Identifying suicidal behavior among adolescents using administrative claims data.

PURPOSE: To assess the safety of psychotropic medication use in children and adolescents, it is critical to be able to identify suicidal behaviors from medical claims data and distinguish them from other injuries. The purpose of this study was to develop an algorithm using administrative claims data to identify medically treated suicidal behavior in a cohort of children and adolescents. METHODS: The cohort included 80,183 youth (6-18 years) enrolled in Tennessee's Medicaid program from 1995-2006 who were prescribed antidepressants. Potential episodes of suicidal behavior were identified using external cause-of-injury codes (E-codes) and ICD-9-CM codes corresponding to the potential mechanisms of or injuries resulting from suicidal behavior. For each identified episode, medical records were reviewed to determine if the injury was self-inflicted and if intent to die was explicitly stated or could be inferred. RESULTS: Medical records were reviewed for 2676 episodes of potential self-harm identified through claims data. Among 1162 episodes that were classified as suicidal behavior, 1117 (96%) had a claim for suicide and self-inflicted injury, poisoning by drugs, or both. The positive predictive value of code groups to predict suicidal behavior ranged from 0-88% and improved when there was a concomitant hospitalization but with the limitation of excluding some episodes of confirmed suicidal behavior. CONCLUSIONS: Nearly all episodes of confirmed suicidal behavior in this cohort of youth included an ICD-9-CM code for suicide or poisoning by drugs. An algorithm combining these ICD-9-CM codes and hospital stay greatly improved the positive predictive value for identifying medically treated suicidal behavior.

Evaluation and disposition of Medicaid-insured children and adolescents with suicide attempts.

OBJECTIVE: Guidelines and quality of care measures for the evaluation of adolescent suicidal behavior recommend prompt mental health evaluation, hospitalization of high-risk youth, and specific follow-up plans-all of which may be influenced by sociodemographic factors. The aim of this study was to identify sociodemographic characteristics associated with variations in the evaluation of youth with suicidal behavior. METHODS: We conducted a large cohort study of youth, aged 7 to 18, enrolled in Tennessee Medicaid from 1995 to 2006, who filled prescriptions for antidepressants and who presented for evaluation of injuries that were determined to be suicidal on the basis of external cause-of-injury codes (E codes) and ICD-9-CM codes and review of individual medical records. Chi-square tests and logistic regression were performed to assess the relationship between sociodemographic characteristics and documentation of mental health evaluation, hospitalization, and discharge instructions. RESULTS: Of 929 episodes of suicidal behavior evaluated in an acute setting, rural-residing youth were less likely to be admitted to a psychiatric hospital (adjusted odds ratio [AOR] 0.72; 95% confidence interval [CI] 0.55-0.95) and more likely to be medically hospitalized only (AOR 1.92; 95% CI 1.39-2.65). Female subjects were less likely to be admitted to a psychiatric hospital (AOR 0.55; 95% CI 0.41-0.74) and more likely to be discharged home (AOR 1.44; 95% CI 1.01-2.04). Only 40% of those discharged to home had documentation of discharge instructions with both follow-up provider and date. CONCLUSIONS: In this statewide cohort of youth with suicidal behavior, there were significant differences in disposition associated with sociodemographic characteristics.

A systematic review of validated methods for identifying Kawasaki disease using administrative or claims data.

PURPOSE: To identify and assess algorithms used to identify Kawasaki syndrome/Kawasaki disease in administrative and claims databases. METHODS: We searched the MEDLINE database from 1991 to September 2012 using controlled vocabulary and key terms related to Kawasaki disease. We also searched the reference lists of included studies. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria. Two reviewers independently extracted data regarding participant and algorithm characteristics. RESULTS: Our searches identified 177 citations of which 22 met our inclusion criteria. All studies used algorithms including International Classification of Diseases, Ninth Revision (ICD-9) code 446.1 either alone, or with evidence of intravenous immunoglobulin (IVIG) administration, or with ICD-10 code M30.3. Six studies confirmed diagnoses by medical chart review. Three of these six studies reported validation statistics, with positive predictive values of 74%, 84%, and 86%, respectively. CONCLUSIONS: All studies that reported algorithms used either the ICD-9 code 446.1 either alone, with evidence of IVIG administration or with ICD-10 code M30.3. The ICD-9 code 446.1 alone produced positive predictive values of 74%, 84%, and 86% in separate studies in Georgia and California. The sensitivity of these codes to detect Kawasaki disease is unknown, as no sampling of medical records for missed true cases of Kawasaki disease was done. Further research would be helpful to determine whether the relatively high positive predictive values found in southern California are seen elsewhere and also to evaluate the performance of other codes to identify cases of Kawasaki disease and the sensitivity of the narrow algorithms that have been used to date.