TY - JOUR
T1 - Positive predictive value of automated database records for diabetic ketoacidosis (DKA) in children and youth exposed to antipsychotic drugs or control medications
T2 - A tennessee medicaid study
AU - Bobo, William V.
AU - Cooper, William O.
AU - Epstein, Richard A.
AU - Arbogast, Patrick G.
AU - Mounsey, Jackie
AU - Ray, Wayne A.
N1 - Funding Information:
Funding: This study was supported in part by the Agency for Healthcare Research and Quality (AHRQ), Centers for Education and Research on Therapeutics (HS1-0384), and CERT consortium grant (5U18HS017918-02). WVB is supported by a National Institute of Mental Health grant K23MH087747. RAE is supported by a National Institute of Child Health and Human Development (NICHD) grant K12HD043483. None of the funding agencies listed participated directly in the design or conduct of the study; the collection, management, or analysis of study data; or preparation, review, or approval of the manuscript. We are indebted to Leanne Balmer, RN, Vanderbilt University School of Medicine, who assisted with medical records abstraction. We gratefully acknowledge the Tennessee Bureau of TennCare and Department of Health, which provided study data.
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
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U2 - 10.1186/1471-2288-11-157
DO - 10.1186/1471-2288-11-157
M3 - Article
C2 - 22112194
AN - SCOPUS:81555237207
SN - 1471-2288
VL - 11
JO - BMC Medical Research Methodology
JF - BMC Medical Research Methodology
M1 - 157
ER -