Home-based nursing care for clients carrying multidrug-resistant organisms: a focus group study
Bibliographic record
Abstract
Abstract Background The growing population of vulnerable clients receiving home-based nursing care, combined with the worldwide increase in the prevalence of multidrug-resistant organisms (MDROs), poses a new burden on nursing staff. This study aimed to gain insight into the experiences, attitudes, perceptions, dilemmas in daily practice and needs of nursing staff providing home-based nursing care for clients carrying MDROs. Methods Seven focus group discussions with home-based nursing staff (N = 34) were performed in the Netherlands between April and July 2022, using a semi-structured, open-ended topic list based on the I-change model and seven domains synthesized by Flottorp et al. Data were analysed using thematic analysis. Results Home-based nursing staff often considered infection prevention and control recommendations inconsistent, unclear or inapplicable in daily practice. Although participants acknowledged the importance of these precaution measures, their proportionality was sometimes questioned. Participants indicated to be influenced by perceptions, knowledge and behaviour of their colleagues and clients. In addition, they frequently experienced untimely, incomplete or inconspicuous information transfers about clients carrying MDROs. Concerns were expressed that clients were often insufficiently informed, debating the roles and responsibilities of involved healthcare professionals in providing and exchanging information. Finally, participants elaborated on the effect of the covid-19 pandemic and expressed the need for organisational support in providing education and sufficient resources regarding MDROs. Conclusions Insights of this study have aided in aligning upcoming MDRO guidelines for home-based nursing care in the Netherlands. Organisational support in expanding knowledge and providing sufficient resources is essential and clarity about roles and responsibilities of involved healthcare professionals regarding information transfer and informing patients is needed. Key messages • Expanding knowledge, sufficient resources and adequate information transfer about MDRO carriage are essential to ultimately prevent transmission and spread of MDROs. • The specific context of home-based nursing care for clients carrying MDROs should be acknowledged in MDRO guidelines.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".