A Term Extraction Approach to Survey Analysis in Health Care
Refereed Conference Meeting Proceeding
The voice of the customer has for a long time been a key focus of businesses in all domains. It has received a lot of attention from the research community in Natural Language Processing (NLP) resulting in many approaches to analysing customers feedback ((aspectbased) sentiment analysis, topic modeling, etc.). In the health domain, public and private bodies are increasingly prioritising patient engagement for assessing the quality of the service given at each stage of the care. Patient and customer satisfaction analysis relate in many ways. In the domain of health particularly, a more precise and insightful analysis is needed to help practitioners locate potential issues and plan actions accordingly. We introduce here an approach to patient experience with the analysis of free text questions from the 2017 Irish National Inpatient Survey campaign using term extraction as a means to highlight important and insightful subject matters raised by patients. We evaluate the results by mapping them to a manually constructed framework following the Activity, Resource, Context (ARC) methodology (Ordenes et al., 2014) and specific to the health care environment, and compare our results against manual annotations done on the full 2017 dataset based on those categories.
The 12th Language Resources and Evaluation Conference LREC
Proceedings of The 12th Language Resources and Evaluation Conference
Digital Object Identifer (DOI):
National University of Ireland, Galway (NUIG)
Open access repository: