Structured Clinical Tools for Periodic Health Assessment of Older Adults in Primary Care: A Scoping Review
Bibliographic record
Abstract
Background and Aims: Delivering preventive care to older adults presents challenges due to the lack of consensus on screening items, particularly regarding geriatric syndromes. Furthermore, chronological age often differs from biological age, which requires primary care clinicians (PCCs) to assess each patient's aging profile and tailor preventive interventions accordingly. Periodic Health Assessments (PHAs) offer an opportunity to administer preventive care. While several authors have developed Structured Clinical Tools (SCTs) to assist clinicians during PHAs, no SCT is widely used across clinicians. The study aims to identify existing SCTs for the PHA of older adults and evaluate their content, formats, and practical usability. Methods: We conducted a scoping review following the 6-step methodology recommended by Arksey and O'Malley (2005) and Levac (2010). We searched in PubMed, CINAHL, and Ageline, as well as in the grey literature, using keywords related to four main concepts: older adults, primary care, periodic health assessment, and SCT. We retrieved SCTs published in French and English between 2000 and 2024. Data were screened and charted by two independent reviewers. For step six (consultation), we gathered opinions of 10 PCCs on the practical usability of different SCTs. Results: Among the 8029 identified publications, we retrieved 16 distinct SCTs. Design objectives and conception processes of these SCTs varied. They were presented in various formats, including questionnaires, tables, schemas, checklists, acronyms, and mnemonics. While all SCTs addressed geriatric syndromes, only two adapted their recommendations to patients' aging profiles. Consulted PCCs emphasized that an ideal SCT should be integrated into an electronic health record, accommodate various aging profiles, and rely on evidence-based medicine. Conclusions: A reliable and user-friendly SCT for the PHA of older adults would facilitate the delivery of preventive care. However, no published SCTs to date meet the expectations of PCCs. Further research is necessary to develop one.
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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 | 0.049 | 0.191 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.031 | 0.027 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".