ArticleJournal of the American Medical Informatics Association : JAMIA
Exploring the degree of concordance of coded and textual data in answering clinical queries from a clinical data repository.
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 27 papers, 1 of them a synthesis that pooled it.
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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, 1 synthesis or guideline pooled 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
- Rare Diseases in Hospital Information Systems-An Interoperable Methodology for Distributed Data Quality Assessments.Methods of information in medicine · 2023Article
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- Developing a Data Quality Standard Primer for Cardiovascular Risk Assessment from Electronic Health Record Data Using the DataGauge Process.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- A method for extracting electronic patient record data from practice management software systems used in veterinary practice.BMC veterinary research · 2016Article
- Overcoming the Challenges of Unstructured Data in Multisite, Electronic Medical Record-based Abstraction.Medical care · 2016Article
- Social Support, Postpartum Depression, and Professional Assistance: A Survey of Mothers in the Midwestern United States.The Journal of perinatal education · 2015Article
- Applied Use of Composite Quality Measures for EHR-enabled Practices.EGEMS (Washington, DC) · 2015Article
- Can an electronic health record system be used for preconception health optimization?Maternal and child health journal · 2014Article
- Preparing Electronic Clinical Data for Quality Improvement and Comparative Effectiveness Research: The SCOAP CERTAIN Automation and Validation Project.EGEMS (Washington, DC) · 2013Article
- Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research.Journal of the American Medical Informatics Association : JAMIA · 2013Review
- Identification of methicillin-resistant Staphylococcus aureus within the nation's Veterans Affairs medical centers using natural language processing.BMC medical informatics and decision making · 2012Article
- Derivation and validation of automated electronic search strategies to identify pertinent risk factors for postoperative acute lung injury.Mayo Clinic proceedings · 2011Article
- Why "What Data Are Necessary for This Project?" and Other Basic Questions are Important to Address in Public Health Informatics Practice and Research.Online journal of public health informatics · 2011Article
- Electronic laboratory data quality and the value of a health information exchange to support public health reporting processes.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2011Article
- Quantifying clinical data quality using relative gold standards.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2010Article
- Analyzing the effect of data quality on the accuracy of clinical decision support systems: a computer simulation approach.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2006Article
- Narrative notes in a nursing information system (NIS).Proceedings. AMIA Symposium · 2001Article
- An electronic health record based on structured narrative.Journal of the American Medical Informatics Association : JAMIAArticle
- Acute infections in primary care: accuracy of electronic diagnoses and electronic antibiotic prescribing.Journal of the American Medical Informatics Association : JAMIAArticle
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4 authors.
Funding
Abstract
objectiveTo query a clinical data repository (CDR) for answers to clinical questions to determine whether different types of fields (coded and free text) would yield confirmatory, complementary, or conflicting information and to discuss the issues involved in producing the discrepancies between the fields.
methodsThe appropriate data fields in a subset of a CDR (5,135 patient records) were searched for the answers to three questions related to surgical procedures. Each search included at least one coded data field and at least one free-text field. The identified free-text records were then searched manually to ensure correct interpretation. The fields were then compared to determine whether they agreed with each other, were supportive of each other, contained no entry (absence of data), or were contradictory.
resultsThe degree of concordance varied greatly according to the field and the question asked. Some fields were not granular enough to answer the question. The free-text fields often gave an answer that was not definitive. Absence of data was most logically interpreted in some cases as lack of completion of data and in others as a negative answer. Even with a question as specific as which side a hernia was on, contradictory data were found in 5 to 8 percent of the records.
conclusionsUsing the data in the CDR to answer clinical questions can yield significantly disparate results depending on the question and which data fields are searched. A database cannot just be queried in automated fashion and the results reported. Both coded and textual fields must be searched to obtain the fullest assessment. This can be expected to result in information that may be confirmatory, complementary, or conflicting. To yield the most accurate information possible, final answers to questions require human judgment and may require the gathering of additional information.
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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.