Nursing Information Systems Requirements
Bibliographic record
Abstract
Considering the integral role of understanding users' requirements in information system success, this research aimed to determine functional requirements of nursing information systems through a national survey. Delphi technique method was applied to conduct this study through three phases: focus group method modified Delphi technique and classic Delphi technique. A cross-sectional study was conducted to evaluate the proposed requirements within 15 general hospitals in Iran. Forty-three of 76 approved requirements were clinical, and 33 were administrative ones. Nurses' mean agreements for clinical requirements were higher than those of administrative requirements; minimum and maximum means of clinical requirements were 3.3 and 3.88, respectively. Minimum and maximum means of administrative requirements were 3.1 and 3.47, respectively. Research findings indicated that those information system requirements that support nurses in doing tasks including direct care, medicine prescription, patient treatment management, and patient safety have been the target of special attention. As nurses' requirements deal directly with patient outcome and patient safety, nursing information systems requirements should not only address automation but also nurses' tasks and work processes based on work analysis.
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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 | 0.012 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".