Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum Disorder.

OBJECTIVE: Cohort selection is challenging for large-scale electronic health record (EHR) analyses, as International Classification of Diseases 9th edition (ICD-9) diagnostic codes are notoriously unreliable disease predictors. Our objective was to develop, evaluate, and validate an automated algorithm for determining an Autism Spectrum Disorder (ASD) patient cohort from EHR. We demonstrate its utility via the largest investigation to date of the co-occurrence patterns of medical comorbidities in ASD. METHODS: We extracted ICD-9 codes and concepts derived from the clinical notes. A gold standard patient set was labeled by clinicians at Boston Children's Hospital (BCH) (N = 150) and Cincinnati Children's Hospital and Medical Center (CCHMC) (N = 152). Two algorithms were created: (1) rule-based implementing the ASD criteria from Diagnostic and Statistical Manual of Mental Diseases 4th edition, (2) predictive classifier. The positive predictive values (PPV) achieved by these algorithms were compared to an ICD-9 code baseline. We clustered the patients based on grouped ICD-9 codes and evaluated subgroups. RESULTS: The rule-based algorithm produced the best PPV: (a) BCH: 0.885 vs. 0.273 (baseline); (b) CCHMC: 0.840 vs. 0.645 (baseline); (c) combined: 0.864 vs. 0.460 (baseline). A validation at Children's Hospital of Philadelphia yielded 0.848 (PPV). Clustering analyses of comorbidities on the three-site large cohort (N = 20,658 ASD patients) identified psychiatric, developmental, and seizure disorder clusters. CONCLUSIONS: In a large cross-institutional cohort, co-occurrence patterns of comorbidities in ASDs provide further hypothetical evidence for distinct courses in ASD. The proposed automated algorithms for cohort selection open avenues for other large-scale EHR studies and individualized treatment of ASD.

Relationships between feeding problems, behavioral characteristics and nutritional quality in children with ASD.

Many children with autism spectrum disorders (ASD) have co-occurring feeding problems. However, there is limited knowledge about how these feeding habits are related to other behavioral characteristics ubiqitious in ASD. In a relatively large sample of 256 children with ASD, ages 2-11, we examined the relationships between feeding and mealtime behaviors and social, communication, and cognitive levels as well repetitive and ritualistic behaviors, sensory behaviors, and externalizing and internalizing behaviors. Finally, we examined whether feeding habits were predictive of nutritional adequacy. In this sample, we found strong associations between parent reported feeding habits and (1) repetitive and ritualistic behaviors, (2) sensory features, and (3) externalizing and internalizing behavior. There was a lack of association between feeding behaviors and the social and communication deficits of ASD and cognitive levels. Increases in the degree of problematic feeding behaviors predicted decrements in nutritional adequacy.