Assignment Instructions:
Read a selection of your colleagues’ responses and respond in one or more of the following ways:
Ask a probing question, substantiated with additional background information, evidence, or research.
Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
Offer and support an alternative perspective using readings from the classroom or from your own research in the Walden Library.
Validate an idea with your own experience and additional research.
Suggest an alternative perspective based on additional evidence drawn from readings or after synthesizing multiple postings.
Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.
NOTE: PLEASE!!! Use APA 7th Edition and no references older then 5 years and each Colleague needs 2 references that makes it a total of 4 references. PLEASE! DO NOT combine the References together, each colleagues should have there own references that follows after there response. Thank you!
Colleague #1
One healthcare delivery problem that can be explored using correlational statistics is the relationship between nurse staffing levels and patient outcomes in hospitals. The research question formulated to address this problem is: “Is there a correlation between nurse-to-patient ratios and patient recovery rates in hospital settings?”
The null hypothesis (H0) would be: “There is no significant correlation between nurse-to-patient ratios and patient recovery rates in hospital settings.” The alternate hypothesis (H1) would be: “There is a significant correlation between nurse-to-patient ratios and patient recovery rates in hospital settings.”
This study’s independent variable is the nurse-to-patient ratio, while the dependent variable is the patient recovery rate. It is hypothesized that these variables will have a positive correlation, suggesting that higher nurse-to-patient ratios (more nurses per patient) will be associated with better patient recovery rates. This prediction is based on the premise that increased staffing allows for more personalized care and quicker response times, potentially leading to improved patient outcomes (Haegdorens et al., 2019).
Other factors that might affect the outcome include the severity of patients’ conditions, hospital resources, and the quality of nurse training. For instance, hospitals with more severe cases or limited resources might show different correlations than those with milder cases or abundant resources. Moreover, differences in nurse training and hospital policies can also play a crucial role in influencing patient outcomes (Griffiths et al., 2019). Understanding these dynamics is essential for improving healthcare delivery and patient care, ensuring hospitals can make informed decisions about nurse staffing policies.
Colleague #2
According to the research (Pramesh & Ranganathan, 2019) the null hypothesis is the statement or claim being made (which we are trying to disprove), and the alternative hypothesis is the hypothesis that we are trying to prove and that is accepted if we have sufficient evidence to reject the null hypothesis. According to Pernet (2016) they work as a complementary pair, each stating that the other is wrong.
My focused practice problem is increased cases of hospital-acquired infections among adults. The null hypothesis would be there is no relationship between the rates of whether a patient develops hospital-acquired infections (HAIs) and whether they receive chlorohexidine gluconate solution (CHG) baths or prophylactic antibiotics.
The independent variable: the rate of patients developing hospital-acquired infections. There are a few dependent variables: the patient receives CHG baths, the patient doesn’t receive CHG baths, the patient receives prophylactic antibiotics, and the patient doesn’t receive prophylactic antibiotics. My prediction is the rate of patients developing hospital-acquired infections is lower in patients who receive prophylactic antibiotics compared to those who don’t, and the rate of patients developing hospital-acquired infections is lower in patients who receive CHG baths compared to those who don’t. Therefore the relationship between the dependent and independent variable is a negative relationship. The reason why I predicted this is because CHG solution is an antiseptic antibacterial agent. It’s usually used to clean surfaces like hands or body areas before surgery or a procedure. When it’s used on the skin, it kills and prevents the growth of bacteria on the skin. According to Musuuza et al. (2019) there is a significant reduction in the risk of developing hospital-acquired infections when the patients receive treatment with either CHG baths or CHG wipes. Prophylactic antibiotics are antibiotics taken to prevent infection. They can be used for many reasons, such as before surgery or dental procedures. After a bite or a wound or for people with certain health problems, for example, for people who are prone to infections such as after chemotherapy or certain heart conditions. Or for patients with chronic conditions such as frequent flare-ups of chronic obstructive pulmonary disease (COPD), recurrent urinary tract infections (UTI), or skin infections.
Some factors can also affect the outcome. For example, depending on the unit’s standard protocol of infection prevention, the unit might already have a low rate of patients developing HAIs. The unit might practice universal hand washing, disinfect green caps at the end of IV ports, and have routine protocols for changing out Foley catheters and IV dressing. All of which can help decrease the risk of developing HAIs. Or the unit might have a population that is more prone to HAIs, for example, patients who receive chemo or radiation treatments. Or who have had a procedure and are not ambulatory, for example, older adults with hip or knee replacement. The unit’s standard infection control protocol, patients’ age, immune response, and whether or not they just had a procedure could all be factors that might change the outcome and affect the research results.
