ArticleInternational journal of medical informatics2017
Need of informatics in designing interoperable clinical registries.
Article in International journal of medical informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Using natural language processing to extract information from clinical text in electronic medical records for populating clinical registries: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2026Pooled it
- Data quality and patient characteristics in European ANCA-associated vasculitis registries: data retrieval by federated querying.Annals of the rheumatic diseases · 2024Pooled it
- From Conversation to Standardized Terminology: An LLM-RAG Approach for Automated Health Problem Identification in Home Healthcare.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025Article
- Modeling the Potential Impact of Missing Race and Ethnicity Data in Infectious Disease Surveillance Systems on Disparity Measures: Scenario Analysis of Different Imputation Strategies.JMIR public health and surveillance · 2022Article
- A State-of-the Art Review of SNOMED CT Terminology Binding and Recommendations for Practice and Research.Methods of information in medicine · 2021Article
- The use of SNOMED CT, 2013-2020: a literature review.Journal of the American Medical Informatics Association : JAMIA · 2021Review
- The world is not enough - the value of increasing registry data in idiopathic pulmonary fibrosis.Respiratory research · 2020Article
- Clinical Text Data in Machine Learning: Systematic Review.JMIR medical informatics · 2020Review
- Proposed minimum information guideline for kidney disease-research and clinical data reporting: a cross-sectional study.BMJ open · 2019Article
- Automated extraction of sudden cardiac death risk factors in hypertrophic cardiomyopathy patients by natural language processing.International journal of medical informatics · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Clinical registries are designed to collect information relating to a particular condition for research or quality improvement. Intuitively, informatics in the area of data management and extraction plays a central role in clinical registries. Due to various reasons such as lack of informatics awareness or expertise, there may be little informatics involvement in designing clinical registries. In this paper, we studied a clinical registry from two critical perspectives, data quality and interoperability, where informatics can play a role. We evaluated these two aspects of an existing registry, Gynecology Surgery Registry, by mapping data elements and value sets, used in the registry, to a standardized terminology, SNOMED-CT. The results showed that majority of the values are ad-hoc and only 6 of 91 procedures in the registry could be mapped to the SNOMED-CT. To tackle this issue, we assessed the feasibility of automated data abstraction process, by training machine learning classifiers, based on existing manually extracted data. These classifiers achieved a reasonable average F-measure of 0.94. We concluded that more informatics engagement is needed to improve the interoperability, reusability, and quality of the registry.
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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.