Impacts of Hospital Acquired Infections among Cancer Patients in Critical Care Unit.

Impacts of Hospital Acquired Infections among Cancer Patients in Critical Care Unit.

Introduction.

The hospital acquired infections are of great concern when it comes to the treatment of critically ill patients. This may be related to the nature of treatment that usually requires an extended period of stay as well as having very many invasive equipment and procedures. A study by Cornejo-Juárez et al., 2015 aimed to describe site-specific hospital-acquired infections rates and the microbiological and antibiotic resistance profiles for the infecting pathogens. T6his is a non-experimental study but retrospective in nature since it depends on the existing data.

Methods.

The study was a 5-year retrospective descriptive on the hospital-acquired infections for intensive care unit (ICU patients between the period of January 2007 to December 2011.This was done in The National Cancer Institute of Mexico within the Mexico city. The researchers used data obtained from the microbiology laboratory reports, patient medical charts, ICU daily reports and the patients’ medical charts. The information that was of significance was patient characteristics and comorbidities, information concerning neoplasm and the treatment, resistance pattern of isolates and microbiology.

Analysis.

The statistical variables were compared by use of the chi-square test and the Fisher test. The continuous data were analyzed via the method of the u-tests and the t-test with use of 95% level of confidence.

 

Discussion.

There exists high incidence with patients receiving multimodal with chemotherapy, radiotherapy, surgery and targeted therapies which have prevented remission and cure. The risk of infection with the multi-drug resistant was associated with the cross-transactional, previous antimicrobial activity and length of stay in the hospital. The patients who were having the multidrug-resistant experienced high mortality rate in comparison to the other non-cancer patients. This extends in the

Sampling method.

In this retrospective study, quota sampling method was used. In this method, a predetermined number of cases Rare selected over a specific period from each the site of the diagnostic determinant (Dunemn et al., 2016). Like in the study, the patients were admitted and relevant information taken with entry into the study marked by legibility. This was done to the 1418 patients that were admitted between 2007 and 2011.

Variables.

The independent variable, in this case, was the cancerous infection that formed the diagnosis besides being the cause of critical illness. The dependent variable was the mortality rate or the level of mortality that could be influenced by cancer as the original condition or the comorbid conditions from hospital-acquired infections.

 

 

Data collection methods.

The researchers used document review method of data collection were reports on patients information was recorded and used to facilitate the study (Ott and Longnecker, 2015). The information revolved around the characteristics of comorbid patient conditions, data about neoplasm and its treatment and resistance pattern among the isolated patients. At the same time, length of stay in the unit, number of ventilator days, days of the cardiovascular catheter and urinary catheter days were also taken into account.

Interventions.

Following the results of the study that placed the existence of 159 infections in 134 patients and the overall incidence of hospital-acquired infections being at 11.2%, programs were put in place to promote antimicrobial stewardship as well as monitoring of antimicrobial resistance. The above moves have also been enhanced since 2011.

Part 2.

The scenario provided is a descriptive study because it describes the characteristics of community A and B concerning lifestyle and practices such as health-seeking behavior. At the same time, the study is not able to explain why, how and when the identified characteristics occur but is only able to single them out to be having a toxic chemical plant, high rates of cigarette smoking, poor health-seeking behavior in community A and community B also having poor health-seeking behavior but with low rates of tobacco smoking(Yin, 2013).

The researcher collected information concerning lifestyle of the residents to determine if there exists a relationship between the way of living and the occurrence of cancer since this is also a lifestyle condition. The researcher also collected information related to the businesses in each community to determine if any of them had an environmental health risk that would predispose any of the communities to the cancer development. The medical records could also provide vital information on the most common condition in the two areas. This was however challenging as both the communities had poor health-seeking behavior.

In community A, the researcher cannot establish that present of chemical plant and cigarette smoking are the cause of higher rates of cancer among the residents because he cannot back up such claim with evidence. This is so because this study is of descriptive design and such evidence and data could only be obtained from the medical records which are also not available since the community has a poor health-seeking behavior (Woodward, 2013). This provides less substantial data to support the claim.

Similarly, the investigator cannot establish that lower smoking and absence of chemical factory leads to the lower rates of cancer since this cannot be supported by data evidence. This is so because the community does not adhere to the frequent medical checkup which would have provided data and information on the most common conditions handled as well as detailed information that would have brought the relationship amongst the variables.

 

 

 

References:

Dunemn, K. N., Roehrs, C. J., & Wilson, V. L. (2016). Critical appraisal and selection of data

collection instruments: A step-by-step guide. Journal of Nursing Education and Practice,

7(3), 77.

Ott, R. L., &Longnecker, M. T. (2015). An introduction to statistical methods and data analysis.

Nelson Education.

Woodward, M. (2013). Epidemiology: study design and data analysis. CRC press.

Yin, R. K. (2013). Case study research: Design and methods. Sage publications.

 

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