Research hotspots analysis of patient reported outcome measurement information system based on bicomb co-word clustering

Abstract

Objective To summarize the research trends and hotspots of patient reported outcome measurement information system (PROMIS). Methods China National Knowledge Infrastructure (CNKI) and PubMed databases were systematically searched, Bicomb 2.0 software was used for data sorting and cleaning, keywords were extracted, word frequency analysis was performed on high-frequency fields, and co-word matrix was constructed. SPSS 24.0 was used for co-word clustering analysis to summarize and explore research trends and hotspots. Results The hot topic clusters of the PROMIS were patient reported outcome measures, quality of life, symptoms and psychological variables assessment. Conclusion PROMIS has become a hot issue in the field of patient health level and care quality. Future studies tend to use consensus-based health measurement tools to conduct the measurement test of PROMIS, build a systematic clinical interpretation system, and then promote its transformation and application in clinical practice.

Keywords

• patient reported outcome measurement information system， co-word cluster analysis， research hotspots