Planning for Data Collection
Data Collection in Patient Satisfaction Surveys
Quality improvement is a systematic strategy “to improve practices and processes within a specific organization” (Polit & Beck, 2017b, p.741). Many quality improvement studies, specifically patient satisfaction, are measured via surveys. A survey of four different tertiary care hospitals in four different countries found that various attributes and aspects of nursing care and easy access of care were the strongest drivers of patient satisfaction as a whole, as compared to physician relations, admission process and environmental cleanliness (Al-Abri & Al-Balushi, 2014). Primary care settings may measure satisfaction through similar criteria. Various data collection aspects of patient satisfaction measurement from a suburban primary care setting population are the focus of this paper.
Scenario and Survey Questions
Employees of a suburban primary care clinic, seeing 10,000 patients annually are interested in patient satisfaction. The healthcare organization has chosen to implement a satisfaction survey focusing on the areas of ease of access, wait time, friendliness of staff, and likelihood of recommending the clinic to others. The following questions was chosen for the patient satisfaction survey in the primary care clinic
1. How satisfied were you with the ease of setting up an appointment?
1 2 3 4
Very dissatisfied Dissatisfied Satisfied Very Satisfied
2. How satisfied are you with obtaining answers to questions during off hours?
1 2 3 4
Very dissatisfied Dissatisfied Satisfied Very Satisfied
3. How satisfied are you with the wait time in the office before seeing your provider?
1 2 3 4
Very Dissatisfied Dissatisfied Satisfied Very Satisfied
4. How satisfied are you with the attentiveness of the staff to your need?
1 2 3 4
Very dissatisfied Dissatisfied Satisfied Very Satisfied
5. How would you rate the ease of entry to our office (parking, location, hours)?
1 2 3 4
Very dissatisfied Dissatisfied Satisfied Very Satisfied
6. Would you recommend our office to a friend or family member?
1 2 3 4
Probably not Not sure Likely Very Likely
7. Age of the patient__________
8. Male/Female ___________
9. Name of Physician/Care Provider______________________
10. Please indicate if you are a new patient or returning patient___________
Comments:
Sample Size and Participant Selection
According to Polit and Beck (2017c), a representative sample is one containing characteristics closely related to those of the population. Since this is a quality improvement study and a wide variety of patient opinion is requested, a consecutive sample of 50 fully completed surveys per provider will be the goal for this study (Ross, 2016, March 1). Users will be asked to complete the paper and pencil survey upon check in to the office for an appointment. Each participant’s name will be entered into a drawing to win a $50 Visa gift card as an incentive to complete the survey in its entirety.
Reliability and Validity
In a primary care setting multiple confounding variables can affect the quality of study results. In this situation, statistical control would be used to manage confounders such as age, gender, time of care under specific physician, amid others (Polit & Beck, 2017a). For example, one aged 20-29 years may be visiting for a yearly physical or simply the flu and have few if any complaints about the waiting room time or convenience of the office. Whereas, someone aged 75+ years and accompanied by a family member, who is taking diuretics and has mobility issues might have difficulty waiting without the need to access the restroom, or walking a great distance through the parking lot to access the building itself.
Systematic bias involves an over or under representation of a particular attribute related to the research question (Polit & Beck, 2017c). For example, internet surveys can be biased since some may not have access or have a comfort in the use of a computer. Non-response or extreme response biases are another trouble spot for self report studies. Having patients complete the survey at the office will likely assure the greatest number of responses. Social desirability response bias is the tendency of individuals to misrepresent by answering questions in accordance with publicly desirable responses (Polit & Beck, 2017a). To ensure anonymity, patients will be provided an envelope in which the survey can be placed, once completed, and dropped into a survey box in the office lobby. No patient identifiers will be placed on the questionnaire.
The tool’s reliability is achieved statistically by measuring the number of questions addressing each criterion (easy of access, wait time, friendliness of staff, and recommendation to others). In a reliable survey, several different questions would address ease of access. Several more would address wait time. Each question would speak to a different aspect of the criterion being measured. Consistent patient responses to varying questions of the same area of measurement are a reliable indicator of the survey’s strength (U.S Department of Education, n.d).
Conclusion
While quality improvement projects are research-like and not actual research, such endeavors are a necessary part of health care organization survival (Polit and Beck, 2017d). Patient satisfaction surveys identify areas to improve patient outcomes and maintain customer loyalty. By taking action to close gaps, patients breathe a bit easier knowing the customer’s voice is being heard. Health care quality improvement specialists adept at such skills can support the effort and increase the implementation of evidenced based practice, for the unending process of patient satisfaction.
References
Al-Abri, R., & Al-Balushi, A. (2014). Patient satisfaction survey as a tool towards quality improvement. Oman Medical Journal, 29(1), pp. 3–7. http://doi.org/10.5001/omj.2014.02
Merrill, K. (2015). Is this quality improvement or research? American Nurse Today, 10(4). Retrieved from https://www.americannursetoday.com/quality-improvement-research/
Polit, D. F., & Beck, C. T. (2017a). Data collection in quantitative research. In Polit, D. F., & Beck, C. T. Nursing research: Generating and assessing evidence for nursing practice (pp. 266-296). (10th ed.). Philadelphia, PA: Wolters Kluwer
Polit, D. F., & Beck, C. T. (2017b). Glossary. In Polit, D. F., & Beck, C. T. Nursing research: Generating and assessing evidence for nursing practice (pp. 719-748). (10th ed.). Philadelphia, PA: Wolters Kluwer
Polit, D. F., & Beck, C. T. (2017c). Sampling in quantitative research. In Polit, D. F., & Beck, C. T. Nursing research: Generating and assessing evidence for nursing practice (pp.249-265). (10th ed.). Philadelphia, PA: Wolters Kluwer
Polit, D. F., & Beck, C. T. (2017d). Specific types of quantitative research. In Polit, D. F., & Beck, C. T. Nursing research: Generating and assessing evidence for nursing practice (pp. 236-247). (10th ed.). Philadelphia, PA: Wolters Kluwer
Ross, R. (2016, March 1). Determine provider-level sample sizes for patient satisfaction surveys. Retrieved from http://www.mgma.com/practice-resources/mgma-connection- plus/mgma-connection/2016/march-2016/determine-provider-level-sample-sizes-for- for- patient-satisfaction-surveys
U.S. Department of Education. (n.d.). Judging the reliability of a survey. Retrieved from https://www.evaluationtoolkit/system/resources/87/original/531_tool_judging.doc?...
