Emergency Physician Use of the Alberta Netcare Portal, a Province-Wide Interoperable Electronic Health Record: Multi-Method Observational Study
Bibliographic record
Abstract
BACKGROUND: The adoption and use of an electronic health record (EHR) can facilitate real-time access to key health information and support improved outcomes. Many Canadian provinces use interoperable EHRs (iEHRs) to facilitate health information exchange, but the clinical use and utility of iEHRs has not been well described. OBJECTIVE: The aim of this study was to describe the use of a provincial iEHR known as the Alberta Netcare Portal (ANP) in 4 urban Alberta emergency departments. The secondary objectives were to characterize the time spent using the respective electronic tools and identify the aspects that were perceived as most useful by emergency department physicians. METHODS: In this study, we have included 4 emergency departments, 2 using paper-based ordering (University of Alberta Hospital [UAH] and Grey Nuns Community Hospital [GNCH]) and 2 using a commercial vendor clinical information system (Peter Lougheed Centre [PLC] and Foothills Medical Centre [FMC]). Structured clinical observations of ANP use and system audit logs analysis were compared at the 4 sites from October 2014 to March 2016. RESULTS: Observers followed 142 physicians for a total of 566 hours over 376 occasions. The median percentage of observed time spent using ANP was 8.5% at UAH (interquartile range, IQR, 3.7%-13.3%), 4.4% at GNCH (IQR 2.4%-4.4%), 4.6% at FMC (IQR 2.4%-7.6%), and 5.1% at PLC (IQR 3.0%-7.7%). By combining administrative and access audit data, the median number of ANP screens (ie, results and reports displayed on a screen) accessed per patient visit were 20 at UAH (IQR 6-67), 9 at GNCH (IQR 4-29), 7 at FMC (IQR 2-18), and 5 at PLC (IQR 2-14). When compared with the structured clinical observations, the statistical analysis of screen access data showed that ANP was used more at UAH than the other sites. CONCLUSIONS: This study shows that the iEHR is well utilized at the 4 sites studied, and the usage patterns implied clinical value. Use of the ANP was highest in a paper-based academic center and lower in the centers using a commercial emergency department clinical information system. More study about the clinical impacts of using iEHRs in the Canadian context including longer term impacts on quality of practice and safety are required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".