Identifying type 1 and type 2 diabetic cases using administrative data: A tree-structured model

Journal of Diabetes Science and Technology

Volumn 5, Issue 3, 2011, Pages 486-493

  Lo Ciganic, Weihsuan ^a   Zgibor, Janice C ^a   Ruppert, Kristine ^a   Arena, Vincent C ^a   Stone, Roslyn A ^a  

^a UNIVERSITY OF PITTSBURGH GRADUATE SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Administrative database; Classification and regression tree; Diabetes; Medical archival retrieval system; Negative predictive value; Positive predictive value; Sensitivity; Specificity

Indexed keywords

INSULIN; ORAL ANTIDIABETIC AGENT;

AFRICAN AMERICAN; AGE; ALGORITHM; CLASSIFICATION; COMORBIDITY; CONFERENCE PAPER; DATA BASE; DIABETIC KETOACIDOSIS; FEMALE; HUMAN; HYPOGLYCEMIC COMA; INSULIN DEPENDENT DIABETES MELLITUS; INSULIN TREATMENT; MAJOR CLINICAL STUDY; MALE; MEDICAL RECORD; NON INSULIN DEPENDENT DIABETES MELLITUS; PREDICTIVE VALUE; SENSITIVITY AND SPECIFICITY; ADOLESCENT; ADULT; AGED; ARTICLE; DECISION TREE; FACTUAL DATABASE; HOSPITAL PATIENT; INFORMATION PROCESSING; MIDDLE AGED; OUTPATIENT; REGISTER; UNITED STATES;

ADOLESCENT; ADULT; AGED; ALGORITHMS; DATA COLLECTION; DATABASES, FACTUAL; DECISION TREES; DIABETES MELLITUS, TYPE 1; DIABETES MELLITUS, TYPE 2; FEMALE; HUMANS; INPATIENTS; MALE; MEDICAL RECORDS; MIDDLE AGED; OUTPATIENTS; PENNSYLVANIA; REGISTRIES;

EID: 84855161083     PISSN: None     EISSN: 19322968     Source Type: Journal    
DOI: 10.1177/193229681100500303     Document Type: Conference Paper

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