Quantitative Analysis Assignment

Quantitative Analysis Assignment

Summary Data Analysis Form

This is the form you need to use to describe the findings (or results) of your quantitative analyses of the patient safety data set. For each finding, you are given specific instructions on how to use the Excel program to analyze the data that will give you the results you need for this Assignment. When you have completed the analyses and described your findings on this form, you then need to submit it using the Week 5 platform for assignments.

Analysis 1:

What is the mean age of patients in the patient safety data set?

_54.8____ years

Instructions:

1. Open up your patient safety data set using the Microsoft Excel program.
2. At the top of your screen, click on “Formulas.”
3. Highlight Column B, starting at line 2 and ending at line 52..

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4. Click on “Autosum,” and then click on “Average.”
5. You will find the mean age of patients in the data set on line 52 for Column B.

Analysis 2:

What percentage of patients were reported to have fallen during their hospitalization?

__38___ %

Instructions:

1. Open up your patient safety data set using the Microsoft Excel program.
2. At the top of your screen, click on “Formulas.”
3. Highlight Column G, starting at line 2 and ending at line 52.
4. Click on “Sum.”
5. The number of patients in the data set who had reported falls during their hospitalization is now given on line 52 for Column G.
6. To calculate the percentage of patients who fell during their hospitalization, divide the number of falls by the total number of patients in the data set (n = 50).

Analysis 3:

What percentage of patients reported catheter-associated urinary tract infections (CAUTIs) during their hospitalization?

___24__ %

Instructions:

1. Open up your patient safety data set using the Microsoft Excel program.
2. At the top of your screen, click on “Formulas.”
3. Highlight Column H, starting at line 2 and ending at line 52.
4. Click on “Sum.”
5. The number of patients in the data set who reported CAUTIs during their hospitalization is now given on line 52 for Column H.
6. To calculate the percentage of patients with CAUTIs during their hospitalization, divide the number of CAUTIs by the total number of patients in the data set (n = 50).

Analysis 4:

What percentage of patients reported medication errors during their hospitalization?https://studygroom.com/analysis-and-interpretation-using-the-one-way-anova/

__30___ %

Instructions:

1. Open up your patient safety data set using the Microsoft Excel program.
2. At the top of your screen, click on “Formulas.”
3. Highlight Column I, starting at line 2 and ending at line 52.
4. Click on “Sum.”
5. The number of patients in the data set who reported medication errors during their hospitalization is now given on line 52 for Column I.
6. To calculate the percentage of patients with reported medication errors during their hospitalization, divide the number of errors by the total number of patients in the data set (n = 50).

Analysis 5:

What percentage of patients reported methicillin-resistant Staphylococcus aureus (MRSA) infections when first admitted to the medical unit?

_14____ %

Instructions:

1. Open up your patient safety data set using the Microsoft Excel program.
2. At the top of your screen, click on “Formulas.”
3. Highlight Column J, starting at line 2 and ending at line 52.
4. Click on “Sum.”
5. The number of patients in the data set who reported MRSA infections at the beginning of their hospitalization is now given on line 52 for Column J.
6. To calculate the percentage of patients with MRSA, divide the number of errors by the total number of patients in the data set (n = 50).

Data Analysis

Summarize the findings from your analyses about these patient safety events that occurred in 1 month on the two medical units at this major urban hospital. What additional information would you need to help develop a plan to decrease the occurrence of these events? The summary should consist of a minimum of 350 words and should be two to three paragraphs.

Summary

Descriptive analysis is essential in displaying general outlook of data. The summary statistics such as mean describe the underlying basic details of data. This paper uses mean and percentages to describe data on patient safety in hospitals. The mean age of the patients in the patient safety dataset is found to be 54.8 years. Thirty eight percent of patients in the dataset recorded to have fallen during hospitalization. Patients who reported catheter-associated urinary tract infections (CAUTIs) during their hospitalization were 24% of the entire patients in the dataset. Additionally, 30% of patients reported medication errors, where as 14% reported MRSA infections. The percentages of related outcomes of hospitalization need to be reduced through different mitigation measures.

There are several risk factors that could cause falls during hospitalization. Among the factors include, severe drug reactions, confusion, and gait instability (Gray et al. 2017). It is imperative to prevent mitigate the issue by proper medication by avoiding reactive drugs, risk assessments through systematic reviews, and use movement aids such as wheel chairs. Risk factors associated with CAUTIs include old age, insertion of catheter six days after hospitalization, not using the operating room to insert catheter, levels of serum creatinine greater than 2 mg/dL during catheter insertion (Qiaozhi et al. 2018). The percentage of patients reporting the infections is to be reduced by putting in place prevention measures such as adhering to hand hygiene strictly, using the operating room and proper machines during catheterization (Qiaozhi et al. 2018). Similarly, it is vital to enhance educational sessions to healthcare workers on the best drugs to use as antibiotic therapy for patients. Auditing of health workers on the antibiotic use can be useful in reducing cases of the infections (Qiaozhi et al. 2018).

Rampant medication errors on patients during hospitalization should also be prevented. Medication errors could be through dispensing, administering, and even monitoring of drug doses. Intervention strategies to the errors include proper communication among different healthcare staff and physicians. Likewise, pharmacists based to every ward will enhance improved administering and dispensing of drugs. The MRS infections during hospitalization can be reduced through proper hand hygiene. Other measures to prevent the infections are, cohorting and screening patients, vaccination and surveillance (Qiaozhi et al. 2018). The discussed measures will ensure reduced rates of infections to patients during hospitalization.

Reference

Gray, J. R, Grove, S. K., & Sutherland, S. (2017). The practice of nursing research: Appraisal,

Synthesis, and generation of evidence (8th ed.). St. Louis, MO: Elsevier.

Qiaozhi Hu et al. (2018). Adverse events identified by the global trigger tool at a university hospital: A retrospective medical record review.  Journal of Evidence-Based Medicine.