Improving the quality of primary care for adults with intellectual and developmental disabilities: Value of the periodic health examination.
Bibliographic record
Abstract
OBJECTIVE: To implement a Health Check protocol for patients with intellectual and developmental disabilities (IDD) and assess outcomes. DESIGN: Retrospective chart review and staff survey. SETTING: Two Ontario family health teams. PARTICIPANTS: Of 276 patients with IDD identified, 139 received the Health Check (Health Check group). A convenience sample (N = 147) of clinical staff participated in the survey. MAIN OUTCOME MEASURES: The protocol included patient identification, invitation, and modified health examination. Chart review assessed completion of 8 preventive maneuvers, and clinical staff were surveyed on their comfort, knowledge, and skills in care of patients with IDD. Logistic regression analyses were used to compare outcomes for the Health Check and non-Health Check groups, adjusted for practice site. RESULTS: < .05) for those who performed the Health Check. Still, fewer than half thought they had the necessary skills and resources to care for patients with IDD. CONCLUSION: Performing the Health Check was associated with improved preventive care and staff experience. Wider implementation and evaluation is needed, along with protocol adjustments to provide more support to staff for this work.
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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".