University of Calgary Reports Findings in Healthcare Information Technology (Categorising patient concerns using natural language processing techniques)

2021 JUL 09 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- New research on Information Technology - Healthcare Information Technology is the subject of a report. According to news reporting from Calgary, Canada, by NewsRx journalists, research stated, “Patient feedback is critical to identify and resolve patient safety and experience issues in healthcare systems. However, large volumes of unstructured text data can pose problems for manual (human) analysis.”

Financial support for this research came from Western Canadian University Seed Funding.

The news correspondents obtained a quote from the research from the University of Calgary, “This study reports the results of using a semiautomated, computational topic-modelling approach to analyse a corpus of patient feedback. Patient concerns were received by Alberta Health Services between 2011 and 2018 (n=76 163), regarding 806 care facilities in 163 municipalities, including hospitals, clinics, community care centres and retirement homes, in a province of 4.4 million. Their existing framework requires manual labelling of pre-defined categories. We applied an automated latent Dirichlet allocation (LDA)-based topic modelling algorithm to identify the topics present in these concerns, and thereby produce a framework-free categorisation. The LDA model produced 40 topics which, following manual interpretation by researchers, were reduced to 28 coherent topics. The most frequent topics identified were communication issues causing delays (frequency: 10.58%), community care for elderly patients (8.82%), interactions with nurses (8.80%) and emergency department care (7.52%). Many patient concerns were categorised into multiple topics. Some were more specific versions of categories from the existing framework (eg, communication issues causing delays), while others were novel (eg, smoking in inappropriate settings). LDA-generated topics were more nuanced than the manually labelled categories. For example, LDA found that concerns with community care were related to concerns about nursing for seniors, providing opportunities for insight and action.”

According to the news reporters, the research concluded: “Our findings outline the range of concerns patients share in a large health system and demonstrate the usefulness of using LDA to identify categories of patient concerns.”

For more information on this research see: Categorising patient concerns using natural language processing techniques. BMJ Health & Care Informatics, 2021;28(1).

Our news journalists report that additional information may be obtained by contacting Zilong Zhang, Center for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada. Additional authors for this research include Paul Fairie, Adam G. D’Souza, Tara Walsh, Hude Quan and Maria J. Santana.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1136/bmjhci-2020-100274. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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