Liu J, Capurro D, Nguyen A, Verspoor K. “Note Bloat” impacts deep learning-based NLP models for clinical prediction tasks. Journal of biomedical informatics. 2022 Sep 1;133:104149. https://doi.org/10.1016/j.jbi.2022.104149

“Note Bloat” impacts deep learning-based NLP models for clinical prediction tasks One unintended consequence of the Electronic Health Records (EHR) implementation is the overuse of content-importing technology, such as copy-and-paste, that creates “bloated” notes containing large amounts of textual redundancy. Despite the rising interest in applying machine learning models to learn from real-patient data, it

El-Hayek C, Barzegar S, Faux N, Doyle K, Pillai P, Mutch SJ, Vaisey A, Ward R, Sanci L, Dunn AG, Hellard ME. An evaluation of existing text de-identification tools for use with patient progress notes from Australian general practice. International Journal of Medical Informatics. 2023 May 1;173:105021. https://doiorg.simsrad.net.ocs.mq.edu.au/10.1016/j.ijmedinf.2023.105021

An evaluation of existing text de-identification tools for use with patient progress notes from Australian general practice Digitized patient progress notes from general practice represent a significant resource for clinical and public health research but cannot feasibly and ethically be used for these purposes without automated de-identification. Internationally, several open-source natural language processing tools have

Ward K, Vagholkar S, Sakur F, Khatri NN, Lau AY. Visit Types in Primary Care With Telehealth Use During the COVID-19 Pandemic: Systematic Review. JMIR Medical Informatics. 2022 Nov 28;10(11):e40469. https://doi.org/10.2196/40469

Visit Types in Primary Care With Telehealth Use During the COVID-19 Pandemic: Systematic Review Background:Telehealth was rapidly incorporated into primary care during the COVID-19 pandemic. However, there is limited evidence on which primary care visits used telehealth. Objective:The objective of this study was to conduct a systematic review to assess what visit types in primary

Liu J, Capurro D, Nguyen A, Verspoor K. Early prediction of diagnostic-related groups and estimation of hospital cost by processing clinical notes. NPJ Digit Med. 2021 Jul 1;4(1):103. https://doi.org/10.1038/s41746-021-00474-9

Early prediction of diagnostic-related groups and estimation of hospital cost by processing clinical notes As healthcare providers receive fixed amounts of reimbursement for given services under DRG (Diagnosis-Related Groups) payment, DRG codes are valuable for cost monitoring and resource allocation. However, coding is typically performed retrospectively post-discharge. We seek to predict DRGs and DRG-based case

Yin K, Coiera E, Jung J, Rohilla U, Lau AY. Consumer workarounds during the COVID-19 pandemic: analysis and technology implications using the SAMR framework. Journal of the American Medical Informatics Association. 2022 Jul 1;29(7):1244-52. https://doi.org/10.1093/jamia/ocac061

Consumer workarounds during the COVID-19 pandemic: analysis and technology implications using the SAMR framework Objective To understand the nature of health consumer self-management workarounds during the COVID-19 pandemic; to classify these workarounds using the Substitution, Augmentation, Modification, and Redefinition (SAMR) framework; and to see how digital tools had assisted these workarounds. Read More.

Surian D, Wang Y, Coiera E, Magrabi F. Using automated methods to detect safety problems with health information technology: a scoping review. Journal of the American Medical Informatics Association. 2023 Feb 1;30(2):382-92. https://doiorg.simsrad.net.ocs.mq.edu.au/10.1093/jamia/ocac220

Using automated methods to detect safety problems with health information technology: a scoping review Health information technology (HIT) can play an important role in supporting care delivery and improving patient safety.1–6 Problems with HIT however can introduce new, often unforeseen,7 modes of failure that reduce the safety and quality of clinical care and may lead to patient

Coiera E, Yin K, Sharan RV, Akbar S, Vedantam S, Xiong H, Waldie J, Lau AY. Family informatics. Journal of the American Medical Informatics Association. 2022 Jul 1;29(7):1310- 5. https://doi.org/10.1093/jamia/ocac049

Family informatics While families have a central role in shaping individual choices and behaviors, healthcare largely focuses on treating individuals or supporting self-care. However, a family is also a health unit. We argue that family informatics is a necessary evolution in scope of health informatics. To deal with the needs of individuals, we must ensure technologies account

Rohilla U, Ramarao JP, Lane J, Khatri NN, Smith J, Yin K, Lau AY. How general practitioners and patients discuss type 2 diabetes mellitus and cardiovascular diseases concerns during consultations: Implications for digital health. Digital Health. 2023 Jul;9. https://doi.org/10.1177/20552076231176162

How general practitioners and patients discuss type 2 diabetes mellitus and cardiovascular diseases concerns during consultations: Implications for digital health Increasingly, patients are expected to take care of their health outside of medical settings (i.e. self-management).1 Self-management includes the actions taken by individuals to lead a healthy lifestyle, manage their long-term condition and prevent further illness,

Lederman A, Lederman R, Verspoor K. Tasks as needs: reframing the paradigm of clinical natural language processing research for real-world decision support, Journal of the American Medical Informatics Association, Volume 29, Issue 10, October 2022, Pages 1810–1817, https://doi.org/10.1093/jamia/ocac121

Tasks as needs: reframing the paradigm of clinical natural language processing research for real-world decision support. Electronic medical records are increasingly used to store patient information in hospitals and other clinical settings. There has been a corresponding proliferation of clinical natural language processing (cNLP) systems aimed at using text data in these records to improve clinical