteristics and co-interventions. The study will take place in eight primary care practices of the Saguenay region of Quebec (Canada). To be included, patients will have to be referred by their primary care provider and present at least one of the following conditions (or their risk factors): diabetes, cardiovascular diseases, chronic obstructive pulmonary disease, asthma. Patients presenting serious cognitive problems will be excluded. DISCUSSION: In the short-term, improved patient self-efficacy and empowerment are expected. In the mid-term, we expect to observe an improvement in health behaviour, functional health status, quality of life and psychological well-being. At the organizational level, the project should lead to coordinated service delivery, improved patient follow-up mechanisms and enhanced interprofessional collaboration. Integration of CDPM services at the point of care in primary care practices is a promising innovation in care delivery that needs to be thoroughly evaluated. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01319656.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".