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Barriers and facilitators to the implementation and adoption of computerised clinical decision support systems: an umbrella review protocol.
Syst Rev
January 2025
Big Data in Medicine, Carl von Ossietzky Universität Oldenburg, Ammerländer Heerstraße 114-118, 26129, Oldenburg, Germany.
Background: The implementation of computerised clinical decision support systems has the potential to enhance healthcare by improving patient safety, practitioner performance, and patient outcomes. Notwithstanding the numerous advantages, the uptake of clinical decision support systems remains constrained, thereby impeding the full realisation of their potential. To ensure the effective and successful implementation of these systems, it is essential to identify and analyse the reasons for their low uptake and adoption.
View Article and Find Full Text PDFWith big data comes big responsibility: Strategies for utilizing aggregated, standardized, de-identified electronic health record data for research.
Clin Transl Sci
January 2025
The Center for Clinical Informatics Research and Education, The MetroHealth System, Cleveland, Ohio, USA.
Electronic health records (EHRs), though they are maintained and utilized for clinical and billing purposes, may provide a wealth of information for research. Currently, sources are available that offer insight into the health histories of well over a quarter of a billion people. Their use, however, is fraught with hazards, including introduction or reinforcement of biases, clarity of disease definitions, protection of patient privacy, definitions of covariates or confounders, accuracy of medication usage compared with prescriptions, the need to introduce other data sources such as vaccination or death records and the ensuing potential for inaccuracy, duplicative records, and understanding and interpreting the outcomes of data queries.
View Article and Find Full Text PDFChatbots for breast cancer education: a systematic review and meta-analysis.
Support Care Cancer
December 2024
Cochrane Taiwan, Taipei Medical University, Taipei, Taiwan.
Background: Effective education and awareness regarding breast cancer are critical. Traditional educational methods often fail to meet the diverse information needs of patients. Patients should be provided with tailored, accessible information to improve their retention and understanding of disease-related information.
View Article and Find Full Text PDFIdentification of key factors related to digital health observational study adherence and retention by data-driven approaches: an exploratory secondary analysis of two prospective longitudinal studies.
Lancet Digit Health
January 2025
Biomedical Engineering Department, Duke University, Durham, NC, USA; Biostatistics and Bioinformatics Department, Duke University, Durham, NC, USA. Electronic address:
Background: Longitudinal digital health studies combine passively collected information from digital devices, such as commercial wearable devices, and actively contributed data, such as surveys, from participants. Although the use of smartphones and access to the internet supports the development of these studies, challenges exist in collecting representative data due to low adherence and retention. We aimed to identify key factors related to adherence and retention in digital health studies and develop a methodology to identify factors that are associated with and might affect study participant engagement.
View Article and Find Full Text PDFMapping Knowledge Landscapes and Emerging Trends for the Spread of Health-Related Misinformation During the COVID-19 on Chinese and English Social Media: A Comparative Bibliometric and Visualization Analysis.
J Multidiscip Healthc
December 2024
Clinical Research Center, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, People's Republic of China.
Background: Online health-related misinformation poses a serious threat to public health. As the coronavirus disease 2019 (COVID-19) pandemic aggravated the spread of misinformation regarding COVID-19, relevant research has surged.
Objective: To systematically summarize Chinese and English articles regarding health-related misinformation about COVID-19 on social media and quantitatively describe research progress.
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