ArticleBMC medical informatics and decision making2024
Community perspectives on the use of electronic health data to support reflective practice by health professionals.
Article in BMC medical informatics and decision making, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Determinants of consent for electronic health information exchange: an observational retrospective study.Health research policy and systems · 2025Observational
- Methods for identifying health status from routinely collected health data: An overview.Integrative medicine research · 2025Article
- Integrating eHealth data analytics into Continuing Professional Development for medical practitioners: an ecosystemic perspective.Frontiers in medicine · 2025Article
- Improving community health centres with big data analytics: A systematic literature review on adoption.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundElectronic health records and other clinical information systems have crucial roles in health service delivery and are often utilised for patient care as well as health promotion and research. Government agencies and healthcare bodies are gradually shifting the focus on how these data systems can be harnessed for secondary uses such as reflective practice, professional learning and continuing professional development. Whilst there has been a presence in research around the attitudes of health professionals in employing clinical information systems to support their reflective practice, there has been very little research into consumer attitudes towards these data systems and how they would like to interact with such structures. The study described in this article aimed to address this gap in the literature by exploring community perspectives on the secondary use of Electronic Health Data for health professional learning and practice reflection.
methodsA qualitative methodology was used, with data being collected via semi-structured interviews. Interviews were conducted via phone and audio recordings, before being transcribed into text for analysis. Reflective thematic analysis was undertaken to analyse the data.
resultsFifteen Australians consented to participate in an interview. Analysis of interview data generated five themes: (1) Knowledge about health professional registration and professional learning; (2) Secondary uses of Electronic Health Data; (3) Factors that enable the use of Electronic Health Data for health professional learning; (4) Challenges using Electronic Health Data for health professional learning and (5) Expectations around consent to use Electronic Health Data for health professional learning.
conclusionsAustralians are generally supportive of health professionals using Electronic Health Data to support reflective practice and learning but identify several challenges for data being used in this way.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.