Stratified Random Sampling

To ensure representation across different patient groups, I would use stratified random sampling. This involves dividing the patient population into subgroups (strata) based on relevant characteristics such as:

• Department: (e.g., cardiology, oncology, pediatrics)
• Age: (e.g., 18-35, 36-55, 56+)
• Visit Type: (e.g., inpatient, outpatient, emergency)

Then, I would randomly select patients from each stratum to participate in the survey. This ensures that the sample reflects the diversity of the patient population and allows for analysis of satisfaction levels within specific groups.

Strengths:

• Representative Sample: Ensures that all subgroups are represented in the sample, reducing bias and increasing the generalizability of the results.
• Stratum-Specific Analysis: Allows for the identification of areas where specific patient groups may be more or less satisfied.
• Precision: Can lead to more precise estimates of overall patient satisfaction compared to simple random sampling.

Weaknesses:

• Complexity: Requires careful planning and execution to identify relevant strata and ensure proper randomization within each stratum.
• Cost: May be more expensive and time-consuming than other sampling methods due to the need for stratification and separate sampling within each group.
• Sample Size: May require a larger overall sample size to achieve sufficient representation within each stratum.

Additional Considerations:

• Survey Instrument: The survey itself should be carefully designed to elicit honest and informative feedback from patients.
• Data Collection: Consider using multiple methods for data collection, such as online surveys, paper questionnaires, or phone interviews, to maximize participation rates.
• Ethical Considerations: Ensure that patient participation is voluntary and that their responses are kept confidential.
• Analysis: Use appropriate statistical methods to analyze the data and identify key areas for improvement in patient satisfaction.

By using stratified random sampling and carefully considering the above factors, the healthcare facility can obtain valuable insights into patient satisfaction and make data-driven decisions to improve the quality of care.