Bibliographic record
Abstract
Introduction: Digital technology has a tremendous impact on all sectors of health care. The advent of Electronic Health Record (HER) in healthcare systems and clinical practice has led to a greater appreciation of the importance of nursing documentation data. The aim of our work was to identify the state-of-the-art of implementation of nursing minimum data sets in different countries, the millstones encountered and ways to determine Romanian healthcare community to widely adopt the electronic nursing documentation record. Methods: Our study is based on a literature review (1995-2019), including conference proceedings, enhanced by an oral survey conducted for public hospitals and two private hospitals in Romania. Results: In most hospitals from USA, Canada, UK and EU, Australia and New Zeeland the transition period from nursing paper records to EHR started years ago and is still an ongoing process. In England the Government has committed to making all records concerning patients and care services, digital, real-time and interoperable by 2020. In EU, regarding Nursing Minimum Data Sets (NMDS), the most advanced implementation is in Belgium. A comparison of different NMDS implementations has shown, besides differences in advantages and disadvantages, there is not a unified view on what data must be included. In Romania, the EHR is mainly based on Diagnosis-Related Groups (DRGs) and do not include nursing documentation data. Moreover, with one or two exceptions, there are no paper-based nursing files. Conclusions: Electronic nursing documentation records and NMDS become a must in the digital era. Though there are valuable operational implementations of NMDS at the level of several countries, data sharing requires a broader consensus regarding nursing standards and classifications of nursing diagnosis, interventions and practices. Systems like ICNP, NANDA, ICF, and ZEFP must be further developed and improved to allow cross-mappings and capturing of multi-cultural aspects. Regarding Romania, the first steps toward an electronic nursing record are to update the nursing curriculum in all medical universities to include standards and classification systems and examples of nursing documentation files.
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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 | 0.058 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.032 | 0.034 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".