PRAGMATIC IMPLEMENTATION OF AN ADVANCE CARE PLANNING INITIATIVE: MOVING KNOWLEDGE INTO ACTION
Bibliographic record
Abstract
Abstract Primary care is an important setting for patient and family-centered communication with older adults given the high frequency of interactions, longitudinal trusted relationships, and patient preferences for advance care planning (ACP). Increasing ACP conversations and documentation of advance directives in primary care is a focus of quality-of-care initiatives and is particularly relevant for older adults, including those with dementia. The SHARING Choices ACP program evaluation was designed to examine the fidelity of implementation with the two partner health systems. SHARING Choices includes a mailing (introductory letter, an agenda-setting checklist, a blank advance directive, and information about shared-portal access for family) sent two weeks prior to scheduled primary care visits for patients aged 65 and above along with access to an ACP facilitator in each practice. Embedding SHARING Choices within primary care practices involved a multi-step process, including onboarding of health system partners, facilitator identification and training, tailored onboarding, practice champion engagement, and practice orientation and ongoing support. Of 23,220 candidate patients, 17,931 outreach attempts by phone (77.9%) and the patient portal (22.1%) were made by ACP facilitators and 645 conversations occurred. Most conversations (94.8%) were less than 45 minutes in duration. Study findings reinforce the value of adaptable study design; co-designing workflow adaptations with frontline staff; adapting implementation processes to fit the operational and organizational priorities of the health system.
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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 | 0.063 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 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".