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Article ; Online: Natural language processing for clinical notes in dentistry: A systematic review.

Pethani, Farhana / Dunn, Adam G

2023 Volume 138, Page(s) 104282

Abstract: Objective: To identify and synthesise research on applications of natural language processing (NLP) for information extraction and retrieval from clinical notes in dentistry.: Materials and methods: A predefined search strategy was applied in EMBASE, ...

Abstract	Objective: To identify and synthesise research on applications of natural language processing (NLP) for information extraction and retrieval from clinical notes in dentistry. Materials and methods: A predefined search strategy was applied in EMBASE, CINAHL and Medline. Studies eligible for inclusion were those that that described, evaluated, or applied NLP to clinical notes containing either human or simulated patient information. Quality of the study design and reporting was independently assessed based on a set of questions derived from relevant tools including CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS). A narrative synthesis was conducted to present the results. Results: Of the 17 included studies, 10 developed and evaluated NLP methods and 7 described applications of NLP-based information retrieval methods in dental records. Studies were published between 2015 and 2021, most were missing key details needed for reproducibility, and there was no consistency in design or reporting. The 10 studies developing or evaluating NLP methods used document classification or entity extraction, and 4 compared NLP methods to non-NLP methods. The quality of reporting on NLP studies in dentistry has modestly improved over time. Conclusions: Study design heterogeneity and incomplete reporting of studies currently limits our ability to synthesise NLP applications in dental records. Standardisation of reporting and improved connections between NLP methods and applied NLP in dentistry may improve how we can make use of clinical notes from dentistry in population health or decision support systems. Protocol registration: PROSPERO CRD42021227823.
MeSH term(s)	Humans ; Natural Language Processing ; Reproducibility of Results ; Electronic Health Records ; Dentistry
Language	English
Publishing date	2023-01-07
Publishing country	United States
Document type	Journal Article ; Review ; Research Support, Non-U.S. Gov't ; Systematic Review
ZDB-ID	2057141-0
ISSN	1532-0480 ; 1532-0464
ISSN (online)	1532-0480
ISSN	1532-0464
DOI	10.1016/j.jbi.2023.104282
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Article ; Online: Will online symptom checkers improve health care in Australia?

Dunn, Adam G

The Medical journal of Australia

2020 Volume 212, Issue 11, Page(s) 512–513

MeSH term(s)	Australia ; Telemedicine ; Triage
Keywords	covid19
Language	English
Publishing date	2020-05-21
Publishing country	Australia
Document type	Editorial ; Comment
ZDB-ID	186082-3
ISSN	1326-5377 ; 0025-729X
ISSN (online)	1326-5377
ISSN	0025-729X
DOI	10.5694/mja2.50621
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Article ; Online: Characteristics of clinical trials associated with early results reporting at ClinicalTrials.gov.

Bashir, Rabia / Dunn, Adam G

Contemporary clinical trials

2022 Volume 117, Page(s) 106785

Abstract: Objective: We aimed to investigate the trial characteristics associated with earlier results reporting on ClinicalTrials.gov.: Study design and setting: We sampled interventional trials registered with ClinicalTrials.gov and examined the time from ... ...

Abstract	Objective: We aimed to investigate the trial characteristics associated with earlier results reporting on ClinicalTrials.gov. Study design and setting: We sampled interventional trials registered with ClinicalTrials.gov and examined the time from trial completion to results reporting on ClinicalTrials.gov as the event of interest. A Cox proportional hazards model was used to examine associations between the time to results reporting on ClinicalTrials.gov with funding type, intervention type, number of enrolled participants, trial phase, trial allocation status, and the year of trial completion. The model accounts for multiple risk factors simultaneously. Results: Among 102,404 completed trials, the median follow-up for the result reporting event was 18.5 months (IQR 12.7-33.6), during which time 25% (26,608 of 102,404) had results available on ClinicalTrials.gov. Compared to industry funded trials (18.1 months), non-industry trials (median 18.8 months) had results reported slower (HR 0.35, 95% CI 0.34-0.36); compared to drug trials (18.4 months) non-drug trials (19.0 months) were reported slower (HR 0.61, 95% CI 0.59-0.64); compared to trials with more than 50 participants (18.0 months), smaller trials (19.3 months) were reported slower (HR 0.97, 95% CI 0.94-0.99). Conclusion: Non-industry, non-drug, and earlier phase trials reported results on ClinicalTrials.gov more slowly if at all. Much of the efforts aimed at improving trial reporting through structured reporting on ClinicalTrials.gov have been focused on industry funded drug trials, but these results suggest that incentives and tools targeting non-industry and non-drug trials are also needed.
MeSH term(s)	Clinical Trials as Topic ; Databases, Factual ; Humans ; Proportional Hazards Models ; Registries
Language	English
Publishing date	2022-05-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	2182176-8
ISSN	1559-2030 ; 1551-7144
ISSN (online)	1559-2030
ISSN	1551-7144
DOI	10.1016/j.cct.2022.106785
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Article ; Online: Will online symptom checkers improve health care in Australia?

Dunn, Adam G

2020

Keywords	COVID-19 ; Coronavirus ; covid19
Language	English
Publishing country	au
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Will online symptom checkers improve health care in Australia?

Dunn, Adam G

2020

Abstract: In times when health services are under increasing strain, digital health technologies such as online symptom checkers appear convenient and cost‐effective tools for reducing the burden on clinics, telemedicine services, and emergency departments. In ... ...

Abstract	In times when health services are under increasing strain, digital health technologies such as online symptom checkers appear convenient and cost‐effective tools for reducing the burden on clinics, telemedicine services, and emergency departments. In practical terms, an online symptom checker is a smartphone app or web‐based form that can provide a diagnosis on the basis of a set of self‐reported symptoms. They can suggest diagnoses for a broad range of conditions with which people may present to a clinic or emergency department. When they work properly, symptom checkers should turn current practice guidelines into tools that can diagnose and triage patients at low cost. In times when health services are under increasing strain, digital health technologies such as online symptom checkers appear convenient and cost‐effective tools for reducing the burden on clinics, telemedicine services, and emergency departments. In practical terms, an online symptom checker is a smartphone app or web‐based form that can provide a diagnosis on the basis of a set of self‐reported symptoms. They can suggest diagnoses for a broad range of conditions with which people may present to a clinic or emergency department. When they work properly, symptom checkers should turn current practice guidelines into tools that can diagnose and triage patients at low cost.
Keywords	COVID-19 ; Coronavirus ; covid19
Subject code	360
Language	English
Publishing date	2020-01-01
Publishing country	au
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Online health information behaviour and its association with statin adherence in patients with high cardiovascular risk: A prospective cohort study.

Lim, Hooi Min / Ng, Chirk Jenn / Abdullah, Adina / Danee, Mahmoud / Raubenheimer, Jacques / Dunn, Adam G

Digital health

2024 Volume 10, Page(s) 20552076241241250

Abstract: Objective: Statins are effective for preventing cardiovascular disease. However, many patients decide not to take statins because of negative influences, such as online misinformation. Online health information may affect decisions on medication ... ...

Abstract	Objective: Statins are effective for preventing cardiovascular disease. However, many patients decide not to take statins because of negative influences, such as online misinformation. Online health information may affect decisions on medication adherence, but measuring it is challenging. This study aimed to examine the associations between online health information behaviour and statin adherence in patients with high cardiovascular risk. Methods: A prospective cohort study involving 233 patients with high cardiovascular risk was conducted at a primary care clinic in Malaysia. Participants used a digital information diary tool to record online health information they encountered for 2 months and completed a questionnaire about statin necessity, concerns and adherence at the end of the observation period. Data were analysed using structural equation modelling. Results: The results showed that 55.8% (130 of 233 patients) encountered online health information. Patients who actively sought online health information (91 of 233 patients) had higher concerns about statin use ( Conclusions: Our results suggest that patients with higher levels of concern about statins may be actively seeking online information about statins, and their concerns might influence how they search, what they find, and the potential to encounter misinformation. Our study highlights the importance of addressing patients' concerns about medications to improve adherence.
Language	English
Publishing date	2024-03-21
Publishing country	United States
Document type	Journal Article
ZDB-ID	2819396-9
ISSN	2055-2076
ISSN	2055-2076
DOI	10.1177/20552076241241250
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Article ; Online: K-PathVQA: Knowledge-Aware Multimodal Representation for Pathology Visual Question Answering.

Naseem, Usman / Khushi, Matloob / Dunn, Adam G / Kim, Jinman

IEEE journal of biomedical and health informatics

2023 Volume PP

Abstract: Pathology imaging is routinely used to detect the underlying effects and causes of diseases or injuries. Pathology visual question answering (PathVQA) aims to enable computers to answer questions about clinical visual findings from pathology images. ... ...

Abstract	Pathology imaging is routinely used to detect the underlying effects and causes of diseases or injuries. Pathology visual question answering (PathVQA) aims to enable computers to answer questions about clinical visual findings from pathology images. Prior work on PathVQA has focused on directly analyzing the image content using conventional pretrained encoders without utilizing relevant external information when the image content is inadequate. In this paper, we present a knowledge-driven PathVQA (K-PathVQA), which uses a medical knowledge graph (KG) from a complementary external structured knowledge base to infer answers for the PathVQA task. K-PathVQA improves the question representation with external medical knowledge and then aggregates vision, language, and knowledge embeddings to learn a joint knowledge-image-question representation. Our experiments using a publicly available PathVQA dataset showed that our K-PathVQA outperformed the best baseline method with an increase of 4.15% in accuracy for the overall task, an increase of 4.40% in open-ended question type and an absolute increase of 1.03% in closed-ended question types. Ablation testing shows the impact of each of the contributions. Generalizability of the method is demonstrated with a separate medical VQA dataset.
Language	English
Publishing date	2023-07-11
Publishing country	United States
Document type	Journal Article
ZDB-ID	2695320-1
ISSN	2168-2208 ; 2168-2194
ISSN (online)	2168-2208
ISSN	2168-2194
DOI	10.1109/JBHI.2023.3294249
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Article ; Online: How do patients with high cardiovascular risk evaluate online health information? A qualitative study.

Lim, Hooi Min / Ng, Chirk Jenn / Abdullah, Adina / Dunn, Adam G

BMC primary care

2023 Volume 24, Issue 1, Page(s) 240

Abstract: Background: People are exposed to variable health information from the Internet, potentially influencing their health decision-making and behaviour. It remains a challenge for people to discern between good- and poor-quality online health information ( ... ...

Abstract	Background: People are exposed to variable health information from the Internet, potentially influencing their health decision-making and behaviour. It remains a challenge for people to discern between good- and poor-quality online health information (OHI). This study explored how patients evaluate and determine trust in statin-related OHI in patients with high cardiovascular risk. Methods: This qualitative study used vignettes and think-aloud methods. We recruited patients from a primary care clinic who were at least 18 years old, had high cardiovascular risk and had previously sought OHI. Participants were given two statin-related vignettes: Vignette 1 (low-quality information) and Vignette 2 (high-quality information). Participants voiced their thoughts aloud when reading the vignettes and determined the trust level for each vignette using a 5-point Likert scale. This was followed by a semi-structured interview which was audio-recorded and transcribed verbatim. The transcripts were coded and analysed using thematic analysis. Results: A total of 20 participants were recruited, with age ranging from 38-74 years. Among all the high cardiovascular-risk participants, eight had pre-existing cardiovascular diseases. For Vignette 1 (low-quality information), five participants trusted it while nine participants were unsure of their trust. 17 participants (85%) trusted Vignette 2 (high-quality information). Five themes emerged from the analysis of how patients evaluated OHI: (1) logical content, (2) neutral stance and tone of OHI content, (3) credibility of the information source, (4) consistent with prior knowledge and experience, and (5) corroboration with information from other sources. Conclusion: Patients with high cardiovascular risks focused on the content, source credibility and information consistency when evaluating and determining their trust in statin-related OHI. Doctors should adopt a more personalised approach when discussing statin-related online misinformation with patients by considering their prior knowledge, beliefs and experience of statin use.
MeSH term(s)	Humans ; Adult ; Middle Aged ; Aged ; Adolescent ; Cardiovascular Diseases/epidemiology ; Hydroxymethylglutaryl-CoA Reductase Inhibitors/adverse effects ; Risk Factors ; Patients ; Information Seeking Behavior
Chemical Substances	Hydroxymethylglutaryl-CoA Reductase Inhibitors
Language	English
Publishing date	2023-11-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	2731-4553
ISSN (online)	2731-4553
DOI	10.1186/s12875-023-02182-7
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: What generative AI means for trust in health communications.

Dunn, Adam G / Shih, Ivy / Ayre, Julie / Spallek, Heiko

Journal of communication in healthcare

2023 Volume 16, Issue 4, Page(s) 385–388

Abstract: ... ...

Abstract	ABSTRACT
MeSH term(s)	Humans ; Health Communication ; Trust ; Artificial Intelligence ; Biological Transport ; Information Technology
Language	English
Publishing date	2023-12-14
Publishing country	England
Document type	Journal Article
ISSN	1753-8076
ISSN (online)	1753-8076
DOI	10.1080/17538068.2023.2277489
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Article ; Online: Experiences and influences of online health information-seeking about statin use in patients with high cardiovascular risk: a qualitative study.

Lim, Hooi Min / Ng, Chirk Jenn / Dunn, Adam G / Abdullah, Adina

Family practice

2023 Volume 40, Issue 5-6, Page(s) 796–804

Abstract: Objectives: Online health information (OHI) has been shown to influence patients' health decisions and behaviours. OHI about statins has created confusion among healthcare professionals and the public. This study explored the views and experiences of ... ...

Abstract	Objectives: Online health information (OHI) has been shown to influence patients' health decisions and behaviours. OHI about statins has created confusion among healthcare professionals and the public. This study explored the views and experiences of patients with high cardiovascular risk on OHI-seeking about statins and how OHI influenced their decision. Design: This was a qualitative study using semi-structured in-depth interviews. An interpretive description approach with thematic analysis was used for data analysis. Setting: An urban primary care clinic in Kuala Lumpur, Malaysia. Participants: Patients aged 18 years and above who had high cardiovascular risk and sought OHI on statins were recruited. Results: A total of 20 participants were interviewed. The age of the participants ranged from 38 to 74 years. Twelve (60%) participants took statins for primary cardiovascular disease prevention. The duration of statin use ranged from 2 weeks to 30 years. Six themes emerged from the data analysis: (i) seeking OHI throughout the disease trajectory, (ii) active and passive approaches to seeking OHI, (iii) types of OHI, (iv) views about statin-related OHI, (v) influence of OHI on patients' health decisions, and (vi) patient-doctor communication about OHI. Conclusion: This study highlights the changing information needs throughout patient journeys, suggesting the opportunity to provide needs-oriented OHI to patients. Unintentional passive exposure to OHI appears to have an influence on patients' adherence to statins. The quality of patient-doctor communication in relation to OHI-seeking behaviour remains a critical factor in patient decision-making.
MeSH term(s)	Humans ; Hydroxymethylglutaryl-CoA Reductase Inhibitors/therapeutic use ; Information Seeking Behavior ; Cardiovascular Diseases/drug therapy ; Cardiovascular Diseases/prevention & control ; Risk Factors ; Qualitative Research
Chemical Substances	Hydroxymethylglutaryl-CoA Reductase Inhibitors
Language	English
Publishing date	2023-03-30
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	605939-9
ISSN	1460-2229 ; 0263-2136
ISSN (online)	1460-2229
ISSN	0263-2136
DOI	10.1093/fampra/cmad034
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