If you're inclined to answer “false,” you might choose from any number of objections. Perhaps you're not convinced the data are reliable. Perhaps you don't believe the results justify the costs. Or perhaps you don't want to be measured simply for the sake of being measured. All are legitimate concerns, but, as you'll see, they can be overcome. The truth about patient satisfaction surveys is that they can help you identify ways of improving your facility. Ultimately, that translates into better care and happier patients. “Unless a facility is not interested at all in information, a patient satisfaction survey can be useful, and it shows your staff and the community that you're interested in quality. It demonstrates that you are looking for ways to improve.

If that's not enough of a reason to push you nearer to the point of surveying your patients, consider this: Whether you think patient satisfaction surveys are good or bad, the fact of the matter is that the marketplace you work in is demanding that data on patient satisfaction be used to empower consumers. As many facilities know if they do not get on board and try to make the data as good as possible and get their scores as high as possible, they are going to be hurt in the marketplace.

•A patient satisfaction survey can demonstrate that a practice is interested in quality and in doing things better.
•When choosing (or designing) a survey questionnaire, look for three things: brevity, clarity and consistency.
•Even an in-house survey can be statistically correct if practices stick to some basic rules.

STATISTICAL CORRECTNESS One of the main criticisms of patient satisfaction surveys is that their results are not reliable. It's true that not all surveys meet the standards for statistical reliability. But you can, if you stick to these guidelines. Sample size. When you distribute your questionnaire, try to survey the largest group possible. Response rates. Thirty percent to 35 percent is a typical response rate for a mailed survey, where Care Analytics Tablet based assessments have a 99% response rate. Number of responses. An adequate response rate is important, but what trumps that is the number of responses you receive. If you've managed to get a 40 percent response rate on your survey, but you've surveyed only 100 patients, don't kid yourself that you have enough data to draw meaningful conclusions. The more responses you can get, the more valid and reliable your results are likely to be..

ANALYZING THE DATA. Analyzing the data may be the most complex part of the survey process. Usually, you can get a survey put together in-house, you can get a database of people you want to send it out to, and you may happen to come up with a reasonable response rate. The primary challenge emerges when the completed surveys are returned. If you don't have someone in-house with strong analytic and database-management skills, you are prone to end up with a stack of surveys that are never analyzed adequately. That's where you're going to get the meaning and the value out of it. If your facility does not have the time or resources to analyze your survey data, consider outsourcing this step to a firm that specializes in health care data analysis. WHAT DO I DO WITH THE RESULTS? While you don't have to act on every suggestion that your patients give you, you should take action on the key items that are causing dissatisfaction. Remember that your goal is to improve quality, not to place blame.


Care Analytics is a tablet-based software that assesses skilled nursing facilities and provides feedback to make quality improvements for patient satisfaction in real time. To advance the patient experience, providers must understand patient needs and address targeted opportunities within patient populations. Care Analytics provides meaningful and actionable insights into every aspect of patient perception. We work with facilities across the globe to collect feedback through real-time point of care tablet based assessments. We provide straight-forward steps focusing on the key drivers of exceptional patient experiences. Our model is based on the marriage of big data and years of experience with improving patient satisfaction