ArticleJournal of the American Medical Informatics Association : JAMIA2011
Collaborative search in electronic health records.
Article in Journal of the American Medical Informatics Association : JAMIA, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- Design, Implementation, and Usability of the Electronic Medical Record Search Engine (EMERSE) Tool.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2022Article
- Use, Impact, Weaknesses, and Advanced Features of Search Functions for Clinical Use in Electronic Health Records: A Scoping Review.Applied clinical informatics · 2021Article
- An exploratory study of networks constructed using access data from an electronic health record.Journal of interprofessional care · 2018Article
- TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.Scientific reports · 2017Article
- Development and empirical user-centered evaluation of semantically-based query recommendation for an electronic health record search engine.Journal of biomedical informatics · 2017Article
- Supporting information retrieval from electronic health records: A report of University of Michigan's nine-year experience in developing and using the Electronic Medical Record Search Engine (EMERSE).Journal of biomedical informatics · 2015Article
- Care episode retrieval: distributional semantic models for information retrieval in the clinical domain.BMC medical informatics and decision making · 2015Article
- Article
- An information retrieval system for computerized patient records in the context of a daily hospital practice: the example of the Léon Bérard Cancer Center (France).Applied clinical informatics · 2014Article
- Electronic health records-driven phenotyping: challenges, recent advances, and perspectives.Journal of the American Medical Informatics Association : JAMIA · 2013Article
- Describing the relationship between cat bites and human depression using data from an electronic health record.PloS one · 2013Article
- Leveraging EHR data for outcomes and comparative effectiveness research in oncology.Current oncology reports · 2012Article
- Clinical research informatics: a conceptual perspective.Journal of the American Medical Informatics Association : JAMIA · 2012Article
- Query log analysis of an electronic health record search engine.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2011Article
- Voice-dictated versus typed-in clinician notes: linguistic properties and the potential implications on natural language processing.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
objectiveA full-text search engine can be a useful tool for augmenting the reuse value of unstructured narrative data stored in electronic health records (EHR). A prominent barrier to the effective utilization of such tools originates from users' lack of search expertise and/or medical-domain knowledge. To mitigate the issue, the authors experimented with a 'collaborative search' feature through a homegrown EHR search engine that allows users to preserve their search knowledge and share it with others. This feature was inspired by the success of many social information-foraging techniques used on the web that leverage users' collective wisdom to improve the quality and efficiency of information retrieval.
designThe authors conducted an empirical evaluation study over a 4-year period. The user sample consisted of 451 academic researchers, medical practitioners, and hospital administrators. The data were analyzed using a social-network analysis to delineate the structure of the user collaboration networks that mediated the diffusion of knowledge of search.
resultsThe users embraced the concept with considerable enthusiasm. About half of the EHR searches processed by the system (0.44 million) were based on stored search knowledge; 0.16 million utilized shared knowledge made available by other users. The social-network analysis results also suggest that the user-collaboration networks engendered by the collaborative search feature played an instrumental role in enabling the transfer of search knowledge across people and domains.
conclusionApplying collaborative search, a social information-foraging technique popularly used on the web, may provide the potential to improve the quality and efficiency of information retrieval in healthcare.
Indexed as
Identifiers
What 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.