Practice Problem: The rate of nosocomial infections amongst dialysis patients is a rapidly growing population. Solution: Will frequent handwashing in chronic hemodialysis patients and direct patient care staff assist in the prevention of nosocomial infections?
Null Hypothesis: There was no change in the number of nosocomial infections between frequent handwashing in chronic hemodialysis patients and direct patient care staff.
Alternate Hypothesis: Increased handwashing in dialysis patients and direct patient care staff will assist in the prevention of nosocomial infection.
Independent variable: Dialysis patient and direct patient care staff.
Dependent variable: Increased frequency of handwashing
Prediction: The rate of nosocomial infections amongst dialysis patients is a rapidly growing population. not requiring hemodialysis (Agata., Mount., & Schaffner, 2000). To identify the risk factors for acquiring a nosocomial infection among hemodialysis patients, a matched case-control study must be conducted (Agata., Mount., & Schaffner, 2000). The Plan, Do, Study, Act (PDSA) model can be applied to assist with frequent handwashing. The objective of the cycle will be stated explicitly. Preliminary work must be completed to assist with recruitment and establishment in practice setting, which will involve stakeholder engagement (McQuillan et al., 2016). The details will be clearly defined detailing the proposed change and its implementation as part of the planning process (McQuillan et al., 2016). The measurement of success will assist standardizing the intervention and data collection components of the PDSA cycle, which will ultimately improve the quality of the change intervention process (McQuillan et al., 2016). The prediction concludes that frequent handwashing in the dialysis patient and direct patient care staff will decrease hospital admission for nosocomial infection by 1% annually.
Agata, E., Mount, D., & Schaffner, T. (2000). Hospital-acquired infections among chronic
hemodialysis patients. National Library of Medicine. 35(6): 1083-8.
McQuillan, R., Silver, S., Harel, Z., Weizman, A., Thomas, A., Bell, C., Chertow, G., Chan,
C., & Nesrallah, G. (2016). How to measure and interpret quality improvement data.
Clinical Journal of the American Society of Nephrology. 11(5) 908-914.
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