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ThinkMind // BUSTECH 2018, The Eighth International Conference on Business Intelligence and Technology // View article bustech_2018_2_10_98002


Automated Analysis of Patient Experience Text Mining using a Design Science Research (DSR) Approach

Authors:
Mohammed Bahja
Manzoor Razaak

Keywords: patient experience; sentiment analysis; text mining; topic modelling; DSR; design science research

Abstract:
Online forums of hospitals are a common method of collecting patient feedback on the healthcare received. The feedback data obtained are often free text and large which may make a manual analysis of the data difficult and time-consuming. An approach to automatically analyse patient experience data would be beneficial for the hospital staff in several ways. In this paper, a Design Science Research (DSR) paradigm based framework is proposed that is used for our ongoing research in developing solutions with an aim for an automated approach to analyse patient experience data using natural languages processing techniques such as Sentiment Analysis, Topic Modelling, and Dependency Parsing. The framework design proposed provides a three-stage iterative process wherein at each iteration the patient feedback is deeply analysed based on the outcomes obtained from the preceding ones. This iterative approach facilitates the development of a strong, effective patient feedback analysis system.

Pages: 21 to 24

Copyright: Copyright (c) IARIA, 2018

Publication date: February 18, 2018

Published in: conference

ISSN: 2308-4391

ISBN: 978-1-61208-614-9

Location: Barcelona, Spain

Dates: from February 18, 2018 to February 22, 2018

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