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overview My research focuses on quality of care and outcomes in treatment of chronic endocrine diseases. Our group utilizes advanced Medical Informatics technologies, including Natural Language Processing, to analyze electronic medical record data of thousands of patients to determine how we can improve care of patients with diabetes, hypertension and hyperlipidemia. Main directions of our research include: a) optimal targets and strategies in treatment of diabetes and hypertension b) adverse reactions to medications in chronic disease c) lifestyle counseling in chronic illness in real-life medical practice d) relationship of electronic documentation to patient outcomes
One or more keywords matched the following items that are connected to Turchin, Alexander
Item TypeName
Academic Article Reducing unintended consequences of e-prescribing on the path to nuanced prescriptions.
Academic Article I am Not Dead Yet: Identification of False-Positive Matches to Death Master File.
Academic Article Identification of patients with diabetes from the text of physician notes in the electronic medical record.
Academic Article The use of electronic medication reconciliation to establish the predictors of validity of computerized medication records.
Academic Article A Weighty Problem: Identification, Characteristics and Risk Factors for Errors in EMR Data.
Academic Article Using regular expressions to abstract blood pressure and treatment intensification information from the text of physician notes.
Academic Article Bridging the chasm: effect of health information exchange on volume of laboratory testing.
Academic Article The quality data warehouse: delivering answers on demand.
Academic Article Identification of inactive medications in narrative physician notes.
Academic Article DITTO – a Tool for Identification of Patient Cohorts from the Text of Physician Notes in the Electronic Medical Record
Academic Article Identification of misspelled words without a comprehensive dictionary using prevalence analysis.
Academic Article Effect of an electronic medication reconciliation application and process redesign on potential adverse drug events: a cluster-randomized trial.
Academic Article Hypoglycemia and clinical outcomes in patients with diabetes hospitalized in the general ward.
Academic Article Development of a tool within the electronic medical record to facilitate medication reconciliation after hospital discharge.
Academic Article Comparison of information content of structured and narrative text data sources on the example of medication intensification.
Academic Article Comparative evaluation of accuracy of extraction of medication information from narrative physician notes by commercial and academic natural language processing software packages.
Academic Article Computational analysis of non-adherence and non-attendance using the text of narrative physician notes in the electronic medical record.
Academic Article DITTO - a tool for identification of patient cohorts from the text of physician notes in the electronic medical record.
Academic Article Lexical concept distribution reflects clinical practice.
Academic Article Identification of documented medication non-adherence in physician notes.
Academic Article Identification of inactive medications in narrative medical text.
Academic Article Design and implementation of an application and associated services to support interdisciplinary medication reconciliation efforts at an integrated healthcare delivery network.
Concept Medical Records
Concept Medical Records Systems, Computerized
Concept Medical Record Linkage
Grant Monitoring Intensification of Treatment for Hyperglycemia and Hyperlipidemia
Grant Identification of patients with diabetes at high risk for treatment failure
Grant Natural Language Processing to Study Epidemiology of Statin Side Effects
Grant Identification of Patients with Low Life Expectancy
Search Criteria
  • Medical Records
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.