Assessing infection prevention and control programs in residential aged care in Australia: A multi‐methods cross‐sectional study
Bibliographic record
Abstract
AIM: To assess infection prevention and control programs in residential aged care facilities. METHODS: A cross-sectional survey and structured interviews from 10 residential aged care facilities in Victoria, Australia, were used. Infection prevention and control nurse leads from each facility completed a purpose-built survey based on best practice infection prevention control program core components, including staff training, policies and procedures, governance, and surveillance. Follow-up interviews with residential aged care staff, residents and family visitors were carried out to elaborate and verify survey data. RESULTS: Surveys from all 10 facilities were received and 75 interviews carried out. All facilities had an infection prevention and control lead nurse who had undergone additional training, and 60% of facilities had an infection prevention and control lead position description. All facilities had a committee to oversee their infection prevention and control program, and all had policies and procedures for standard and transmission-based precautions. One facility did not have a policy on healthcare-associated infection surveillance, and two facilities did not have an antimicrobial stewardship policy. All facilities provided staff training in hand hygiene and personal protective equipment use, but not all routinely assessed competency in these. CONCLUSIONS: The residential aged care facilities' infection prevention and control programs were generally in a strong position, although there were some areas that require improvement. Further assessment of the quality of infection prevention and control program components, such as content of education and training, and policies and procedures, and ongoing evaluation of programs is recommended. Geriatr Gerontol Int 2024; 24: 358-363.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".