Application of biomedical informatics to chronic pediatric diseases: a systematic review
Bibliographic record
Abstract
BACKGROUND: Chronic diseases affect millions of children worldwide leading to substantial disease burden to the children and their families as well as escalating health care costs. The increasing trend in the prevalence of complex pediatric chronic diseases requires innovative and optimal delivery of care. Biomedical informatics applications play an important role in improving health outcomes while being cost-effective. However, their utility in pediatric chronic diseases has not been studied in a comprehensive and systematic way. The objective of this study was to conduct a systematic review of the effects of biomedical informatics applications in pediatric chronic diseases. METHODS: A comprehensive literature search was conducted using MEDLINE, the Cochrane Library and EMBASE databases from inception of each database to September 2008. We included studies of any methodological type and any language that applied biomedical informatics to chronic conditions in children and adolescents 18 years of age or younger. Two independent reviewers carried out study selection and data extraction. Quality assessment was performed using a study design evaluation instrument to appraise the strength of the studies and their methodological adequacy. Because of heterogeneity in the conditions and outcomes we studied, a formal meta-analysis was not performed. RESULTS: Based on our search strategy, 655 titles and abstracts were reviewed. From this set we identified 27 relevant articles that met our inclusion criteria. The results from these studies indicated that biomedical informatics applications have favourable clinical and patient outcomes including, but not limited to, reduced number of emergency room visits, improved knowledge on disease management, and enhanced satisfaction. Seventy percent of reviewed papers were published after year 2000, 89% of users were patients and 11% were either providers or caregivers. The majority (96%) of the selected studies reported improved outcomes. CONCLUSION: Published studies suggested positive impacts of informatics predominantly in pediatric asthma. As electronic tools become more widely adopted, there will be opportunities to improve patient care in a wide range of chronic illnesses through informatics solutions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".