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Open Access Research article

Positive predictive value of automated database records for diabetic ketoacidosis (DKA) in children and youth exposed to antipsychotic drugs or control medications: a tennessee medicaid study

William V Bobo1*, William O Cooper23, Richard A Epstein1, Patrick G Arbogast24, Jackie Mounsey1 and Wayne A Ray2

Author Affiliations

1 Department of Psychiatry; Vanderbilt University School of Medicine; Nashville, Tennessee USA

2 Department of Preventive Medicine; Vanderbilt University School of Medicine; Nashville, Tennessee USA

3 Department of Pediatrics; Vanderbilt University School of Medicine; Nashville, Tennessee USA

4 Department of Biostatistics; Vanderbilt University School of Medicine; Nashville, Tennessee USA

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BMC Medical Research Methodology 2011, 11:157  doi:10.1186/1471-2288-11-157

Published: 23 November 2011

Abstract

Background

Diabetic ketoacidosis (DKA) is a potentially life-threatening complication of treatment with some atypical antipsychotic drugs in children and youth. Because drug-associated DKA is rare, large automated health outcomes databases may be a valuable data source for conducting pharmacoepidemiologic studies of DKA associated with exposure to individual antipsychotic drugs. However, no validated computer case definition of DKA exists. We sought to assess the positive predictive value (PPV) of a computer case definition to detect incident cases of DKA, using automated records of Tennessee Medicaid as the data source and medical record confirmation as a "gold standard."

Methods

The computer case definition of DKA was developed from a retrospective cohort study of antipsychotic-related type 2 diabetes mellitus (1996-2007) in Tennessee Medicaid enrollees, aged 6-24 years. Thirty potential cases with any DKA diagnosis (ICD-9 250.1, ICD-10 E1x.1) were identified from inpatient encounter claims. Medical records were reviewed to determine if they met the clinical definition of DKA.

Results

Of 30 potential cases, 27 (90%) were successfully abstracted and adjudicated. Of these, 24 cases were confirmed by medical record review (PPV 88.9%, 95% CI 71.9 to 96.1%). Three non-confirmed cases presented acutely with severe hyperglycemia, but had no evidence of acidosis.

Conclusions

Diabetic ketoacidosis in children and youth can be identified in a computerized Medicaid database using our case definition, which could be useful for automated database studies in which drug-associated DKA is the outcome of interest.