A national intervention to support frail older adults in primary care: a protocol for an adapted implementation framework
Bibliographic record
Abstract
BACKGROUND: Older Canadians are high users of health care services, however the health care system is not well-designed to meet the complex needs of many older adults. Older persons often look to their primary care practitioners to assess their needs and coordinate their care. The intervention seeks to improve primary care for older persons living with frailty and will be implemented in six primary care clinics in three Canadian provinces. Presently, more than 1.6 million older Canadians are living with frailty, and this is projected to increase to 2.5 million within a decade (Canadian Frailty Network, Frailty Matters, 2020). The model will include frailty screening, an online portal to expedite referrals and improve coordination with community services, and several tools and techniques to support patient and family engagement and shared decision-making. Our project is guided by the Consolidated Framework for Implementation Research (CFIR) (Damschroder LJ, et al. Implement Scil, 4, 50, 2009). As others have done, we adapted the CFIR for our work. Our adapted framework combines elements of the socio-ecological model, key concepts from the CFIR, and elements from other implementation science frameworks. Nested within a broader mixed-method implementation study, the focus of this paper is to outline our guiding conceptual framework and qualitative methods protocol. METHODS: We will use the adapted CFIR framework to inform the data we collect and our analytic approach. Our work is divided into three phases: (1) baseline assessment of 'usual care'; (2) tailoring and implementing a new primary care model; and (3) evaluation. In each of these phases we will engage in qualitative data collection, including clinical observations, focus groups, in-depth interviews and extensive field notes. At each site we will collect data with health care providers, key informants (e.g., executive directors), and rostered patients ≥ 70 years. We will engage in team-based analysis across multiple sites, three provinces and two languages through regular telephone conferences, a comprehensive analysis codebook, leadership from our Qualitative Working Group and a collective appreciation that "science is a team sport" (Clinical Orthopaedics and Related Research 471, 701-702, 2013). DISCUSSION: Outcomes of this research may be used by other research teams who chose to adapt the CFIR framework to reflect the unique contexts of their work, and clinicians seeking to implement our model, or other models of care for frail older patients in primary care. TRIAL REGISTRATION: U.S. National Library of Medicine, NCT03442426 . Registered 22 February 2018- Retrospectively registered.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".