Information discovery on electronic health records using authority flow techniques

Clinical Information Retrieval: A Literature Review

Clinical information retrieval (IR) plays a vital role in modern healthcare by facilitating efficient access and analysis of medical literature for clinicians and researchers. This scoping review aims to offer a comprehensive overview of the current state of clinical IR research and identify gaps and potential opportunities for future studies in this field. The main objective was to assess and analyze the existing literature on clinical IR, focusing on the methods, techniques, and tools employed for effective retrieval and analysis of medical information. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted an extensive search across databases such as Ovid Embase, Ovid Medline, Scopus, ACM Digital Library, IEEE Xplore, and Web of Science, covering publications from January 1, 2010, to January 4, 2023. The rigorous screening process led to the inclusion of 184 papers in our review. Our findings provide a detailed analysis of the clinical IR research landscape, covering aspects like publication trends, data sources, methodologies, evaluation metrics, and applications. The review identifies key research gaps in clinical IR methods such as indexing, ranking, and query expansion, offering insights and opportunities for future studies in clinical IR, thus serving as a guiding framework for upcoming research efforts in this rapidly evolving field. The study also underscores an imperative for innovative research on advanced clinical IR systems capable of fast semantic vector search and adoption of neural IR techniques for effective retrieval of information from unstructured electronic health records (EHRs).

Supplementary Information

The online version contains supplementary material available at 10.1007/s41666-024-00159-4.

Semantic Web Technologies for Sharing Clinical Information in Health Care Systems

Introduction:

Semantic Web (SW) technologies is capable of facilitating the management and sharing of knowledge and promote semantic interoperability among healthcare information systems.

Aim:

This article is designed to provide an overview of the SW technologies.

Methods:

This article was performed based on a literature review and Internet search through scientific databases such as PubMed, Scopus, Web of Science and Google Scholar.

Result:

The literature on SW addresses the technical and content aspects of SW technologies including description of ontology, interoperability standards in SW, creating ontology, types of ontologies, ontology editors, ontologies in healthcare.

Discussion:

The discussion on this forum aims to help understand the benefits of SW technologies in healthcare.

Conclusion:

SW promotes a shift from the “syntactic” level to the “semantic” level of services, applications, and people and finally to pragmatic level by sharing knowledge among clinicians, researchers and healthcare providers.

Information discovery on electronic health records using authority flow techniques

BACKGROUND

As the use of electronic health records (EHRs) becomes more widespread, so does the need to search and provide effective information discovery within them. Querying by keyword has emerged as one of the most effective paradigms for searching. Most work in this area is based on traditional Information Retrieval (IR) techniques, where each document is compared individually against the query. We compare the effectiveness of two fundamentally different techniques for keyword search of EHRs.

METHODS

We built two ranking systems. The traditional BM25 system exploits the EHRs' content without regard to association among entities within. The Clinical ObjectRank (CO) system exploits the entities' associations in EHRs using an authority-flow algorithm to discover the most relevant entities. BM25 and CO were deployed on an EHR dataset of the cardiovascular division of Miami Children's Hospital. Using sequences of keywords as queries, sensitivity and specificity were measured by two physicians for a set of 11 queries related to congenital cardiac disease.

RESULTS

Our pilot evaluation showed that CO outperforms BM25 in terms of sensitivity (65% vs. 38%) by 71% on average, while maintaining the specificity (64% vs. 61%). The evaluation was done by two physicians.

CONCLUSIONS

Authority-flow techniques can greatly improve the detection of relevant information in EHRs and hence deserve further study.