RT Journal Article SR Electronic T1 Patient evaluation of hospital outcomes: an analysis of open-ended comments from extreme clusters in a national survey JF BMJ Open JO BMJ Open FD British Medical Journal Publishing Group SP e004848 DO 10.1136/bmjopen-2014-004848 VO 4 IS 5 A1 Hilde Hestad Iversen A1 Øyvind Andresen Bjertnæs A1 Kjersti Eeg Skudal YR 2014 UL http://bmjopen.bmj.com/content/4/5/e004848.abstract AB Objectives A recent study identified patients in six distinct response groups based on their evaluations of outcomes related to overall satisfaction, malpractice and benefit of treatment. This study validates the response clusters by analysing and comparing open-ended comments from the extreme positive and extreme negative response groups. Design Qualitative content analysis. Setting Data from open-ended comment fields provided by patients who completed a national patient-experience survey carried out in Norway in 2011. 10 514 patients responded to the questionnaire and 3233 provided comments. A random sample of 50 open-ended comments from respondents representing cluster 1 (‘excellent services’), cluster 5 (‘services have clear improvement needs’) and outliers (‘very poor services’) was reviewed. Results 3 distinct patient profiles were identified. More than half of the comments in cluster 1 included descriptions of positive healthcare experiences, one addressed patient safety issues. Only 1 of the comments in cluster 5 was positive, and 12 were related to safety. All comments from the outliers were negative, and more than three-quarters reported experiences related to malpractice or adverse events. Recurring themes did not differ significantly between the three respondent groups, but significant differences were found for the descriptions and severity of the experiences. Conclusions Patients in negative response groups had distinct and much poorer healthcare descriptions than those in the extreme positive group, supporting the interpretation of quality differences between these groups. Further research should assess ways of combining statistical cluster information and qualitative comments, which could be used for local quality improvement and public reporting.