Comparing Approaches to Measuring the Adoption and Usability of Electronic Health Records: Lessons Learned from Canada, Denmark and Finland
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
Internationally, the adoption of health information technology is increasing. However, a number of issues have complicated the adoption of electronic health records (EHRs). In addition to adoption issues, it is becoming increasingly recognized that healthcare providers face a variety of usability issues. In this paper, we consider approaches that have been taken to assess both adoption and usability of EHRs in Canada, Denmark and Finland. Although all three countries deploy surveys to assess adoption, the approach and focus of the surveys differs across the countries. In Denmark and Finland, these surveys are dedicated to assessing information technology (IT) usage; while in Canada, questions about IT usage are part of a larger physician survey. Regarding usability, approaches vary considerably. In Finland, the approach includes a national survey about EHR usability. In Canada, ratings of system usability are reported regionally on web sites; while in Denmark, regional study results are reported based on evaluation of commercial products. This paper highlights the need to consider different evaluation approaches internationally.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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