General practitioners' attitudes towards electronic prescribing and the use of the national prescription centre
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: The purpose of this study was to assess general practitioners' (GP) experience of an electronic prescription (e-prescription) system and the use of a national prescription centre. METHODS: A web-based survey with 29 structured questions and 8 open-ended questions was used. The technology acceptance model was used to explain first users' use of e-prescribing technology. GPs (n = 269) in two different primary health care organizations, which implemented the e-prescribing module as the first of its kind in Finland. RESULTS: Of the 269 GPs, 69 (26%) completed the survey. E-prescribing had influenced GP work and their management of patients' medication positively. Electronic health records and e-prescribing increased GPs' flexibility at work. There was a notable improvement in the management of prescription of narcotics with the introduction of e-prescribing. Issues with the e-prescribing system software delayed data processing and produced negative experience as users were forced to browse through too many pages to write a prescription. CONCLUSIONS: E-prescribing has improved GP's patient medication management, meeting Finland's national objectives. E-prescriptions not only reinforce the process of writing, transmitting and checking the authenticity of prescriptions but also make it mandatory for all key prescription information to be present for transmission. The perceived usefulness of e-prescribing by GPs could lead to more widespread adoption of the technology. Making e-prescribing more user friendly requires reforming work processes, which in turn would enhance the effectiveness of GP work.
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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 | 0.052 | 0.146 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".