The association between survey timing and patient-reported experiences with hospitals: results of a national postal survey
Department for Quality Measurement and Patient Safety, Norwegian Knowledge Centre for the Health Services, Oslo, Norway
BMC Medical Research Methodology 2012, 12:13 doi:10.1186/1471-2288-12-13Published: 15 February 2012
Research on the effect of survey timing on patient-reported experiences and patient satisfaction with health services has produced contradictory results. The objective of this study was thus to assess the association between survey timing and patient-reported experiences with hospitals.
Secondary analyses of a national inpatient experience survey including 63 hospitals in the 5 health regions in Norway during the autumn of 2006. 10,912 (45%) patients answered a postal questionnaire after their discharge from hospital. Non-respondents were sent a reminder after 4 weeks. Multilevel linear regression analysis was used to assess the association between survey timing and patient-reported experiences, both bivariate analysis and multivariate analysis controlling for other predictors of patient experiences.
Multivariate multilevel regression analysis revealed that survey time was significantly and negatively related to three of six patient-reported experience scales: doctor services (Beta = -0.424, p< 0.05), information about examinations (Beta = -0.566, p < 0.05) and organization (Beta = -0.528, p < 0.05). Patient age, self-perceived health and type of admission were significantly related to all patient-reported experience scales (better experiences with higher age, better health and routine admission), and all other predictors had at least one significant association with patient-reported experiences.
Survey time was significantly and negatively related to three of the six scales for patient-reported experiences with hospitals. Large differences in survey time across hospitals could be problematic for between-hospital comparisons, implying that survey time should be considered as a potential adjustment factor. More research is needed on this topic, including studies with other population groups, other data collection modes and a longer time span.