Background Patient experience surveys often include free-text responses. Analysis of these responses is time-consuming and often underutilized. This study examined whether Natural Language... Show moreBackground Patient experience surveys often include free-text responses. Analysis of these responses is time-consuming and often underutilized. This study examined whether Natural Language Processing (NLP) techniques could provide a data-driven, hospital-independent solution to indicate points for quality improvement. Methods This retrospective study used routinely collected patient experience data from two hospitals. A data-driven NLP approach was used. Free-text responses were categorized into topics, subtopics (i.e. n-grams) and labelled with a sentiment score. The indicator 'impact', combining sentiment and frequency, was calculated to reveal topics to improve, monitor or celebrate. The topic modelling architecture was tested on data from a second hospital to examine whether the architecture is transferable to another hospital. Results A total of 38,664 survey responses from the first hospital resulted in 127 topics and 294 n-grams. The indicator 'impact' revealed n-grams to celebrate (15.3%), improve (8.8%), and monitor (16.7%). For hospital 2, a similar percentage of free-text responses could be labelled with a topic and n-grams. Between-hospitals, most topics (69.7%) were similar, but 32.2% of topics for hospital 1 and 29.0% of topics for hospital 2 were unique. Conclusions In both hospitals, NLP techniques could be used to categorize patient experience free-text responses into topics, sentiment labels and to define priorities for improvement. The model's architecture was shown to be hospital-specific as it was able to discover new topics for the second hospital. These methods should be considered for future patient experience analyses to make better use of this valuable source of information. Show less
Bastemeijer, C.M.; Boosman, H.; Ewijk, H. van; Verweij, L.M.; Voogt, L.; Hazelzet, J.A. 2019
Purpose: In the era of value-based healthcare, one strives for the most optimal outcomes and experiences from the perspective of the patient. So, patient experiences have become a key quality... Show morePurpose: In the era of value-based healthcare, one strives for the most optimal outcomes and experiences from the perspective of the patient. So, patient experiences have become a key quality indicator for healthcare. While these are supposed to drive quality improvement (QI), their use and effectiveness for this purpose has been questioned. The aim of this systematic review was to provide insight into QI interventions used in a hospital setting and their effects on improving patient experiences, and possible barriers and promoters for QI work.Methods: Prisma guidelines were used to design this review. International academic literature was searched in Embase, Medline OvidSP, Web of Science, Cochrane Central, PubMed Publisher, Scopus, PsycInfo, and Google Scholar. In total, 3,289 studies were retrieved and independently screened by the first two authors for eligibility and methodological quality. Data was extracted on the study purpose, setting, design, targeted patient experience domains, QI strategies, results of QI, barriers, and promotors for QI.Results: Twenty-one pre-post intervention studies were included for review. The methodological quality of the included studies was assessed using a Critical Appraisal Skills Program (CASP) Tool. QI strategies used were staff education, patient education, audit and feedback, clinician reminders, organizational change, and policy change. Twenty studies reported improvement in patient experience, 14 studies of the 21 included studies reported statistical significance. Most studies (n=17) reported data-related barriers (eg, questionnaire quality), professional, and/or organizational barriers (eg, skepticism among staff), and 14 studies mentioned specific promoters (eg, engaging staff and patients) for QI.Conclusions: Several patient experience domains are targeted for QI using diverse strategies and methodological approaches. Most studies reported at least one improvement and also barriers and promoters that may influence QI work. Future research should address these barriers and promoters in order to enhance methodological quality and improve patient experiences. Show less
