Are we making a difference in primary care for adults with intellectual and developmental disabilities?
Bibliographic record
Abstract
In 2003, an International Think Tank on Reducing Health Disparities was held in Ottawa, Canada; it included representatives from Australia, Canada, Mexico, New Zealand, and the United States of America.The participants at that event identified individuals with disabilities (and intellectual and developmental disabilities (IDD) specifically) as one of 11 vulnerable populations with regards to being "more likely to become ill and less likely to receive appropriate care" (1).Individuals with IDD present with cognitive deficits associated with limitations in activities of daily living that begin in the developmental period, typically before the age of 18 years.As a group, they are at greater risk for health problems and for using resource-intensive health care services.However, because of their disabilities, they have greater difficulty negotiating their way through health services (2), ABSTRACTObjectives.To examine the impact of the dissemination of guidelines to physicians and of a population-level health communication intervention on the percentage of adults with intellectual and developmental disabilities (IDD) receiving preventive care through primary care.Methods.Noninstitutionalized adults with IDD in the province of Ontario, Canada, aged 40 to 64 years were matched to Ontarians without such disabilities each fiscal year (FY) from 2003 to 2016.Health administrative data were used to create a composite measure of receipt of recommended preventive primary care.Age-adjusted rates were used to assess trends, and average two-year rate ratios (RRs) and confidence intervals (CIs) were used to evaluate the effectiveness of the interventions.Results.The number of adults with IDD identified ranged from 20 030 in FY 2003 to 28 080 in FY 2016.The percentage of adults with IDD receiving recommended preventive primary care ranged from 43.4% in 2003 to 55.7% in 2015.Men with IDD had a 53.7% increase across the 13 years, while women with IDD only had a 30.9% increase.When evaluating the impact of the interventions, men with IDD were 4% more likely (RR: 1.04; 95% CI: 1.02-1.05) to receive recommended primary care in FY 2015 and FY 2016 as compared to FY 2009 and FY 2010; in contrast, women with IDD were 5% less likely (RR: 0.95; 95% CI: 0.93-0.98).A comparable drop was observed among women without IDD.Conclusions.Nearly 45% of adults with IDD in Ontario still do not receive recommended preventive care through primary care.Long-term impacts of the interventions introduced in the province may still occur over time, so ongoing monitoring is warranted.Special attention should be given to the preventive care needs of women with IDD.
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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 | 0.015 | 0.098 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".