The Quality-Cost Connection: Telling the patient satisfaction story
Telling the patient satisfaction story
Feedback should lead to service improvements
By Patrice Spath, RHIT
Brown-Spath & Associates
Forest Grove, OR
Many health care organizations are gathering feedback from patients to determine their satisfaction with health services. Armed with this information, senior leaders and managers can establish customer-driven process improvement priorities and make more informed process redesign decisions. Regular patient and family input on their needs, expectations, and experiences also enables the organization to measure whether it is increasing its ability to satisfy customers. The bottom line is that finding out what patients, families, and other stakeholders think about what the organization does and how it is done should lead to service improvements.
It is likely that your organization will be overwhelmed with the amount of information it receives from satisfaction surveys and other feedback mechanisms. This is especially true if the survey tool is lengthy or if there are a large number of open-ended comments. It can be challenging to aggregate and report the results in a manner that helps senior leaders determine what improvements should be done first, where improvement actions should be focused, and what enhancements are worth making.
To make the best use of patient satisfaction data, the results must be presented in a way that allows for accurate analysis. Depending on the methodology used to gather the data, the results may be represented as an average score or rating for various service aspects. Chances are, however, that the information also can provide a wealth of insights about how patients and other stakeholders view the services they have received from your organization.
An analytical approach that is very useful for evaluating satisfaction survey results is driver analysis. Driver analysis identifies the service or services that most significantly affect respondents’ satisfaction. Using multivariate analysis, the most important factors affecting satisfaction are identified. For example, the overall satisfaction rating is compared to levels of satisfaction for specific services to determine the degree to which variation in the overall level of satisfaction is explained by the variation in specific service ratings. Those individual factors or services that most adequately explain the variation in overall patient satisfaction are considered the drivers. By identifying the drivers of satisfaction, the organization can initiate changes patients and their families will most likely notice and value.
Driver analysis provides decision makers with a tool to prioritize the satisfaction survey results. The results are prioritized because customer feedback efforts often yield more information than a health care organization can deal with. Also, the organization may not have sufficient resources to address all aspects of service that receive low patient/family satisfaction ratings. Driver analysis enables the organization to identify which functions or services deserve the highest levels of attention.
To tell the story in customer satisfaction data, different techniques can be used. In the table beloware descriptions of the statistical techniques that most likely will meet all the needs and expectations of the decision makers charged with analyzing patient satisfaction data.
The following is a simple example of how feedback from a satisfaction survey might be analyzed: Suppose your organization’s patient satisfaction survey includes the question: "On a scale of 1 to 5, where 1 represents highly dissatisfied’ and 5 represents highly satisfied,’ how would you rate your satisfaction with discharge instructions?" Over a three month time period, 450 patients responded to this question.
If you were to tabulate all the scores, the average response would be the mean. Although the mean is a very important piece of information, there is a lot more you can do with the data. It is often useful to begin with a frequency distribution where you determine the number and percentage of respondents who gave each score between 1 and 5. One way to present that distribution is shown in the top box below.
Of the 450 patients responding to the survey question, 22 did not remember receiving discharge instructions, and 35 said they had no opinion or did not know how they would rate their satisfaction with the instructions.
In the example provided, the information about those who do not remember or have no opinion is presented separately to allow the decision makers to focus attention on those patients who did have an opinion to express. The percentage of those with opinions based on the 393 respondents is presented in column 3. However, if it is important to determine the percentage of patients who do not remember or have no opinion about the discharge instructions, the figures also are calculated using 450 — the total number of patients who were asked the question (column 4).
The information shown may be too detailed for some people in the organization. For instance, the difference between a 1 and a 2 rating may not be meaningful for them. Thus, it is useful to collapse the information into a smaller number of categories. One possibility is to create three categories: dissatisfied, neutral, and satisfied. (See box below)
If the data are being analyzed by individual services in hopes of finding improvement opportunities, it may be inappropriate to collapse the data because the difference between satisfied and highly satisfied is important.
However, if the information is to be used for high-level trend analysis, collapsing categories often can help make the information easier to grasp. The responsibility for producing meaningful reports falls to the quality manager. It is the manager’s task to identify sensible ways to collapse or expand categories according to the needs of the audience.
It is important to present patient satisfaction data as succinctly and clearly as possible.
Therefore, it may be best to present the survey results in a simple, straightforward manner to most audiences and save the mathematical details for an appendix or supplementary briefing. Graphic representations of data also are powerful ways to display findings. It is very easy for audiences to get the message when information is presented in bar graphs, pie charts, and similar data displays.
There is no reason to elicit patient feedback unless your organization plans to use the information to improve services. Patient and other customer feedback may suggest many potential improvements or enhancements to consider. Narrowing down the list to those that will have the most direct effects on overall customer satisfaction is the ideal.
Driver analysis can help senior leaders select those actions most likely to affect overall service satisfaction. While each organization must consider its own capacity for action, it is important to do something or patients may feel that their input was not valued or the effort they expended to respond was wasted.
To get leadership support for improvements, satisfaction results should be accurately reported and presented in a constructive way that emphasizes the positive.
Results, findings, and recommendations should be presented as opportunities for improvement — not for punitive purposes. If patient satisfaction surveys cannot be used to influence change or improvement, the feedback process did not meet its objective, no matter how carefully the survey was planned and carried out.
Many health care organizations are gathering feedback from patients to determine their satisfaction with health services. Armed with this information, senior leaders and managers can establish customer-driven process improvement priorities and make more informed process redesign decisions.
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