Description
Hello
I need to post 6 comments to my peers. Responses to peers or faculty should be 150 min words and include one reference.
Comment 1:
In a healthcare facility, cluster sampling for a patient satisfaction survey involves dividing the facility into distinct clusters or groups, such as different departments, floors, or units. From each cluster, a random sample of patients or encounters would be selected to participate in the survey. For instance, if the facility has various departments like cardiology, pediatrics, and orthopedics, each could be considered a cluster, and a subset of patients from each department would be surveyed.
Strengths of cluster sampling in this scenario include its logistical convenience. It simplifies the process by organizing participants into manageable clusters, especially in large healthcare settings (Su & Ding, 2021). It can also potentially reduce costs and time compared to individually surveying every patient. Additionally, it can provide insights into specific areas or departments within the facility, allowing for targeted improvements based on departmental feedback.
However, there are some weaknesses to consider. One drawback is the potential for intra-cluster homogeneity, meaning that individuals within the same cluster might share similar characteristics or experiences (Gupt et al., 2021). For example, patients within a specific department might have similar opinions due to the nature of their conditions or treatments, which might not represent the broader patient population accurately. Another challenge is that cluster sampling might lead to less precise results compared to other methods like simple random sampling, especially if there is high variability between clusters.
Despite these limitations, cluster sampling remains a valuable method in healthcare settings due to its practicality and ability to provide insights into specific areas. Complemented with careful consideration of cluster selection and its potential limitations, it can still offer valuable information for improving patient satisfaction within various sections of a healthcare facility.
Comment 2:
Stratified Sampling is the modification of simple random that requires the condition of sampling frame being available. This method involves dividing a population into homogenous subgroups known as strata (Emfil, et al., 2017). Conducting patient satisfaction survey in health care facility, the stratified sampling method would be applied by dividing the entire population into distinct subgroups or strata based on certain characteristics or attribute then randomly selecting samples from each of these strata such as Age groups (For example , Children, adults, seniors), Type of service received ( Inpatient, outpatient , emergency) Health condition (chronic diseases, acute illness). Once the strata are defined, a simple sample is taken from each stratum to ensure that each subgroup is adequately represented in the survey.
Strengths and Weaknesses of the Stratified Sampling
Strength: Stratified sampling can provide higher accurate results than simple random sampling, especially when the strata are well-defined and significantly different from each other (Linkedin 2024). It ensures that subgroups within the population are represented in the sample which is particularly useful when some subgroups are small.
Weaknesses: Stratified sampling can be more complex and time consuming than simple random sampling (Linkedin, 2024) . It requires a good understanding of the population and careful definition of the strata. It can be more costly specially if the strata are geographically dispersed or difficult to access.
Comment 3:
Random Sample is when members from the population are selected in such a way that each individual member has the same chance of being selected (Visual Learner). Random Sampling is when members of the population are selected at random to make the choice equal for all participating individuals. The is no way to increase the likelihood of being selected. Patient satisfaction surveys are something that hospital administrators use as feedback. Over the past 20 years, patient satisfaction surveys have gained increasing attention as meaningful and essential sources of information for identifying gaps and developing an effective action plan for quality improvement in healthcare organizations (Al-Abri & Al Balushi, 2014). I would leave patient survey cards in ever patients room, and upon discharge from the hospital when going home. I would also make them available throughout the hospital in on stands. There would be no place for name or identification.
Top of Patient Survey Card: Please rate your hospital stay on a scale from 1-10. 1 being horrible and 10 being the best. The card would have 5 questions on it. Pencils and a solid writing stand would be available as well. The following questions would be listed on the survey card on a scale from 1-10.
First Question: How was the cleanliness of your room?
Second Question: How was your interaction with the doctor?
Third Questions: How was your interaction with the nurse?
Fourth Question: How was your wait time?
Fifth Questions: How would you rate your overall stay?
Strengths of the use of my plan is that the selections would all be at random. The would support that it gives a fair chance for all people to provide feedback. Weaknesses of this survey card would be the current mental health of the patient and language barriers. Other weaknesses are the identification of who is the doctor and who is the nurse can sometimes get mixed up. Personal bias may also get I the way of this survey.
Comment 4:
As my assigned sampling method is Cluster Sampling, I would apply it in the following way for the patient satisfaction survey at my healthcare facility. Firstly, I would divide the patients based on different wards or departments in the healthcare facility, and then randomly select a few clusters of patients from each ward or department. After selecting clusters, I would further divide them into subgroups, such as age, gender, treatment type, and other relevant criteria. Finally, I would randomly select a few participants from each subgroup to get a representative sample of patients from each ward or department.
The strengths of cluster sampling in this scenario are that it is an efficient method to gather data from a large population. By dividing the patients into clusters, the survey can be conducted more easily, quickly, and cost-effectively. It also provides a more representative sample of patients from different departments or wards in the healthcare facility. Furthermore, cluster sampling ensures that the sample size is appropriate for each subgroup, making it easier to analyze the data and conclude.
However, the weaknesses of cluster sampling are that it may not be ideal for small healthcare facilities with limited departments or wards. It can also lead to bias if the clusters are not selected randomly or are not representative of the population. Additionally, it may not provide a detailed analysis of each department or ward, making it challenging to identify specific issues and improve patient satisfaction.
Comment 5:
A random sample is when members of the population are selected in such a way that each individual member has the same chance of being selected. (Random-Sample, n.d.)
All patients who have lately used the services of the medical facility would constitute the population in this example. Random sampling is the process of choosing a subset of patients at random from the sampling frame. Depending on their preferred method of communication, patients are contacted by phone, email, or in-person visit after the random sample has been determined to take part in the satisfaction survey. Gather information about how satisfied they are with the services provided by the medical facility, then evaluate the findings. When doing a research study, we should consider the sample to be representative to the target population, as much as possible, with the least possible error and without substitution or incompleteness. (Elfil & Negida, 2017)
Strengths: Because each patient has an equal chance of being selected for the survey, random sampling helps ensure that every patient in the community has an equal chance of being chosen for the survey and reduces the possibility of bias in the selection process.
Weaknesses: If the patient group is vast, random sampling may require a substantial investment of time, money, and effort.
To ensure actual variability, random sampling needs to be carefully planned and carried out, which can be difficult in practice. Despite these disadvantages, random sampling is still one of the most reliable techniques for gathering data from patient satisfaction surveys since it contributes to the validity and dependability of the findings.
Comment 6:
After watching the three required videos on the Visual Learner resource and inputting my Random.org numbers, the set of numbers I chose from the selection was: 1, 4, 9, 14, 18
What was the mean?
The mean is the average. You achieve this by adding all the number together, then take the sum of those numbers and divide by the number of scores used (Visual learner. (n.d.-a).
1 + 4 + 9 + 14 + 18 = 46/5 = 9.2 is the mean
What was the median?
The median is the exact center of the data. Half of the data is the left and other half is on the right. To achieve this, place the numbers from smallest to largest, then if you have an even number of numbers, then you find the halfway of the middle two numbers, if you have an odd number of numbers, then its the middle number halfway between the lowest numbers and highest numbers (Khan Academy).
9 is the median, which is halfway between 1, the lowest number and 18, the highest number.
What was/were the mode/s?
The mode is the number or sometimes multiple numbers that occurs most frequently, or “Bimodel” if two numbers occur frequently and repeat in the sequence or “Multimodel” where more than two numbers occur frequently and repeat. If no numbers repeat, then there is no mode (Visual learner. (n.d.-a).The is no mode, because none of the numbers occur more than once.
Given that the range of data was between 1 and 20, what do these numbers tell you about the overall satisfaction of the patients?
Given that the range of patients was from 1 and 18, this information tells me that half of the patients, or 9.2 of them were satisfied out of 18 people.
If you were reporting these scores back to your supervisor, how would you explain or interpret these satisfaction scores?
We sent out a patient satisfaction survey to 18 people. After reviewing the survey scores, we noticed that half, or 9 of the individuals were satisfied, and there other half was not satisfied.
