ArticleJournal of the American Medical Informatics Association : JAMIA
Comparison of computerized surveillance and manual chart review for adverse events.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it, 55 citations in OpenAlex.
- Systematic review and narrative synthesis of computerized audit and feedback systems in healthcare.Journal of the American Medical Informatics Association : JAMIA · 2022Pooled it
- Data use and effectiveness in electronic surveillance of healthcare associated infections in the 21st century: a systematic review.Journal of the American Medical Informatics Association : JAMIAPooled it
- Enhanced access to healthcare utilization data through medical record review: Lessons learned from a community-based, multi-site project.Research in nursing & health · 2021Trial
- Comparing automated surveillance systems for detection of pathogen-related clusters in healthcare settings.Antimicrobial resistance and infection control · 2024Article
- Incidence, accuracy, and barriers of diagnosing healthcare-associated infections: a case study in southeast Iran.BMC infectious diseases · 2023Article
- Implementation of Machine Learning Pipelines for Clinical Practice: Development and Validation Study.JMIR medical informatics · 2022Article
- Comparing automated vs. manual data collection for COVID-specific medications from electronic health records.International journal of medical informatics · 2022Article
- Applying Machine Learning Across Sites: External Validation of a Surgical Site Infection Detection Algorithm.Journal of the American College of Surgeons · 2021Article
- Role of Artificial Intelligence in Patient Safety Outcomes: Systematic Literature Review.JMIR medical informatics · 2020Review
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- Application of Augmented Intelligence for Pharmacovigilance Case Seriousness Determination.Drug safety · 2020Article
- Statistical outbreak detection by joining medical records and pathogen similarity.Journal of biomedical informatics · 2019Article
- What Can We Learn about Fall Risk Factors from EHR Nursing Notes? A Text Mining Study.EGEMS (Washington, DC) · 2018Article
- Measuring Preventive Care Delivery: Comparing Rates Across Three Data Sources.American journal of preventive medicine · 2016Article
- Accelerating Chart Review Using Automated Methods on Electronic Health Record Data for Postoperative Complications.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- Prevalence and severity of patient harm in a sample of UK-hospitalised children detected by the Paediatric Trigger Tool.BMJ open · 2014Article
- Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration's Adverse Event Reporting System Narratives.JMIR medical informatics · 2014Article
- Retrospective cohort study of anti-tumor necrosis factor agent use in a veteran population.PeerJ · 2014Article
- Clinical research informatics: a conceptual perspective.Journal of the American Medical Informatics Association : JAMIA · 2012Article
- Real-time pharmacy surveillance and clinical decision support to reduce adverse drug events in acute kidney injury: a randomized, controlled trial.Applied clinical informatics · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveTo understand how the source of information affects different adverse event (AE) surveillance methods.
designRetrospective analysis of inpatient adverse drug events (ADEs) and hospital-associated infections (HAIs) detected by either a computerized surveillance system (CSS) or manual chart review (MCR). MEASUREMENT: Descriptive analysis of events detected using the two methods by type of AE, type of information about the AE, and sources of the information.
resultsCSS detected more HAIs than MCR (92% vs 34%); however, a similar number of ADEs was detected by both systems (52% vs 51%). The agreement between systems was greater for HAIs than ADEs (26% vs 3%). The CSS missed events that did not have information in coded format or that were described only in physician narratives. The MCR detected events missed by CSS using information in physician narratives. Discharge summaries were more likely to contain information about AEs than any other type of physician narrative, followed by emergency department reports for HAIs and general consult notes for ADEs. Some ADEs found by MCR were detected by CSS but not verified by a clinician. LIMITATIONS: Inability to distinguish between CSS false positives and suspected AEs for cases in which the clinician did not document their assessment in the CSS.
conclusionThe effect that information source has on different surveillance methods depends on the type of AE. Integrating information from physician narratives with CSS using natural language processing would improve the detection of ADEs more than HAIs.
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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.