ArticlePloS one2010
Combining free text and structured electronic medical record entries to detect acute respiratory infections.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.
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
27 citing papers in PubMed, 2 syntheses or guidelines pooled it, 48 citations in OpenAlex.
- Sepsis prediction, early detection, and identification using clinical text for machine learning: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2022Pooled it
- Extracting information from the text of electronic medical records to improve case detection: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2016Pooled it
- An Algorithm to Assess Guideline Concordance of Antibiotic Choice in Community-Acquired Pneumonia.Hospital pediatrics · 2024Article
- Monitoring the Epidemiology of Otitis Using Free-Text Pediatric Medical Notes: A Deep Learning Approach.Journal of personalized medicine · 2023Article
- A method to advance adolescent sexual health research: Automated algorithm finds sexual history documentation.Frontiers in digital health · 2022Article
- Development and validation of an automated emergency department-based syndromic surveillance system to enhance public health surveillance in Yukon: a lower-resourced and remote setting.BMC public health · 2021Article
- Smart Medical Information Technology for Healthcare (SMITH).Methods of information in medicine · 2018Article
- Development of an automated phenotyping algorithm for hepatorenal syndrome.Journal of biomedical informatics · 2018Article
- Article
- Decision support during electronic prescription to stem antibiotic overuse for acute respiratory infections: a long-term, quasi-experimental study.BMC infectious diseases · 2017Observational
- TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.Scientific reports · 2017Article
- Using electronic medical record data to report laboratory adverse events.British journal of haematology · 2017Article
- Using Anchors to Estimate Clinical State without Labeled Data.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
- Epidemic surveillance using an electronic medical record: an empiric approach to performance improvement.PloS one · 2014Article
- Emergency Medical Text Classifier: New system improves processing and classification of triage notes.Online journal of public health informatics · 2014Article
- Optimising the use of electronic health records to estimate the incidence of rheumatoid arthritis in primary care: what information is hidden in free text?BMC medical research methodology · 2013Article
- Identification of insomnia in a sleep center population using electronic health data sources and the insomnia severity index.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2013Article
- The absence of longitudinal data limits the accuracy of high-throughput clinical phenotyping for identifying type 2 diabetes mellitus subjects.International journal of medical informatics · 2013Article
- Article
- Using the electronic medical record to identify community-acquired pneumonia: toward a replicable automated strategy.PloS one · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundThe electronic medical record (EMR) contains a rich source of information that could be harnessed for epidemic surveillance. We asked if structured EMR data could be coupled with computerized processing of free-text clinical entries to enhance detection of acute respiratory infections (ARI). METHODOLOGY: A manual review of EMR records related to 15,377 outpatient visits uncovered 280 reference cases of ARI. We used logistic regression with backward elimination to determine which among candidate structured EMR parameters (diagnostic codes, vital signs and orders for tests, imaging and medications) contributed to the detection of those reference cases. We also developed a computerized free-text search to identify clinical notes documenting at least two non-negated ARI symptoms. We then used heuristics to build case-detection algorithms that best combined the retained structured EMR parameters with the results of the text analysis. PRINCIPAL
findingsAn adjusted grouping of diagnostic codes identified reference ARI patients with a sensitivity of 79%, a specificity of 96% and a positive predictive value (PPV) of 32%. Of the 21 additional structured clinical parameters considered, two contributed significantly to ARI detection: new prescriptions for cough remedies and elevations in body temperature to at least 38°C. Together with the diagnostic codes, these parameters increased detection sensitivity to 87%, but specificity and PPV declined to 95% and 25%, respectively. Adding text analysis increased sensitivity to 99%, but PPV dropped further to 14%. Algorithms that required satisfying both a query of structured EMR parameters as well as text analysis disclosed PPVs of 52-68% and retained sensitivities of 69-73%.
conclusionStructured EMR parameters and free-text analyses can be combined into algorithms that can detect ARI cases with new levels of sensitivity or precision. These results highlight potential paths by which repurposed EMR information could facilitate the discovery of epidemics before they cause mass casualties.
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.