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.

Major congenital malformations after first-trimester exposure to ACE inhibitors.

BACKGROUND: Use of angiotensin-converting-enzyme (ACE) inhibitors during the second and third trimesters of pregnancy is contraindicated because of their association with an increased risk of fetopathy. In contrast, first-trimester use of ACE inhibitors has not been linked to adverse fetal outcomes. We conducted a study to assess the association between exposure to ACE inhibitors during the first trimester of pregnancy only and the risk of congenital malformations. METHODS: We studied a cohort of 29,507 infants enrolled in Tennessee Medicaid and born between 1985 and 2000 for whom there was no evidence of maternal diabetes. We identified 209 infants with exposure to ACE inhibitors in the first trimester alone, 202 infants with exposure to other antihypertensive medications in the first trimester alone, and 29,096 infants with no exposure to antihypertensive drugs at any time during gestation. Major congenital malformations were identified from linked vital records and hospitalization claims during the first year of life and confirmed by review of medical records. RESULTS: Infants with only first-trimester exposure to ACE inhibitors had an increased risk of major congenital malformations (risk ratio, 2.71; 95 percent confidence interval, 1.72 to 4.27) as compared with infants who had no exposure to antihypertensive medications. In contrast, fetal exposure to other antihypertensive medications during only the first trimester did not confer an increased risk (risk ratio, 0.66; 95 percent confidence interval, 0.25 to 1.75). Infants exposed to ACE inhibitors were at increased risk for malformations of the cardiovascular system (risk ratio, 3.72; 95 percent confidence interval, 1.89 to 7.30) and the central nervous system (risk ratio, 4.39; 95 percent confidence interval, 1.37 to 14.02). CONCLUSIONS: Exposure to ACE inhibitors during the first trimester cannot be considered safe and should be avoided.

Antibiotics potentially used in response to bioterrorism and the risk of major congenital malformations.

This study was designed to assess the association between pregnancy-related exposures to antibiotics recommended for use in the event of a bioterrorism attack and major congenital malformations. A retrospective cohort study included 30 049 infants from Tennessee Medicaid born between 1985 and 2000 identified from computerised state databases. Infants with fetal exposures to ciprofloxacin, azithromycin, doxycycline and amoxicillin (antibiotics recommended for potential bioterrorism attacks) (n = 24 521) and erythromycin (included as a positive control) (n = 2128) were compared with infants with no fetal exposure to any antibiotics (n = 3400). Major congenital malformations identified from computerised records were confirmed through medical record review. Overall, 869 (2.9%) of infants in the cohort had a confirmed major congenital malformation, with major malformations ranging from 2.5% to 3.0% among the antibiotic-specific exposure groups. No increased risk was present in multivariable analyses for any malformations and for malformations of specific organ systems. In conclusion, these data suggest that ciprofloxacin, azithromycin, doxycycline or amoxicillin use by pregnant women should not result in a greater incidence of overall major congenital malformations in infants whose mothers take these medications, though a large increase in risk cannot be ruled out.

Computerized definitions showed high positive predictive values for identifying hospitalizations for congestive heart failure and selected infections in Medicaid enrollees with rheumatoid arthritis.

PURPOSE: Computerized definitions are used to identify serious infections and congestive heart failure leading to hospitalizations in studies of medication safety. However, information on their accuracy is limited. We evaluated the ability of computerized definitions to identify these conditions as the reason for admission among patients diagnosed with rheumatoid arthritis (RA). METHODS: Medical charts were randomly selected from a systematic sample of hospitalizations for selected conditions in a cohort of Medicaid patients with RA. We calculated positive predictive values (PPVs) for computerized definitions for community-acquired pneumonia, invasive pneumococcal disease, sepsis, opportunistic mycoses, and congestive heart failure using charts reviews as gold standard and computed inter-reviewer agreement statistics. RESULTS: From 2667 hospitalizations, 336 (13%) records were selected for review. A total of 277 charts (82%) were available. Based on any discharge diagnosis, PPVs for hospitalizations due to community-acquired pneumonia, invasive pneumococcal disease, sepsis, and opportunistic mycoses were 84, 100, 80, and 62%, respectively. Restricting definitions to principal diagnoses yielded higher PPVs, 95% for pneumonia and 100% for other diagnoses. The PPV of a principal diagnosis for congestive heart failure was 100%. Inter-reviewer agreement was at least 77% for all outcomes. CONCLUSION: These findings suggest that computerized definitions can identify congestive heart failure and selected infections leading to hospitalization in Medicaid patients with RA.

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.

Validation of ICD-9 codes with a high positive predictive value for incident strokes resulting in hospitalization using Medicaid health data.

PURPOSE: To validate ICD 9 codes with a high positive predictive value (PPV) for incident strokes. The study population consisted of Tennessee Medicaid enrollees aged from 50 to 84 years. METHODS: We identified all patients who were hospitalized with a discharge diagnosis of stroke between 1999 and 2003 using highly specific codes (ischemic stroke ICD 9-CM codes 433.x1, 434 [excluding 434.x0], or 436; intracerebral hemorrhage [431]; and subarachnoid hemorrhage [430]). We reviewed medical records of a systematic sample of 250 cohort members. We randomly selected 10-30 eligible records for review from hospitals with at least 10 stroke hospitalizations. RESULTS: We reviewed 231 charts (93% of total sampled), and 205 (89%) met study criteria for new outpatient stroke. Of the 205 confirmed new outpatient strokes, 196 had stroke listed as the primary discharge diagnosis (PPV = 96%). However, 46 (23%) of the 196 patients identified by the primary diagnosis also had a remote stroke history (recurrent stroke not incident). Thus the PPV of the primary discharge diagnosis for identifying incident stroke decreased to 74%. When we applied an algorithm that restricted our population to those with stroke as the primary diagnosis and excluded patients with any prior outpatient diagnosis of stroke, we identified incident stroke events with more precision (PPV = 80%). CONCLUSION: The PPV of incident strokes was 80% using our strategy of primary discharge diagnosis and excluding prior outpatient diagnoses of stroke. Although an unknown percentage of incident strokes are missed, this group of proven incident stroke patients can be used for etiologic studies of medication exposures.