Improving Access to Specialist Care for an Aging Population
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective: The objective of the study is to examine the Champlain. BASE TM (Building Access to Specialists through eConsultation) eConsult service’s impact on access to care for older persons. Methods: We conducted a cross-sectional analysis of all eConsult cases submitted between April 15, 2011, and July 31, 2015, in which the patient was above the age of 65 years. Study data consisted of utilization data collected automatically by the service and responses to surveys completed by primary care providers at the conclusion of all eConsult cases. Results: A total of 1,796 cases were submitted for older persons between April 15, 2011, and July 31, 2015, accounting for 21.3% of all cases submitted during the study period. Specialists responded to cases in a median of 0.8 days. In 94% of cases, providers rated eConsult as having great or excellent value for themselves and their patients. Sixty-eight percent of eConsults did not require a face-to-face visit; only 28% of all cases resulted in a referral. Discussion: As they suffer from higher than average rates of comorbid disease and mobility issues, older persons stand to benefit from shorter wait times and better access to care, which the eConsult service can provide.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it