Open Notes in Swedish Psychiatric Care (Part 1): Survey Among Psychiatric Care Professionals
Bibliographic record
Abstract
BACKGROUND: When the Swedish version of Open Notes, an electronic health record (EHR) service that allows patients online access, was introduced in hospitals, primary care, and specialized care in 2012, psychiatric care was exempt. This was because psychiatric notes were considered too sensitive for patient access. However, as the first region in Sweden, Region Skåne added adult psychiatry to its Open Notes service in 2015. This made it possible to carry out a unique baseline study to investigate how different health care professionals (HCPs) in adult psychiatric care in the region expect Open Notes to impact their patients and their practice. This is the first of two papers about the implementation of Open Notes in adult psychiatric care in Region Skåne. OBJECTIVE: The objective of this study was to describe, compare, and discuss how different HCPs in adult psychiatric care in Region Skåne expect Open Notes to impact their patients and their own practice. METHODS: A full population Web-based questionnaire was distributed to psychiatric care professionals in Region Skåne in late 2015. The response rate was 28.86% (871/3017). Analyses show that the respondents were representative of the staff as a whole. A statistical analysis examined the relationships between different professionals and attitudes to the Open Notes service. RESULTS: The results show that the psychiatric HCPs are generally of the opinion that the service would affect their own practice and their patients negatively. The most striking result was that more than 60% of both doctors (80/132, 60.6%) and psychologists (55/90, 61%) were concerned that they would be less candid in their documentation in the future. CONCLUSIONS: Open Notes can increase the transparency between patients and psychiatric HCPs because patients are able to access their EHRs online without delay and thus, can read notes that have not yet been approved by the responsible HCP. This may be one explanation as to why HCPs are concerned that the service will affect both their own work and their patients.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".