The variable selected for tracking at my workplace is the rate of patient fall as a function of time. Patient falls are common phenomena in hospitals caused by factors such as accidents, impaired cognition, bed rest medication treatments and unfamiliarity with the environment (Bouldin et al., 2013). Individual fall risks tend to vary within short periods. My study shows that the overall patient fall rate in my hospital after the first week of patient admission is 10.2 falls/1000 person-days. At a 95% confidence interval, the patient fall rate in the first week after admission is [10.181-10.219]. In other words, the study is 95% certain that the patient fall rate after the first week of admission falls between 10.181 falls/1000 person-days and 10.219 falls/1000 person-days. The overall patient fall rate after the second week of admission is 6.4 falls/1000 person-days, 95% CI (6.26-6.71]. The patient fall rate decreases with time. Calculating patient fall rate as a function of time shows that the risk of patient fall decreases with time. Therefore, patient fall prevention strategies ought to be increased during the first weeks after admission and relaxed as time goes by. Patient fall prevention programs could also prioritize most recently admitted patients.
Ideally, changing the CI to 90% will reduce the confidence that the patient fall rate lies within the interval selected. On the other hand, increasing the CI to 95% or 99% will increase confidence that the interval selected contains the hospital’s patient fall rate (Hazra, 2017). Therefore, 99% CI is most suitable for the present study. The hospital management should be informed that the patient fall rate after the first week of admission lies between 10.181 falls/1000 person-days and 10.219 falls/1000 per person-days at 95% CI, and decreases with time.
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References
Bouldin, E. L., Andresen, E. M., Dunton, N. E., Simon, M., Waters, T. M., Liu, M., Daniels, M. J., Mion, L. C., & Shorr, R. I. (2013). Falls among adult patients hospitalized in the United States: prevalence and trends. Journal of Patient Safety , 9 (1), 13–17. https://doi.org/10.1097/PTS.0b013e3182699b64
Hazra A. (2017). Using the confidence interval confidently. Journal of Thoracic Disease , 9 (10), 4125–4130. https://doi.org/10.21037/jtd.2017.09.14
