Aims: To assess the feasibility of implementing data standards in Australian primary care dietetics practices.
Methods: A mixed-methods pragmatic study of dietitians working in primary care. Using a four-point Likert scale, participants were surveyed on their baseline use of the 45 business and 33 clinical evidenced-based data standards. The content validity index and kappa statistic for each standard were calculated with a kappa statistic of 0.60-0.74 considered 'Good' and > 0.74 'Excellent'. After 4 weeks of assessment, dietitians were surveyed on the feasibility of implementing each standard and standards in total. Qualitative feedback on enablers and barriers to implementing standards was gathered and triangulated with interviews with select participants.
Results: Forty-five dietitians from every Australian state and territory completed both surveys (response rate: 100%). At baseline, 24% of business and 79% of clinical standards were rated 'Good' or 'Excellent' for current usage. The feasibility of implementing standards was rated 'Good' or 'Excellent for 86% of the business and 97% of the clinical standards. Software, training and time limitations are enablers and barriers to implementing standards.
Conclusion: Embedding data standards within dietetics practices are feasible and have broad applicability for assessing outcomes of care.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/1747-0080.12840 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
In the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Transformers (BERT) to identify privacy information and to verify the feasibility of our method for privacy protection in the Chinese clinical context. We collected and double-annotated 33,017 discharge summaries from 151 medical institutions on a municipal regional health information platform, developed a BERT-based Bidirectional Long Short-Term Memory Model (BiLSTM) and Conditional Random Field (CRF) model, and tested the performance of privacy identification on the dataset. To explore the performance of different substructures of the neural network, we created five additional baseline models and evaluated the impact of different models on performance.
View Article and Find Full Text PDFAnalysis of "Dose Accuracy and Reliability of a Connected Insulin Pen System".
J Diabetes Sci Technol
January 2025
Division of Endocrinology, Diabetes & Metabolism, Weill Cornell Medicine, New York, NY, USA.
In an article in the , Backfish and coauthors examined the dose accuracy and reliability of the Tempo Pen and Tempo Smart Button connected insulin pen system. This study sponsored by Eli Lilly and Company found that this system met the International Organization for Standardization 11608-1:2014 requirements for dose accuracy at a range of doses, as well as the data transfer requirements after all injections. While these results are very encouraging, they were based on simulated human factors data while data from a human factors validation study where individuals successfully dialed and administered correct doses was not reported.
View Article and Find Full Text PDFThe Application Value of an Artificial Intelligence-Driven Intestinal Image Recognition Model to Evaluate Intestinal Preparation before Colonoscopy.
Br J Hosp Med (Lond)
January 2025
Department of Gastroenterology, Nantong First People's Hospital, Affiliated Hospital 2 of Nantong University, Nantong, Jiangsu, China.
Artificial intelligence (AI), with advantages such as automatic feature extraction and high data processing capacity and being unaffected by fatigue, can accurately analyze images obtained from colonoscopy, assess the quality of bowel preparation, and reduce the subjectivity of the operating physician, which may help to achieve standardization and normalization of colonoscopy. In this study, we aimed to explore the value of using an AI-driven intestinal image recognition model to evaluate intestinal preparation before colonoscopy. In this retrospective analysis, we analyzed the clinical data of 98 patients who underwent colonoscopy in Nantong First People's Hospital from May 2023 to October 2023.
View Article and Find Full Text PDFThe Potential of Neonatal Organ Donation in Central Sweden.
Cell Transplant
January 2025
Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden.
Pediatric organ transplant recipients have a higher risk for wait list mortality due to the scarcity of size matched organs. Neonatal organ donation could potentially ameliorate the discrepancy but is currently not implemented in Sweden. This study aims to evaluate the potential of neonatal organ donation in central Sweden using a standardized protocol with organ specific criteria.
View Article and Find Full Text PDFSocio-economic inequalities in second primary cancer incidence: A competing risks analysis of women with breast cancer in England between 2000 and 2018.
Int J Cancer
January 2025
Inequalities in Cancer Outcomes Network (ICON) group, Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, UK.
We aimed to investigate socio-economic inequalities in second primary cancer (SPC) incidence among breast cancer survivors. Using Data from cancer registries in England, we included all women diagnosed with a first primary breast cancer (PBC) between 2000 and 2018 and aged between 18 and 99 years and followed them up from 6 months after the PBC diagnosis until a SPC event, death, or right censoring, whichever came first. We used flexible parametric survival models adjusting for age and year of PBC diagnosis, ethnicity, PBC tumour stage, comorbidity, and PBC treatments to model the cause-specific hazards of SPC incidence and death according to income deprivation, and then estimated standardised cumulative incidences of SPC by deprivation, taking death as the competing event.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!