Guidelines: Informatics for nurses entering practice
Bibliographic record
Abstract
These Guidelines have been created by:Michelle Honey, Emma Collins and Sally Britnell<br><b>Introduction</b>These guidelines identify the key knowledge, skills and behaviours toward nursing informatics for nurses as they enter practice as a Registered Nurse (RN). As such, they have been developed and articulated to inform undergraduate nursing education.With knowledge continually evolving, nurses need the tools and guidelines to adapt to the diverse and changing needs in the delivery of healthcare for New Zealanders. The New Zealand national health strategy released by the Ministry of Health calls for us to work smarter, embrace technology and to use technology to provide better health outcomes for New Zealanders. To do this we need to ensure nursing graduates can work with technology, from the simplest form of technology, such as a glucometer right through to the most complex patient management systems in order to provide optimal patient care.Through curriculum mapping, we identified a mismatch between current nursing education in New Zealand and industry requirements which highlighted the need to make nursing informatics more visible in nursing thus allowing embedding of nursing informatics into everyday nursing practice. Background reading included international nursing informatics literature including from Australia: the Australian National Informatics Standards for Nurses and Midwives; the initiative driven from the United States: Technology Informatics Guiding Education Reform (TIGER); the Royal College of Nursing in England: Every nurse an e-nurse: Digital capabilities for 21st century nursing; and from Canada: Nursing informatics entry to practice competencies for Registered Nurses.Drawing this together, the guidelines presented here identify four informatics principles for student nurses to achieve over the course of their undergraduate nursing education and enter practice as a Level One, or novice Registered Nurse.The four principles are:1. Professional practice2. Information management3. Information and communication technologies to enhance the health of New Zealanders4. General computer and ICT Skills<br>These principles align with Nursing Council of New Zealand (NCNZ) Competencies for Registered Nurses and were informed by an analysis of information collected via curriculum mapping, international nursing informatics competency work and consultation with industry stakeholders to provide beginning registered nurses with a clear direction for embedding nursing informatics within their practice. Inclusion of examples from everyday practice in the NZ health system adds a NZ context and as such, these guidelines form a bridge between theory, education and practice.<br>
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; 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".