Knowledge and Practice of Healthcare Personnel Regarding Disinfection and Sterilization of Surgical Instruments at a Tertiary Level Hospital in Rajshahi
Bibliographic record
Abstract
Background: The process of sterilization involves eliminating or completely destroying all germs, including bacterial spores. Controlling and preventing infections is a crucial component of providing safe patient care. Objective: The objective of this study was to assess the knowledge and practice of healthcare personnel regarding disinfection and sterilization of surgical instruments at tertiary level hospitals in Rajshahi. Methodology: This cross-sectional type of descriptive study was conducted over a period of 1 year in the Department of Community Medicine, Rajshahi Medical College, Rajshahi. In this study, study population was healthcare personnel who were working in different tertiary level hospitals in Rajshahi. The knowledge and practice of healthcare personnel regarding disinfection and sterilization of surgical instruments were done by semi-structured questionnaire with score 1 for Yes and 0 for No answer. Health Care Workers (HCWs) score equal to or above 50% were considered having safe knowledge and instrument processing practice (IPP) and score below 50% having unsafe knowledge and IPP on disinfection and sterilization of surgical instruments. The data were analyzed via SPSS (version 24.0) and p < 0.05 was considered statistically significant. Result: The study population included 236 healthcare workers, of which 142 (60.2%) had safe knowledge and 94 (39.8%) had unsafe knowledge, while, 131 (55.5%) were practicing safely and 105 (44.5%) were practicing unsafely. The majority of healthcare workers with safe knowledge and practice were in the age range of 20-25 years. The relationship between healthcare workers’ knowledge and practice with age, sex, marital status, professional status, working departments and duration of service were not statistically significant ( p > 0.05 each). On the other hand, the relationship between healthcare workers’ infection prevention training, awareness on infection prevention, availability of poster, standard operating procedure (SOP) or guideline and vaccination against hepatitis B were statistically significant ( p < 0.05 each). Conclusion: The findings of this study indicated that the way medical staff members clean and store equipment was unsafe. HCWs must be more knowledgeable about infection prevention and control (IPC) and possess superior operational abilities if healthcare facilities are to be free of infections. Northern International Medical College Journal Vol. 15 No. 1-2 July 2023-January 2024, Page 655-659
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".