Idaho rural physician technology usage over time
Bibliographic record
Abstract
Objective: Health information technology (HIT) in rural settings has considerable potential to address rural health needs such as cost, access, and efficiency. This study contrasts the use of technology by Idaho rural physicians to identify differences in technology usage over time. The study includes information on technology factors such as internet databases, internet journals, e-publications, teleconferencing, electronic health records (EHRs) for patient care, and electronic physician education materials.Methods: Surveys focused on the broad experience of practicing rural medicine were administered to rural physicians in Idaho who practiced in counties containing less than 50,000 people. Identical surveys were sent out in 2007 and again in 2012.Results: Out of the 248 rural physicians who were successfully mailed the survey in 2007, responses were obtained from 92 for a response rate of 37.1%. In 2012, the response rate was 35.3% (89/252). Descriptive and inferential analyses were conducted in order to monitor and compare technology usage over time in the rural medicine workforce environment.Conclusions: Comparative results across time periods indicated a significant increase in overall technology utilization by rural physicians. In addition, there was a trend of decreasing the disparities in technology utilization between gender, age, and employment groups. Among all groups of physicians in both 2007 and 2012, the highest technology usage was of internet databases, journals and e-publications.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".