ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2017
Architecting the Data Loading Process for an i2b2 Research Data Warehouse: Full Reload versus Incremental Updating.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Standardizing and Comparing Management Recommendations for Potential Drug-Drug Interactions Across Different Interaction Checkers.Drug safety · 2026Article
- A framework for sharing of clinical and genetic data for precision medicine applications.Nature medicine · 2024Article
- Clinical Data Warehousing: A Scoping Review.Journal of the Society for Clinical Data Management · 2024Article
- Development and usage of an anesthesia data warehouse: lessons learnt from a 10-year project.Journal of clinical monitoring and computing · 2023Article
- The benefit of augmenting open data with clinical data-warehouse EHR for forecasting SARS-CoV-2 hospitalizations in Bordeaux area, France.JAMIA open · 2022Article
- Incrementally Transforming Electronic Medical Records into the Observational Medical Outcomes Partnership Common Data Model: A Multidimensional Quality Assurance Approach.Applied clinical informatics · 2019Article
- The Korea Cancer Big Data Platform (K-CBP) for Cancer Research.International journal of environmental research and public health · 2019Article
- A Method for EHR Phenotype Management in an i2b2 Data Warehouse.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Research data warehouses integrate research and patient data from one or more sources into a single data model that is designed for research. Typically, institutions update their warehouse by fully reloading it periodically. The alternative is to update the warehouse incrementally with new, changed and/or deleted data. Full reloads avoid having to correct and add to a live system, but they can render the data outdated for clinical trial accrual. They place a substantial burden on source systems, involve intermittent work that is challenging to resource, and may involve tight coordination across IT and informatics units. We have implemented daily incremental updating for our i2b2 data warehouse. Incremental updating requires substantial up-front development, and it can expose provisional data to investigators. However, it may support more use cases, it may be a better fit for academic healthcare IT organizational structures, and ongoing support needs appear to be similar or lower.
Indexed as
Identifiers
29854210PMC5977612What 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.