Impacts of information and communication technologies on nursing care: an overview of systematic reviews (protocol)
Bibliographic record
Abstract
BACKGROUND: Information and communication technologies (ICTs) used in the health sector have well-known advantages. They can promote patient-centered healthcare, improve quality of care, and educate health professionals and patients. However, implementation of ICTs remains difficult and involves changes at different levels: patients, healthcare providers, and healthcare organizations. Nurses constitute the largest health provider group of the healthcare workforce. The use of ICTs by nurses can have impacts in their practice. The main objective of this review of systematic reviews is to systematically summarize the best evidence regarding the effects of ICTs on nursing care. METHODS/DESIGN: We will include all types of reviews that aim to evaluate the influence of ICTs used by nurses on nursing care. We will consider four types of ICTs used by nurses as a way to provide healthcare: management systems, communication systems, information systems, and computerized decision support systems. We will exclude nursing management systems, educational systems, and telephone systems. The following types of comparisons will be carried out: ICT in comparison with usual care/practice, ICT compared to any other ICT, and ICT versus other types of interventions. The primary outcomes will include nurses' practice environment, nursing processes/scope of nursing practice, nurses' professional satisfaction as well as nursing sensitive outcomes, such as patient safety, comfort, and quality of life related to care, empowerment, functional status, satisfaction, and patient experience. Secondary outcomes will include satisfaction with ICT from the nurses and patients' perspective. Reviews published in English, French, or Spanish from 1 January 1995 will be considered. Two reviewers will independently screen the title and abstract of the papers in order to assess their eligibility and extract the following information: characteristics of the population and setting, type of interventions (e.g., type of ICTs and service provided), comparisons, outcomes, and review limitations. Any disagreements will be resolved by discussion and consensus involving the two reviewers or will involve a third review author, if needed. DISCUSSION: This overview is an interesting starting point from which to compare and contrast findings of separate reviews regarding the positive and negative effects of ICTs on nursing care. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42014014762.
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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 | 0.045 | 0.083 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.019 | 0.014 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.031 | 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".