Developing and validating natural language processing algorithms for radiology reports compared to ICD-10 codes for identifying venous thromboembolism in hospitalized medical patients
Authors:
- 1 January 2022
- journal article
- research article
- Published by Elsevier in Thrombosis Research
- Vol. 209, 51-58
Abstract
No abstract availableKeywords
This publication has 32 references indexed in Scilit:
- Improving accuracy of International Classification of Diseases codes for venous thromboembolism in administrative dataThrombosis Research, 2015
- A novel method of adverse event detection can accurately identify venous thromboembolisms (VTEs) from narrative electronic health record dataJournal of the American Medical Informatics Association, 2014
- Validity of AHRQ patient safety indicators derived from ICD-10 hospital discharge abstract data (chart review study)BMJ Open, 2013
- Effect of Computerized Clinical Decision Support on the Use and Yield of CT Pulmonary Angiography in the Emergency DepartmentRadiology, 2012
- Predictive and Associative Models to Identify Hospitalized Medical Patients at Risk for VTEChest, 2011
- Updating and Validating the Charlson Comorbidity Index and Score for Risk Adjustment in Hospital Discharge Abstracts Using Data From 6 CountriesAmerican Journal of Epidemiology, 2011
- ICD-10 hospital discharge diagnosis codes were sensitive for identifying pulmonary embolism but not deep vein thrombosisJournal of Clinical Epidemiology, 2010
- Evaluation of the predictive value of ICD-9-CM coded administrative data for venous thromboembolism in the United StatesThrombosis Research, 2010
- How Valid is the ICD-9-CM Based AHRQ Patient Safety Indicator for Postoperative Venous Thromboembolism?Medical Care, 2009
- Use of Subsequent Anticoagulants to Increase the Predictive Value of Medicaid Deep Venous Thromboembolism DiagnosesEpidemiology, 1990