Research on the effect of survey timing on patients' evaluations of health services has produced contradictory results [3
]. This study found that patients report worse experiences for 3 of 6 patient-reported experience scales when survey time is longer. Individual response time was also negatively related to patient-reported experiences, so regardless of reason increasing time since discharge seems to result in poorer patient-experience scores.
Studies assessing the effect of survey time need to standardize the data-collection mode in order to avoid confounding time and mode effects. Almost all studies showing a worsening in patient evaluation over time changed the data-collection mode between the different measurements [6
]. Therefore, the timing effects might be related to the mode change rather than being actual timing effects. The current study standardized the data-collection mode and found a significant association between survey time and patient-reported experiences for three of the six scales. This is in line with the aforementioned studies, but contradicts another study from Switzerland in which the data-collection mode was also standardized [12
]. However, the Swiss study only included one hospital, a specific patient group and a relatively small sample. Consideration of all of the available data suggests that there is a negative association between survey timing and patient-reported experiences and satisfaction. However, more research is needed including studies with other population groups, other data-collection modes and a longer time span.
The first limitation of the current study relates to the distribution of the survey-time variable. The data-collection protocol means that most patients were sent a questionnaire 0-3 weeks after discharge, with a maximum of 41 days for individual patients. It would be useful to have knowledge about the potential effects of a longer time span, such as the effects of a model with surveys sent 1 month versus 2 months after discharge. The second potential limitation of the current study is the response rate. In general, postal surveys have lower response rates than other data collection modes [3
]. The response rate in the current study is in line with other Norwegian national patient experience surveys. Non-response bias occurs when the main variables differ systematically between respondents and respondents [22
]. In our study, the main question relates to differences between respondent groups, and hence non-response bias is of less concern. However, response rates might be lower in surveys with a longer time between discharge and postal mailing [12
]. Consequently, the association between survey timing and the response rate is an important consideration when designing data-collection procedures. A Swiss study found that the response rate was significantly lower for the 9-week group [12
] but not for the 5-week group, indicating that satisfactory results regarding response rate can be achieved with surveys mailed 0-5 weeks after discharge.
A third possible limitation of the study concerns its observational research design, causing uncertainty related to potential confounding variables. The gold standard for effect research is randomized trials, in which the aim is for only random variations to exist between study groups and for there to be a direct link between intervention and effect. However, a multicentre randomized trial on this topic would present large practical and methodological challenges, both regarding which time frames to use (intervention) and how to apply sample frames and randomization across hospitals. Another suitable design could have been a longitudinal approach, but that was not possible in this study. The present study adjusted for the most important sociodemographic predictors of patient experiences and patient satisfaction, reducing the probability of confounding effects related to variables not included. The study was based on data from all hospitals in Norway, and the survey-time variable was registered and analyzed as a continuous variable at the individual level. The former feature increased the external relevance of the study, and the latter gave the opportunity to use survey time in days in the analysis, providing more detailed information than only groups based on, say, weeks or months.