Effectiveness of preventive primary care outreach interventions aimed at older people: meta-analysis of randomized controlled trials.
Bibliographic record
Abstract
OBJECTIVE: To determine the effectiveness of preventive primary care outreach interventions aimed at older people. Knowing whether such interventions are effective could help busy family physicians make choices about which preventive care services to provide. DATA SOURCES: We searched MEDLINE, CINAHL, AgeLine, Cochrane Controlled Trials Register, and EMBASE databases and reviewed the reference lists of retrieved articles. STUDY SELECTION: We included studies of preventive primary care interventions aimed at patients 65 years and older if the studies were randomized controlled trials and if any of the following outcomes was reported: mortality, living in the community, admission to acute care hospitals, and admission to long-term care. We defined preventive primary care outreach as proactive, provider-initiated care, which can be provided by nurses, physicians, other professionals, or volunteers, that is in addition to usual care and is provided in primary care settings. Such care can be provided through home visits, office visits, telephone contacts, or a combination of these methods. SYNTHESIS: We assessed the quality of studies and extracted descriptive information on study populations, interventions, and outcomes for 19 trials involving 14,911 patients. Summary odds ratios were estimated for each outcome using a random effects model. CONCLUSION: This review showed that studies of preventive primary care outreach interventions aimed at older people were associated with a 17% reduction of mortality and a 23% increased likelihood of continuing to live in the community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.042 | 0.129 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.042 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".