Adoption of Information Technology in Primary Care Physician Offices in Alberta and Denmark, Part 2: A Novel Comparison Methodology
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
The seminal findings indicate that both Danish and Albertan physicians engaged with computers in the early 1990s; however, in Alberta the emphasis was on the recording of diagnosis and visit date for the purpose of payment for services by the provincial government, while in Denmark the emphasis was on creating an exchange mechanism between physicians utilizing existing standard protocols. In Denmark, physicians rapidly adopted locally provided EMRs, while in Alberta physicians retained paper records until the introduction of a standard process for reimbursing the costs of extended computer capability in 2001. While many of their peers in adjacent provincial or European Union country jurisdictions have languished with respect to EMR adoption, these two trajectories have led to nearly 100% of EMR adoption by general practitioners in Denmark as early as 2000 and 60% adoption by primary care physicians in Alberta by 2006. An evaluation of the similarities and differences points to various factors that have contributed to the rate of adoption of primary care physician office computing that may be important for future evaluations in other settings
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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